U.S. patent application number 15/206555 was filed with the patent office on 2016-11-03 for patient permission-based mobile health-linked information collection and exchange systems and methods.
The applicant listed for this patent is Karl Arthur Sillay. Invention is credited to Karl Arthur Sillay.
Application Number | 20160317077 15/206555 |
Document ID | / |
Family ID | 51488630 |
Filed Date | 2016-11-03 |
United States Patent
Application |
20160317077 |
Kind Code |
A1 |
Sillay; Karl Arthur |
November 3, 2016 |
PATIENT PERMISSION-BASED MOBILE HEALTH-LINKED INFORMATION
COLLECTION AND EXCHANGE SYSTEMS AND METHODS
Abstract
A suite of components comprising an objective measurement
medical data collection device and a cohort database may
standardize, simplify, and objectify clinical outcomes tracking,
culminating in population health measurements within the
restorative neurosciences such as Parkinson disease individuals
diagnosed with a disease. A data collection device may comprise one
or more of a gyroscope, an accelerometer, a locator, a camera and a
magnetometer for collecting, for example, data related to tremors
experienced by the individuals diagnosed with disease and receive
instruction data responsive to evaluation of the collected data in
relation to the cohort database. A related method collects
objective measurements during phases of treatment such as
preoperative symptomatology, probabilistic atlas linked targeting
for neuromodulation, accountancy for gravitational effects of brain
shift during surgery, measurements of movement and quality of life
during supervised treatment and ongoing community and self-directed
treatment and provides feedback to implants, intelligent devices
and users thereof.
Inventors: |
Sillay; Karl Arthur;
(Nashville, TN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Sillay; Karl Arthur |
Nashville |
TN |
US |
|
|
Family ID: |
51488630 |
Appl. No.: |
15/206555 |
Filed: |
July 11, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13787406 |
Mar 6, 2013 |
9414776 |
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15206555 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 19/325 20130101;
A61N 1/3605 20130101; A61N 1/37282 20130101; A61B 5/11 20130101;
A61B 5/4842 20130101; G06F 19/321 20130101; H04L 63/10 20130101;
G16H 10/20 20180101; G16H 30/20 20180101; G16H 50/70 20180101; A61B
5/02055 20130101; A61B 5/01 20130101; A61B 5/4082 20130101; A61B
34/20 20160201; A61M 5/142 20130101; A61B 2034/2065 20160201; G16H
20/17 20180101; A61B 5/0022 20130101; A61N 1/36067 20130101; A61M
2210/0687 20130101; G16H 40/63 20180101; A61B 5/1101 20130101; A61B
5/064 20130101; A61M 25/007 20130101; A61B 5/14542 20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 5/01 20060101 A61B005/01; A61B 5/0205 20060101
A61B005/0205; A61B 5/06 20060101 A61B005/06; A61B 5/11 20060101
A61B005/11; H04L 29/06 20060101 H04L029/06; A61N 1/372 20060101
A61N001/372; A61M 5/142 20060101 A61M005/142; A61M 25/00 20060101
A61M025/00; A61B 34/20 20060101 A61B034/20; G06F 19/00 20060101
G06F019/00; A61B 5/145 20060101 A61B005/145; A61N 1/36 20060101
A61N001/36 |
Claims
1. Apparatus for intracranial surgery comprising a first catheter
adapted for penetrating the cranium and comprising a delivery
channel along its length for delivery of one of an infusion,
implanting a device and implanting an electrode, a neuro-surgical
drive for driving the catheter adapted to follow a predetermined
intraoperative trajectory from a point of cranial entry to a first
target point in the cranium, a digital imaging device for providing
at least one digital image of the cranium during the intracranial
surgery, a gravitational sensor for determining the relative
position of components of a brain within the cranium with respect
to gravity, wherein the first catheter is advanced within the
cranium and the delivery channel is actuated for one of a first
infusion, implanting a first device and implanting a first
electrode, the first catheter being advanced further for one of a
second infusion, implanting a second device and implanting a second
electrode.
2. Apparatus for intracranial surgery as recited in claim 1,
further comprising a second catheter having a different
predetermined intraoperative trajectory adapted for penetrating the
cranium at a different location and comprising a delivery channel
along its length for delivery of one of an infusion, implanting a
device and implanting an electrode.
3. Apparatus for intracranial surgery as recited in claim 1 wherein
the neuro-surgical drive comprises a micro-drive having three
degrees of freedom and a Ben-gun insert perpendicular to the
predetermined intraoperative trajectory and parallel to the
micro-drive.
4. Apparatus for intracranial surgery as recited in claim 1 wherein
the digital imaging device comprises one of a CT scan, impedance
spectroscopy, ultrasound and magnetic resonance imaging to orient
the predetermined trajectory and locating the anterior and
posterior commissure with respect to gravitational force applied to
the cranium intraoperatively responsive to the gravitational
sensor.
5. Apparatus for intracranial surgery as recited in claim 1 wherein
the gravitational sensor comprises a handheld device including one
of a gyroscope and an accelerometer.
6. Apparatus for intracranial surgery as recited in claim 4 wherein
the digital imaging device is adapted to output a three dimensional
volumetric scan of the cranium and included brain components.
7. Apparatus for intracranial surgery as recited in claim 6 for
delivery of multiple collinear fluidic infusions having a desired
predetermined three dimensional shape within the brain.
8. Apparatus for intracranial surgery as recited in claim 7 further
comprising an automatic reporting system responsive to the three
dimensional volumetric scan adapted to alert if a predefined
infusion border of the desired three dimensional shape is
reached.
9. Apparatus for intracranial surgery as recited in claim 6 wherein
a time series of three dimensional volumetric scans of the cranium
are output to a display device during the intracranial surgery for
input to a computer processor.
10. Apparatus for intracranial surgery as recited in claim 9
wherein the display device, responsive to the computer processor,
is adapted to identify a field location error associated with a
cranial implant for correction of the field location error during
the intracranial surgery.
11. Apparatus for intracranial surgery as recited in claim 9 for
delivery of a therapeutic device via the delivery channel of the
first catheter, the apparatus further comprising the computer
processor adapted for calculating three dimensional locations in
the cranium of a plurality of thin-film electrodes of the
therapeutic device.
12. Apparatus for intracranial surgery as recited in claim 9 for
delivering a plurality of collinear fluidic infusions along a
desired trajectory by successive advancement of the first catheter,
the time series of three dimensional volumetric scans as displayed
on the display device adapted to record a three dimensional
representation of the shape of the collinear fluidic infusions
within the cranium.
13. Apparatus for intracranial surgery as recited in claim 12
further comprising a three dimensional printer for real-time shaped
infusion monitoring and for providing independent control of one of
hydraulic advancement and fluidic delivery responsive to a time
series of three dimensional volumetric scans.
14. Apparatus for intracranial surgery as recited in claim 9
further comprising a computer processor and memory for recording
one of first catheter entry and target points, first catheter
impedance, first catheter pressure, and delivery channel infusion
pressure for permitting the alteration of one of fluidic flow
through the first catheter and delivery of one of a therapeutic
device and a fluidic infusion through the first catheter.
15. Apparatus for intracranial surgery as recited in claim 13, the
hydraulic advancement actuated by one of mechanical push-pull
cabling, screw rotation and hydraulic advancement by fluidic
pressure.
16. Apparatus for intracranial surgery as recited in claim 9 for
use during intracranial surgery and adapted to alter, responsive to
computer processor calculation, one of a change in delivery channel
pressure over time, regulating pressure to not exceed a maximum
delivery channel pressure and to control delivery between a minimum
and a maximum insertion with respect to a target point, the
apparatus further comprising a plurality of sensors adapted for
measuring one of body temperature, line infusate temperature, and
molecular weight of infusate for regulating rate of infusion.
17. Apparatus for intracranial surgery as recited in claim 11
wherein the plurality of thin-film electrodes comprises a thin-film
electrode array adapted to overlay a horizontally situated cortical
sulcus located in an anteroposterior location, the array for
outputting data to the computer processor and memory, the computer
processor adapted for alerting of an abnormality occurring during
the intracranial surgery and of a need for the computer processor
to alter an electrode stimulation program.
18. Apparatus for intracranial surgery as recited in claim 14, the
computer processor for deriving a resulting equation representing
an implant trajectory within the cranium and outputting a therapy
with reference to a tip of the first catheter at a center of a
target point for the therapy.
19. Apparatus for intracranial surgery as recited in claim 1
further comprising one of ultrasound, microelectrode recording and
impedance spectroscopy adapted to characterize a progression of the
advancement of the first catheter for implant or infusion delivery
system through brain tissue.
20. Apparatus for intracranial surgery as recited in claim 12
wherein the shape of the collinear fluidic infusions within the
cranium comprises a triangular arrangement of at least three
fluidic infusion clouds.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation of U. S. patent
application Ser. No. 13/787,406 filed Mar. 6, 2013, by the same
inventor(s).
TECHNICAL FIELD
[0002] Embodiments of systems and methods for health data
collection and sharing relate to the technical field of objective
medical health data collection utilizing mobile telecommunications
apparatus or an alternative device, a health-linked database
hierarchy, social networking for those diagnosed with disease, a
permission system for health-based data sharing and linked health
data exchange network for access by the diagnosed, medical
practitioners, insurance carriers, medical researchers and others
having access permission.
BACKGROUND
[0003] In today's medical environment, it is common for those
diagnosed with chronic disorders, their medical practitioners,
insurance carriers, medical researchers and scientists to have a
need to provide data to and access a common medical database
hierarchy. Subjective testing of those diagnosed is known such as
in the diagnosis and measurement of progress of, for example, those
inflicted with Parkinson disease (PD). Subjective PD testing may
comprise, for example, a timed observation and video camera
collection of the individual's moving arms and hands or other
extremities in a requested protocol to subjectively assess their
susceptibility to tremors, twitches and the like. Medical
practitioners contemporaneously collect and record time of day,
date, individual with disease data including age, gender, body
weight, height, blood pressure, environmental conditions of the
test and the like.
[0004] Subjective testing suffers from high inter-rater and
intra-rater variability depending on the chosen cohort and metric
(Larsen et al. 1983, van Hilten et al. 1994). By use of the term
cohort in the specification and claims is a group of similarly
situated individuals such as a cohort of individuals diagnosed with
the same disease, a disease cohort or a cohort of caregivers or
others. Subjective measurements further require the burden of
observer resources for administration and data capture. Taken
together, these factors in combination with a perceived potential
for lowering clinical trial burden through lower required sample
size and the ability to engage those individuals diagnosed with
disease in their home environment have lead to improvements in
application specific design offerings for measurements (Mamorita et
al. 2009, Great Lakes Neurologic (video and accelerometer), APDM
(gyroscope/magnetometer/accelerometer), Mcnames et al. "SYSTEM FOR
DATA MANAGEMENT, ANALYSIS, AND COLLABORATION OF MOVEMENT DISORDER
DATA." U.S. patent application Ser. No. 12/763,538, filed Apr. 20,
2010.), Cambridge Neurologics (a device with an accelerometer),
QMAT (Voice, accelerometer, pegboard, and paddles) and techniques
(Boraud et al. 1997, Dunnewold et al. 1997 & 1998, Salarian et
al. 2007, Yokoe et al. 2009, Albers 2011) and early trials to
associate treatment with objective measures (Hoff et al. 2001,
Papapetropoulos et al. 2008, Taylor et al. 2009, Rusk et al. 2011),
including in the home environment (Goetz et al. 2009).
[0005] With Apple's introduction of wireless telecommunication
devices circa 2010-2011, Apple provided hardware within these
devices including but not limited to an on-board camera, GPS
access, a magnetometer, an accelerometer, time and date data and a
gyroscope. In particular, Apple's CMMotionManager is an object
gateway to raw gyroscope, magnetometer and accelerometer data,
which has been used, for example, by camera users, for example, for
attitude data. A poster prepared in 2011 by Dr. Sillay for
presentation in Europe shows x, y, and z coordinate data from a
gyroscope collected from such an Apple device that may be collected
and graphed to comprise objective hand movement data for use with
the known Uniform Parkinson's Disease Rating Scale (UPDRS),
discussed further below, to quantify Parkinson's disease symptoms
such as tremors with and without brain stimulation via programmed
implants, as will be discussed further below. Other devices from
other vendors, such as smart phones, smart watches and tablets, for
example, using the Android operating system, and devices designed
for computer games such as the Microsoft XBOX and Kinect, can also
be used.
[0006] Efforts at objective measurement of disease are beginning to
take hold with experimental (QMAT) and commercially available
devices (Great Lakes Neurological, APDM) and software to make use
of commercially available devices (Navigated Technologies / iMovePD
motion data logger). While early efforts are underway to include
such technologies in clinical trials (UW clinical trial, UCSF
clinical trial), randomized clinical trial results benchmarking
objective measures are lacking.
[0007] On the other hand, such objective data collection, while
gatherable, may not be easily entered into known databases. The
medical records database hierarchy must be periodically updated to
even receive collected data from newly developed
subjective/objective data collection. The data entry screens do not
permit the entry of such new data or new diagnostic or progress
testing, for example, by cameras or other devices. Hurdles to
improvements in care of those diagnosed include, but are not
limited to the acquisition, processing, and reporting of aggregate
health related data from disparate sources. Data sources include
multiple medical providers, caregivers, and individuals diagnosed
with a disease, and each source typically utilizes a different data
store, implying possibly different fields, formats, access methods,
and security, privacy and data sharing legal and technical
protocols.
[0008] Indeed, technical and legal barriers exist for the
successful navigation of ideas to fruition, in particular, the
migration of data across barriers among the individual with
disease, the medical practitioner, the database hierarchy and the
surrounding medical and individual with disease community.
Referring briefly to FIG. 1 (Prior Art), there is depicted an
overlapping hierarchy similar to a Venn diagram on the left whereby
the University of Wisconsin 105 is shown distinct from the
University of Wisconsin Medical Foundation 110, the University of
Wisconsin Hospital and Clinics 115, the medical doctor 120, a given
device for data collection or disease control 155 (such as a body
implant for drug release or electrode stimulation or a gyroscope
motion data collector of an iPhone) which may comprise a memory and
transceiver, clinic nurse practitioners 165, a development team
145, biomedical engineering (BME) students 150, clinic nurses 170
and individual with disease care 160 shown. To the right of FIG. 1
is seen an IP designee 125 interfacing with a non-University of
Wisconsin (UW) tech transfer entity 130 to a software distribution
platform 135 to a further overlapping Venn diagram showing a
individual with disease user 140, the device 180 and its software
170 tied back to the UW hospital and clinics 115. Clearly in such a
complex medical and individual with disease environment with
impediments to data flow, the hierarchy and legal and technical
structure tends to most importantly limit individual with disease
development and progress if not fail to promote research and
development of cures, an individual with disease social network,
the need for an insurance carrier to collect individual with
disease data and the like.
[0009] Parkinson's disease is used in the context of many
neurological diseases or other conditions in the present discussion
by way of example of many such diseases or conditions ranging from
epilepsy, Alzheimer's disease, multiple sclerosis, essential
tremor, dystonia, normal-pressure hydrocephalus, spinal and gate
disorders to stroke. Parkinson's disease (PD), alone, impacts the
quality of life of one per cent of the adult population over sixty
years of age.
[0010] A Parkinson's disease questionnaire (PDQ) is known that is
computer-based that a user with disease may navigate and
particularly complete to quantify and qualify their symptoms and
other data at a given date and time. Referring briefly to FIG.'s 5
and 6 (Prior Art), there are shown a symptoms questionnaire (FIG.
5) comprising, for example, diagnosis date 510, first symptom 520,
onset of medical treatment and what treatment 530, first use of
levodopa or related drug regimen 540, date of significant impact of
PD on individuals with diseases' work/home life 550 and first
consideration of surgical therapy such as a neuromodulator implant
560. Per FIG. 6, (Prior Art), examples of demographic data
collection on the PDQ may include Zip code 610, name of primary
care physician 620, neurologist 630, and neurosurgeon 640.
[0011] A biometrics information telecommunications software
application is known from US Published Patent Application No.
2012/0148115 of Jun. 14, 2012 and is but one example of a plethora
of software applications that have been developed for mobile
telecommunications devices, in this case, to collect biometrics
data such as photographs of individuals, fingerprints, location and
other data with respect to a particular time and date, location and
particular user such as a first responder. PD burden is often
measured by medical clinicians who subjectively grade the degree,
for example, of forearm slowness and pronation/supination movement
(a movement similar to screwing in a light bulb) and rated
according to a known Uniform Parkinson's Disease Rating Scale
(UPDRS) described a quarter century ago (Fahn, et al. 1987). In the
clinical setting, the individual diagnosed with disease may be
captured on camera as the person goes through the movements in
response to the requests of the clinicians. The current method of
data inclusion in medical databases for the most part excludes or
is not permissive of accepting video data, let alone the subjective
data collection such as UPDRS data or the PDQ data completed by the
individual with disease. Expanding the use of clinical measures
(CM) such as the UPDRS to address population health questions is
stymied by rater variability, subjectivity, and provider burden of
effort.
[0012] An exemplary medical database is one known from US Published
Patent Application No. 2008/0208914, published Aug. 28, 2008, in
which it is suggested that an individual with disease (IWD) portal
may provide IWD access to their medical records. Referring briefly
to FIG. 6, FIG. 15 and FIG. 24, the IWD's doctor may also have
unrestricted access to her individual with disease's records 1570.
But this doctor 2410 may not have access to another doctor's
records for a similarly situated individual with disease 2420. Per
FIG. 15 and discussion within the published application, the
individual data of those diagnosed with disease may be permissively
uploaded (with some healthcare data protection) to such entities as
the Center for Disease Control (for controlling a possible
epidemic), the National Institutes of Health 1520, state level and
university level databases for other purposes such as developmental
purposes. However, this suggested ideal may not be practical unless
the databases are compatible, legally and technically.
[0013] Surgical interfaces to medical databases are likewise
lacking. These databases may be doctor based, hospital based,
maintained at a state level, a regional level or a national or
(federal) National Institutes of Health (NIH) or Center for Disease
Control (CDC) level 1520. The databases in the hierarchy may not be
capable of data sharing, retrieval and query by parties that could
use the data for research, progress of individuals with disease,
social networking, insurance or other purposes as in FIG. 24.
[0014] Neuromodulation is known in restorative neuroscience and
functional neurosurgery whereby, by example, a deep brain
stimulator may be implanted in the human brain. FIG. 2 is a PRIOR
ART data flow diagram for a candidate for neuromodulation (DZ) 250
as an example of a disease being managed with best medical therapy
(BMT) 240 or treatment 220 (in this case with deep brain
stimulation [DBS] and the comparative effectiveness or efficacy
being compared with both subjective measures (SM) 230 and objective
measures (OM) 210 in a manual setting of today. Referring briefly
to FIG. 3 (Prior Art), there is shown a data flow chart for an
individual diagnosed with disease who may benefit from
neuromodulation. At step 300, preoperative data is collected at a
healthcare provider appointment and entered into a protected health
record. At step 310, surgical planning data is collected involving
the neurosurgeon and the neurosurgeon's team and maintained at a
surgical planning station. At step 320, data from the surgery
itself may be collected including photographic or video data and
monitored and stored individual with disease data such as blood
pressure and brain activity during surgery. At step 330, the
individual with disease has their new neuromodulator programmed
according to a best projection of how the neuromodulator should
perform. At step 340, there is an opportunity for medical and
community follow-up of those with disease and feedback as to how
the individual diagnosed with disease and subsequently implanted
with a neuromodulator is performing with the programmed
neuromodulator and whether different programming is appropriate,
for example, in combination with L-dopa or another drug regimen or
combination of drug therapies as is known in the art.
[0015] Yet, data from the surgical room where the implant is
performed are not automatically transferred to an electronic health
record, which might include a surgical plan, subjective or
objective documentation of the procedure, or video record of the
surgery itself In the case of neuromodulation in the restorative
neurosciences and functional neurosurgery to implant a deep brain
stimulator, the preoperative data held in the electronic medical
record are not automatically transferred to the surgical planning
station. Data surrounding the implantation of a deep brain
stimulator are not transferred from the surgical environment. The
current method of data inclusion at many centers is manual entry,
photography or scanning of documents, and manual upload of these
items into the electronic health record if available. This type of
surgery is performed by a neurosurgeon; however, follow-up is
performed by a neurologist who in many cases was not present during
the pre-op evaluation or in the operating room. When the
neurologist meets the individual with disease for the first time in
clinic for programming of the deep brain stimulator, in most cases,
only limited data are available to the neurologist to assist in the
programming of an enormous number of possible combinations of the,
for example, quadrapolar implant device having a wide frequency
amplitude and pulse width selection available. Further difficulties
exist in measuring the outcome of these cohort members of
individuals with disease after treatment. No readily available
system allows the remote aggregation and integration of mobile
medical device-acquired objective measurements along with diary
data of these treated individuals with disease in the home
environment. There is limited ability to aggregate and track
factors, which may lead to an improvement in surgical technique or
individual with disease selection across either the entire or a
selected cross-section of the population of individuals with
disease treated. There is currently a delay in the meaningful use
of the electronic health record for specialty care.
[0016] Referring briefly to FIG. 83, the typical current processes
include manual data entry 8322, measurements of head position,
photography of surgical sites, scanning of documents and manual
upload to an electronic health record. Database software may be
incapable of performing data analysis such as might be accomplished
by known content-based image recognition, data parsing and analysis
of the manually input data, database query and retrieval and the
like to effectively provide, for example, researchers or clinicians
with the data they need to assist a given individual with disease
or the population of all individuals with disease sharing the same
disease or disorder. Moreover, surgical follow-up may not be
recorded in any database except at a paper level, or it may be
recorded by a neurologist unfamiliar or not present at the original
surgery or pre-operation individual with disease evaluation. There
is limited ability to aggregate and track factors, which may lead
to an improvement in surgical technique or individual with disease
selection across either the entire or a selected cross-section of
the population of individuals diagnosed with a disease treated.
There is currently a delay in the meaningful use of the electronic
health record (EHR) for specialty care (FIG. 4 showing a delay
centered in 2012 between primary and specialty care). Significant
hurdles exist to increased adoption of currently known therapies,
compliance, and clinical translational research within PD and other
restorative neurosciences ailments. Challenges in measuring,
aggregating, reporting, and querying the rich dataset surrounding
treatments within the restorative neurosciences as well as other
areas of research or individual with disease tracking or treatment
within neuroscience are subject to improvement with emerging
technology.
[0017] Current systems designed for use by individuals diagnosed
with disease and physicians to handle even a limited subset of the
described data are not designed to answer important questions,
which may improve healthcare. An example of this is there is no way
in aggregate form for individuals diagnosed with a disease to track
their outcomes, the battery life of their personal devices
(medical, communication or combination), adverse side effects of
the therapy or other important factors.
[0018] A system is known from US Published Patent Application No.'s
2012/0029369 published Feb. 2, 2012; 2009/0012417 published Jan. 8,
2009 and 2002/0126731 whereby a passive microwave receiver may
obtain internal body temperature at various depths by frequency
selection (with no active microwave transmission which may be
dangerous) from known "black-body" radiation. Moreover, measures of
blood flow and pressure may be possible from this apparatus in
combination with known automatic apparatus for collection of blood
pressure.
[0019] Social networks are known such as Facebook and Linked-In
whereby individuals may share information about themselves with
others. Friend and business relationships may develop from
participation. Disease support groups have sites but these sites
are typically anonymous and impersonal and may not permit similarly
situated individuals to electronically participate outside of a
support group.
[0020] In view of the above, there is clearly a need in the art for
improved systems and methods for collecting objective data (as well
as subjective data collected in a medical environment) of an
individual diagnosed with disease at home or at a doctor's office.
Given the foregoing, what are needed are systems, methods and
computer program products that provide a framework to define a
model-based multidimensional medical record that overcomes legal
and technical hurdles, may span multiple computer systems,
networks, and organizations, and supports new objective data
collection as well as provides an input for sharing such
multi-media data collection as photographic data and video/movie
data as well as provide an opportunity for networking of those
diagnosed with disease, disease treatment development, insurance
carrier access, medical practitioner access, developer access and
the like.
SUMMARY
[0021] This summary is provided to introduce a selection of
concepts. These concepts are further described below in the
Detailed Description. This summary is not intended to identify key
features or essential features of the claimed subject matter, nor
is this summary intended as an aid in determining the scope of the
claimed subject matter. The present invention meets the
above-identified needs by providing devices, systems, methods and
computer program products that provide a framework for the creation
of objective (as well as subjective) medical records, editing,
manipulation and shared use of medical records among those
diagnosed with disease, doctors, insurance carriers, researchers
and the like without technical and legal impediments. Specific
example embodiments of apparatus and methods disclosed provide for
an instrument or device to assist in the collection of objective
data, for example, utilizing an accelerometer, a gyroscope, a
camera, a time of day and date clock, a GPS location system,
environmental sensors and human biological data collection such as
an internal temperature, blood flow rate and the like.
[0022] Novel methods and technologies, such as wearable, hand-held,
or portable devices such as smart phones, tablets, or specialized
or customized devices that can sense and record movement and can be
programmed to record such movement and utilize communications links
to transmit the recorded data to a server for processing and/or
storage or communicate with other devices such as implants for
brain stimulation or drug release, allow the potential to improve
the health of a disease cohort by quantifying results of health
care intervention. While a wireless communications link such as
WiFi, 3G, or 4G wireless systems provide is preferred, it is also
possible to implement the disclosed features using tethered
devices, or devices that can be intermittently tethered, or devices
having a removable storage or memory component such as a SD memory
card, where the removable component can be inserted into or
attached to another computer or device, in order to establish a
communications link to a server or another device. Such technology
empowers the research from the "bench" to the population of at-home
individuals, for example, those diagnosed with PD. For example,
FIG. 7 is a graph of Sample Objective Measure Data collectable from
a device indicating a demonstration of improvement in post
operative function solely based upon an objective measure (UPDRS
motor score from 0-4) with deep brain stimulator (DBS) on 700 or
off 710.
[0023] The inventive technologies can be used in a clinical setting
with supervision, or at a residence or other facility by the
individual diagnosed with disease (unsupervised) or with the
assistance of a caregiver, family member, or a trusted person. The
possibility is great for advancing this modality rapidly through
collaboration with regional, national, and international databases
(NPF QII, Okun et al. 2010; neurosurgical N2QOD, McGirt et al.
2013). These databases or computer servers (step 10310, 10315 and
10320 by example; FIG. 103) may provide secure data collection
portals that are accessible to and controlled by the individual
diagnosed with disease 10355, as well as be available in a clinical
or other controlled setting. They may also provide repositories for
data collection software and/or device tuning software or data that
can be downloaded to and executed or used on an implantable,
wearable, hand-held, or portable device step 10370 used by or for
the individual diagnosed with disease. The combination of the
databases or computer servers and either the implantable, wearable,
hand-held, or portable device or a computer such as a laptop or
desktop computer, can be used by the individual diagnosed with
disease, a caregiver, relative, or assistant, or supervisory
personnel to control privacy and sharing settings to enable another
person or organization to access objective, subjective or
multimedia data, either for the purpose of evaluation or treatment
of the individual with disease, or with appropriate controls on the
release of information that could undesirably identify the
individual with disease for research purposes.
[0024] According to the present invention, servers, computers, or
computer systems may contain data and implement privacy and sharing
policies (FIG. 17) that are controlled by the individual with
disease or an individual with disease's representative. Such
server-controlled databases provide a mechanism for the transfer of
valuable information among the cohort of caregivers and service
providers that address the needs of each individual with disease.
Systems such as these may provide a broader spectrum of information
to teams who perform surgical procedures, including, for example,
diary entries, records of the administration of medications, and
records from other medical facilities that have been requested by
the individual with disease and which the individual with disease
has agreed to share with a different provider (FIG. 17). Such
systems may also make information from surgical procedures
available post-operation, for example to better enable adjustment
or tuning of surgical implants or to better coordinate
post-operative therapies. The utilization of devices capable of
communicating with surgical implants or prostheses capable of
receiving communication (client to client) offers the opportunity
to both capture data relating to the operation of the implants and
to tune or adjust the operation of the implant to better meet
individual with disease needs and accommodate the health and
recovery profile of the individual with disease. Server systems can
be interconnected in a secure manner to enable sharing and
aggregation of information across, for example, geographic regions,
groups of individuals diagnosed with a disease served by specific
medical providers, and members of individual with disease networks
or insurer organizations. The aggregation of individual with
disease data with appropriate safeguards to ensure the deletion or
obfuscation, for example by encryption, of identifying information
may provide valuable data for research.
[0025] In accordance with the principles of the present invention,
permissions from individuals diagnosed with disease may be
aggregated to obtain, aggregate, and report healthcare data. These
individual with disease-based permissions may be finely tuned to be
compatible with existing healthcare information laws such as the
Health Insurance Portability and Accountability Act (HIPPA) and the
Health Information Technology for Economic and Clinical Health
(HITECH) Act. Within the appropriate permissions, all participants
within the data exchange can make structured queries. While
structures of permission-based data exchange have been previously
described, an electronic individual with disease affidavit of
permission, according to the present invention, provides a secure
ability for individuals diagnosed with a disease also to query
within the system hierarchy.
[0026] The present invention proposes home monitoring of progress
via instructed utilization of mobile and other objective data
collection devices in combination with use of the known PDQ (but in
electronic, secure form). An individual with disease navigates the
questionnaire using a computer or other client device that can
communicate with a computer server process such as a web server.
Appropriate security to safeguard private or privileged data is
essential. This paradigm provides the ability to deliver and gather
content using both wireless devices such as a tablet or mobile
phone, wired devices such as a computer or (tethered) tablet and
specialty devices that may be implanted or coupled to body
extremities such as hands and feet.
[0027] Subjective measures (SM) used by a clinician as clinician
measures (CM) or by others outside the clinical environment (where
the measures are frequently described as diary data) may be
combined with objective measures (OM) obtained from the individual
with disease at home or a medical office. In the case of PD,
clinician measured (CM) and scored (CMS) Unified Parkinson's
Disease Rating Scale (UPDRS) data may be combined with objective
measures (OM) obtained at home or office over time to develop an
individual with disease history. The opportunity to develop and
validate easy to use, quantitative objective measures (OM)
resulting in objective measures scores (OMS) for the longitudinal
evaluation of conditions such as for PD is suggested by the present
invention. OMS may quantify impact of therapies to the clinic and
accelerate translation of new treatments by lowering the
administrative burden of disease monitoring. Healthcare OMS are now
possible with emerging low-cost, connected, hand-held mobile
devices capable of running healthcare Apps (mHealth devices). Such
objective measurement devices with communications capability having
specialty sensing and detection (examples include the iPhone, iPod
touch, Android phones and tablets, wearable appliances such as
smart watches or other physically small computerized devices, and
similar devices which may be implantable) have extensive and
accurate capabilities for recording individual with disease
movement and communicating OM. Such emerging technology can enable
widespread adoption by a community of OMS (for example, of movement
in PD) efficiently and at low cost. By extension of the example, in
PD, objective measurements have been related to severity of
disease. Tremor and bradykinesia (slowness) in PD, for example, are
captured with video (for example, using subjective analysis, UPDRS
subscore, and a blinded rater) and with the device (objective
analysis).
[0028] Preliminary data indicate that forearm angular velocity for
the pronation-supination movement (similar to rapidly simulating
"screwing in a light bulb" while holding the device (or a special
device may be implanted) directly correlates with
clinician-provided UPDRS scores, and is highly reproducible even
without an experienced clinician's guidance and subjective measure.
Increased maximum wrist rotation speed correlates with lower UPDRS
scores. In individuals diagnosed with a disease undergoing
deep-brain stimulation (DBS) surgery at UW-Health, peak angular
velocity increases with stimulator activation and also correlates
with the UPDRS. Adding OMS to the study of PD individuals diagnosed
with a disease promises to improve research studies by decreasing
inter- and intra-rater variability and likely decreasing the number
of individuals diagnosed with a disease required for vetting an
emerging therapy. Medical and surgical therapies provided at
luminary medical centers reduce suffering in the restorative
neurosciences and movement disorders, yet objective measures (OM)
of the "health" of the disease cohort (such as a cross-section of
PD individuals diagnosed with a disease selected by region, age, or
ethnicity) as a result of these therapies are lacking.
[0029] The current embodiments aim to standardize, simplify, and
objectify clinical outcomes tracking, culminating in population
health measurements of PD individuals diagnosed with a disease in
the home and in the setting of support group-based periodic
meetings. The disclosed methods allow an objective test to be
performed using devices available within the individual with
disease and provider community and allow unprecedented ease of
participation for longitudinal testing over time. Adding OM to the
study of PD individuals diagnosed with a disease promises to
improve research studies by decreasing inter- and intra-rater
variability and likely decrease the number of individuals diagnosed
with a disease required vetting an emerging therapy.
[0030] Objective measures (OM) from devices described herein
augment clinician-measured scores (CMS) using either or both
clinic-acquired and community-acquired measurements. OM data allow
monitored and unmonitored measurements in the home environment by
participants/caregivers of those with varied disease burdens.
Clinical validation and translational comparative effectiveness
research (CER) through a community registry environment facilitate
population-based monitoring and optimization of targeted therapy in
the community. In the setting of a fluctuating disease process such
as PD, a clear understanding of individuals diagnosed with a
disease' progression with medical or surgical intervention may
require unrealistically high individual with disease participation
or individual with disease numbers exceeding those available at a
given treatment center using historical outcomes measures.
[0031] Meaningful use of consumer devices in the home environment
will provide the following: the data flow for standard of care
treatment augmenting the following workflow for treatment; an
individual with disease reporting to the neurology or neurosurgery
clinic, and a relatively inexpensive test (for example, to account
for the time value of a rater's time) and taking around 30-60
minutes being performed with paper or electronic based or manual
scoring and being scored according to the training and judgment of
the rater. With the embodied disclosure, SM and OM are available
and shared across the clinical, home, and community environments
according to the wishes of the participant. For example, in
addition to the results of the SM from the clinic, OM of movement,
distance traveled, average speed, time walking, time sleeping, time
with dyskinesias, time with an inability to walk well,
participation in exercise activities as marked by GPS location of
the facility pr individual user and by activity level are able to
be identified, analyzed, exchanged, uploaded, transferred, logged,
and "liked" by other members of the community in an ability to
influence the end behavior and therefore improvement in coping with
or treating disease. PD efficacy trials of OM devices will report
the clinician scored Unified Parkinson's Disease Rating Scale
(UPDRS) and be matched by the individual user performing their own
test and obtaining a personal UPDRS score at home.
[0032] Further features and advantages of the present invention, as
well as the structure and operation of various aspects of the
present invention, are described in detail below with reference to
the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0033] The features and advantages of the present invention will
become more apparent from the detailed description set forth below
when taken in conjunction with the drawings in which like reference
numbers indicate identical or functionally similar elements.
[0034] FIG. 1 is a PRIOR ART diagram of a typical complex
hierarchical technical and legal permission system, in particular,
involving the University of Wisconsin, associated organizations,
the individual with disease, the doctor and others.
[0035] FIG. 2 is a PRIOR ART data flow diagram for a candidate for
neuromodulation (DZ) as an example of a disease being managed with
best medical therapy (BMT) or treatment (in this case with deep
brain stimulation [DBS] and the comparative effectiveness or
efficacy being compared with both subjective measures (SM) and
objective measures (OM).
[0036] FIG. 3 is a PRIOR ART data flow diagram demonstrating data
flow for neuromodulation from pre-authorization to surgical
planning data to data from the surgery to neuromodulation
programming to follow up within the community.
[0037] FIG. 4 is a suggested diagram depicting the rate of adoption
of meaningful use of the electronic health record (EHR) depicting
electronic health record technology adoption lagging that for
specialty care.
[0038] FIG. 5 is a PRIOR ART drawing of a typical Parkinson's
Disease Questionnaire (PDQ) wherein FIG. 5 requests symptom
data.
[0039] FIG. 6 is a PRIOR ART drawing of a typical Parkinson's
Disease Questionnaire (PDQ) wherein FIG. 6 requests demographics
data.
[0040] FIG. 7 is a graph of Sample Objective Measure Data
indicating a demonstration of improvement in post operative
function solely based upon an objective measure.
[0041] FIG. 8 depicts a wirelessly linked mobile health device with
multiple on-board sensors such as an accelerometer, gyroscope,
camera, microphone, speaker and position determination capability
such as GPS or processed location data based upon wireless network
access.
[0042] FIG. 9 depicts wireless transfer of user entered and
objectively measured data to a managed host or web environment.
[0043] FIG. 10 depicts a wirelessly linked mobile health device
displaying User Displayed Content via wireless delivery.
[0044] FIG. 11 specifies a novel data acquisition method for
obtaining clinically meaningful maximum effort data in measuring
forearm bradykinesia. Both the protocol and sample data are
shown.
[0045] FIG. 12 is a first of two figures depicting methods for
preparing objectively measured data from the forearm bradykinesia
test for further analysis.
[0046] FIG. 13 is the second of the two figures depicting methods
for preparing objectively measured data from the forearm
bradykinesia test for further analysis.
[0047] FIG. 14A and FIG. 14B are figures demonstrating the clinical
trial design of a currently active investigation and analysis trial
of the objective measure of forearm bradykinesia wherein FIG. 14B
is a continuation of an objective measures scores (OMS) assessments
flowchart of FIG. 14A. The depicitions of FIG. 14A and 14B show the
control and treatment groups and, as this is a neuromodulation
trial, the examination of the treatment group on and off
therapeutic neurostimulation.
[0048] FIG. 15 depicts the organization of data exchange of a
community micro-research registry figure with a description of data
and permissions algorithms for data exchange partners.
[0049] FIG. 16 provides details of a DATA TRANSMISSION PROTOCOL for
transmitting an encoded permissions affidavit along with data and
with an identifier and a checksum.
[0050] FIG. 17 identifies a reporting permissions matrix for use by
participants within a registry to allow selectivity of data
reporting to government, public nonprofit, investigator initiated
research, and commercial partners.
[0051] FIG. 18 demonstrates connectivity to a data repository in
the simplest case of a single site integration of external
community acquired health data.
[0052] FIG. 19 depicts data interoperability in the simplest case
of exchange between a single hospital electronic medical record
containing protected health information and a community/home
environment containing subjective and objective measures, both with
reporting.
[0053] FIG. 20 depicts an EHR individual with disease interaction
workflow beginning with the entry of an individual with disease
subjective and objective data to extracting the ratings and
analytics from the registry to reporting and exporting summary
reports.
[0054] FIG. 21 depicts a Timeline Report detailing metrics and
milestones on the timeline from the time of diagnosis to medical
and surgical interventions to end of disease planning.
[0055] FIG. 22 depicts an Individual Performance Report detailing a
method of providing an individual performance report in relation to
a cohort an automated fashion.
[0056] FIG. 23 depicts a Change with Intervention Report of a
metric or metrics over time facilitating the visualization of
disease burden before and after an intervention in order to measure
results the intervention or depict them visually.
[0057] FIG. 24 depicts a method of aggregating data according to
use permissions in response to a registry data inquiry made to the
various sites or repositories facilitated by the exchange module
and permission-based exchange paradigm.
[0058] FIG. 25 depicts a Permission Based Exchange paradigm
detailing specifics including the interaction between the query and
the encoded permissions as well as the data and the allowance of
exported data to be aggregated.
[0059] FIG. 26 depicts an Individual with disease Outcomes Report
in response to an input query and generation of a disease cohort
database from EHR. In this case, the report depicts results for
deep brain stimulation designed to be viewed by the clinician and
rapidly demonstrate individual with disease progress.
[0060] FIG. 27 depicts a Demographic Report detailing the treatment
cohort demographic in response to a query from a requesting client
device. In this example, a gender and age report, the report allows
for rapid viewing of age and gender based relationship to the
number of procedures or treatments performed, in this case,
surgical implants with automated identification of outliers within
the automatically generated cohort.
[0061] FIG. 28 depicts an Implant Trajectory Report detailing the
Anatomic Target XYZ, and Entry XYZ in a specific reference frame
(in this case AC/PC space). Relative location of the implant within
the aggregate cohort is displayed and reported, facilitating the
automated calculation of the target and implant direction vectors
of the cohort.
[0062] FIG. 29 depicts a sample Consent Report detailing the status
of consents for 1) individual with disease to individual with
disease collaboration, 2) videotaping and photography, and 3)
inclusion within research paradigms and data exchange.
[0063] FIG. 30 depicts a representative Surgery Report detailing
surgical procedures by: identification code, name, surgery date,
type of surgery, surgical target, and presence of specific
associated tests such as diffusion tensor imaging on MM
scanning.
[0064] FIG. 31 depicts a representative Calculated Active X/Y/Z
report depicting the automatically calculated location of active
therapy as derived from the last visit for programming, location of
the implant to neurostimulator's target of nerve stimulation
programming parameters such as activated contacts, voltage/current,
pulse width, rate, impedance measurements, device voltage, current
measurements, outcomes measurements (objective and subjective) as
well as the targeted entry points for director direction vector
calculation as well as the active stimulation location based upon
computational methods of determining the center of active
stimulation and other notes and or linkages to other types of
implant data such as infusion data.
[0065] FIG. 32 represents an automated error checking of electrode
implant location. This report provides a listing and graphical
representation of implant or therapy delivered by location and
provides automated target averaging with automated detection of
outliers.
[0066] FIG. 33 depicts Active Implants within the 3D framework of
certain brain internal landmarks. This report lists numerically
displays separately graphically the location and stimulation
parameters of an active implant. In the case of protein, gene
therapy or other therapy relevant metrics are substituted.
[0067] FIG. 34A and FIG. 34B depict the top and bottom portions,
respectively, of a representative outcomes report for the display
of relevant outcomes measures with and without the combination of
medication and neurostimulation according to an evaluation
protocol.
[0068] FIG. 35 is representative population listing report for
significant metrics regarding active implants. This report may be
generated from a cohort database listing of impedance and device
statistics for automated battery life and impedance change
detection to determine the health of population of
neurostimulators.
[0069] FIG. 36 depicts a conference report form example.
Collaborators from neurosurgery, neurology, physical therapy, and
other collaborators interact in a collaborative setting to
automatically share information pertinent to workflow.
[0070] FIG. 37 outlines individual with disease milestones relevant
to collaborators in operative neuromodulation and perioperative
management generated from a cohort database.
[0071] FIG. 38 is a diagram depicting the overall workflow from a
scheduler screen allowing rapid visualization of pending,
scheduled, incomplete, and completed.
[0072] FIG. 39A-D displays a representative screen capture of a
surgery schedule report for pending surgeries, wherein FIG. 39A
shows a scheduler query screen; FIG. 39B represents a patients
query screen; FIG. 39C represents a Reports tab screen and FIG. 39D
represents a UPDRS Pool tab screen.
[0073] FIG. 40 is the first of two depictions of an example surgery
record prepared for scheduling, including diagnostic studies,
intraoperative metrics, targeting information, complications,
implant or therapy given and outcomes measures. This figure
contains the scheduling and a portion of a diagnostic section.
[0074] FIG. 41 is the second of two depictions of an example
surgery record prepared for scheduling, including diagnostic
studies, intraoperative metrics, targeting information,
complications, implant or therapy given and outcomes measures. This
figure contains the remainder of the diagnostic section, the
intraoperative, metrics, target information, complications,
implants and outcomes sections.
[0075] FIG. 42 is a diagram of the sections of a surgery record.
This record shows further detail of the involved items in a
representative surgery record (general, preop, diagnostic studies,
intraop, metrics, charter information, complications and
implants).
[0076] FIG. 43 is a diagram of the Surgical Record in detail
(Surgical Record Data Structure 1) describing stereotactic
information in a representative reference space (frame space)
including in reference to internal brain landmarks (such as ACPC
space) and in reference to micro-drive orientation and array
information.
[0077] FIG. 44 is a second diagram of the Surgical Record in detail
(Surgical Record Data Structure 2) describing target structure
metrics for assigning to the cohort (such as brain third
ventricular width, trajectory distance to ventricular wall, and
distance to other internal landmarks).
[0078] FIG. 45 is a third diagram of the Surgical Record in detail
(Surgical Record Data Structure 3) describing data associated with
a particular surgical procedure (functional MRI MRI with diffusion
tensor imaging, CT scans, EEG, standard anatomical MM brain scan,
standard CT, x-ray, angiography, myelography TCD duplex ultrasound,
SPECT, WADA, MEG, TMS, PET).
[0079] FIG. 46 is depicts Surgical Record Data Structure 4
outlining preoperative surgical data relevant to a surgery for
neuromodulation.
[0080] FIG. 47 depicts Surgical Record Data Structure 5 outlining
surgery data for diagnostic studies and relevant guiding data for
the surgery.
[0081] FIG. 48 depicts Surgery Record Data Structure
6--data--Intraoperative--outlining surgery and implant data
associated with the extra-cranial portion of the implant.
[0082] FIG. 49 depicts Surgery Record Data Structure
7--Data--Complications--outlining complications envisioned within
the data structure.
[0083] FIG. 50 depicts Surgery Record Data Structure 8--Programming
Information--Including Active Implants/Contacts and Outcome
Measures outlining information regarding the neurostimulator device
programming and relevant outcomes measures.
[0084] FIG. 51 provides details of Surgical Record Data Structure 9
containing outcomes of ratings description for pre- and post-op, on
and off medication evaluations.
[0085] FIG. 52 depicts an onboard device envisioned within a mobile
communications medical device according to an aspect of the present
invention.
[0086] FIG. 53A is a diagram depicting identification data,
exemplary control data of a device or server and a checksum
according to an aspect of the present invention.
[0087] FIG. 53B is a diagram depicting data acquisition or transfer
from a device or server according to an aspect of the present
invention comprising identification data, actual data and a
checksum.
[0088] FIG. 54 is a parasagittal image depicting the guidance by
magnetic resonance imaging (MRI) of an insert into a specific brain
location, quantified by calculations within MRI space according to
an aspect of the present innvention.
[0089] FIG. 55 is a lateral "scout" image derived from a computed
tomography (CT) scan of the head after implantation of cortical
surface electrodes implanted for the purpose of epilepsy monitoring
and seizure localization similar to a lateral radiograph of the
electrode montage according to an aspect of the present invention.
The cross-hairs depict a given electrode in the reference volume CT
space.
[0090] FIG. 56 is a surface image of an array of electrodes
overlying the surface of the brain with visualization of underlying
surface anatomy of the brain including cortical vasculature and
sulcal/gyral patterns according to an aspect of the present
invention.
[0091] FIG: 57 is an axial image of the resulting computed
tomography (CT) of an implanted cortical grid montage of surface
electrodes allowing precise localization of the electrode contact
in reconstructed 3D CT space according to an aspect of the present
invention.
[0092] FIG. 58 is an image depicting volume reconstruction from a
computed tomography (CT) scan obtained after cortical grid montage
implantation of surface electrodes according to an aspect of the
present invention. Electrodes are segmented from the underlying
cortical anatomy and a 3D reconstruction performed allowing both
rapid visualization and identification of electrode locations
within 3D CT space.
[0093] FIG. 59 is an image depicting bilateral infusions within the
putamen with location of infusion catheter tip measured before
contrast infusion and volume of infusion characterized and measured
as previously described according to an aspect of the present
invention.
[0094] FIG. 60 comprises images depicting a frontal approach in
three views: FIG. 60A, FIG. 60B and FIG. 60C to the putamen
according to an aspect of the present invention.
[0095] FIG. 61 is an image depicting multiple stacked infusions
along a single trajectory in an agarose gel model of the brain
according to an aspect of the present invention.
[0096] FIG. 62A is an image depicting a frontal approach to the
putamen for multiple or shaped infusion payloads through a single
approach to fill relatively large portions of the putamen according
to an aspect of the present invention.
[0097] FIG. 62B and FIG. 62C are further images depicting a
strategy of multiple infusion catheters creating a varied and
tailored 3D parenchymal infusion according to an aspect of the
present invention.
[0098] FIG. 63 is an image depicting the addition of a
mobile-tracked: Gravitational Input for Image Guidance in the Mill
Surgical Environment according to an aspect of the present
invention.
[0099] FIG. 64 is an image depicting a method for computing the
gravitational direction vector with respect to internal and
external landmarks in preparation for analysis such as with
intracranial brain shift according to an aspect of the present
invention.
[0100] FIG. 65 depicts Implant Variance within the 3D framework of
certain brain internal landmarks. This report lists numerically
displays separately graphically the location and stimulation
parameters of an active implant. In the case of protein, gene
therapy or other therapy relevant metrics are substituted.
[0101] FIG. 66 depicts the effects upon the resolution of
intracranial brain shift on implanted brain devices (Sillay et al.
2012) according to an aspect of the present invention.
[0102] FIG. 67 depicts the mismatch between the calculated and
measured location of a brain implant with respect to internal brain
landmarks such as the space defined by the anterior commissure,
posterior commissure, and a midline point near the cranial vertex
according to an aspect of the present invention.
[0103] FIG. 68 is depicts the mismatch between the calculated and
measured location of a brain implant with respect to brain implant
landmarks such as the parallel distance (depth) of the intended
implant trajectory.
[0104] FIG. 69 depicts the mismatch between the calculated and
measured location of a brain implant with respect to brain implant
landmarks such as the radial or perpendicular distance (radial
error) with respect to the intended implant trajectory according to
an aspect of the present invention.
[0105] FIG. 70 is a volume reconstruction of the implanted
electrodes from an acquired computed tomography image obtained at
the time of second sided surgery following the first sided
implantation according to an aspect of the present invention.
[0106] FIG. 71 depicts the gravitational force measurement with a
wireless linked mobile medical device for the purpose of
referencing the relative gravity component of a stereotactic frame
according to an aspect of the present invention.
[0107] FIG. 72 depicts components and optical tracking devices with
the mobile device able to provide gravitational input into the
alignment stem position via tracking from the same optical camera
comprising devices of A) an MM safe tracking camera; B) a bone
mounted aiming device; C) a trajectory guide; D) an inserted
device; E) a trajectory guide top view and F) an accelerometer for
a gravity reference input.
[0108] FIG. 73 depicts a first of two mini-frames showing a
relatively recumbent position of a patent's skull vertex when
undergoing a surgery requiring cranial opening_and the devices A),
B), C), D) and F) of FIG. 72 and further including E) gravitational
force and G) the operating room (OR) table according to an aspect
of the present invention.
[0109] FIG. 74 depicts the second of two mini-frames showing a
relatively upright position of a patient's skull vertex when
undergoing a surgery requiring cranial opening_and the devices A),
B), C), D) of FIG. 72 and further including E) gravitational force
and F) the operating room (OR) table according to an aspect of the
present invention.
[0110] FIG. 75 depicts an "in box" for rating scales or data with
known identifiers, however uncertainty regarding a data item
identity according to an aspect of the present invention.
[0111] FIGS. 76A, 76B, 76C, and 76D depict a representative patient
data input and report summary screen for the restorative
neurosciences wherein the IPG serial numbers have been
intentionally redacted but may be displayed according to an aspect
of the present invention.
[0112] FIG. 77 is a diagram showing the navigation of a user within
the representative database for the restorative neurosciences
according to an aspect of the present invention.
[0113] FIG. 78 is the first of two screen captures from a
representative database for the restorative neurosciences
specifically for the logging of outcomes measures and device
programming for neurostimulation according to an aspect of the
present invention.
[0114] FIG. 79 is the second of two screen captures from a
representative database for the restorative neurosciences
specifically for the logging of outcomes measures and device
programming for neurostimulation.
[0115] FIG. 80 is the first of three screen captures from a
representative database for the restorative neurosciences
specifically for the logging of events and data surrounding the
implantation of a neurostimulator or similar device.
[0116] FIG. 81A, with FIG. 80 representing the first screen, is the
second of three screen captures from a representative database for
the restorative neurosciences specifically for the logging of
events and data of a surgical treatment summary surrounding the
implantation of a neurostimulator or similar device.
[0117] FIG. 81B is the third of three screen captures from a
representative database for the restorative neurosciences
specifically for the logging of events and data of a surgical
treatment summary surrounding the implantation of a neurostimulator
or similar device according to an aspect of the present
invention.
[0118] FIG. 82 is a representative screen capture from an active
stimulation calculator for determining the offset of the origin and
shape of volume of tissue stimulated given an implant location and
active contacts for a quadrapolar array according to an aspect of
the present invention.
[0119] FIG. 83 is a representative workflow diagram for the
processing of brain implant data for quality control and lead
location versus clinical outcome analysis.
[0120] FIG. 84 is a representative listing of representative
reports within a representative database for the restorative
neurosciences.
[0121] FIG. 85 is a representative visualization of the centroid of
a trajectory, the outer limit of a device, a range of therapy
delivered, and a surrounding representative area of interest for
therapy delivery. This figure includes the location and direction
vector describing these items at a given time of a number of
identified points (3D reduced to 2-D and a single coordinate plane
for the purposes of visualization).
[0122] FIG. 86 is a figure diagraming the navigation of a user
within a generated representative cohort database for the
restorative neurosciences for the purposes of adding events and
implant data.
[0123] FIG. 87 is a representative figure allowing the association
of neurostimulation devices to neurostimulator pulse generators and
displaying summary target information about the location of the
neurostimulator device given trajectory information from the
surgery and from images taken after the completion of the surgery
for localization purposes.
[0124] FIGS. 88A, 88B, and 88C are screen captures from a
representative database for the capturing of perioperative
trajectories and associated metrics for identifier UW (University
of Wisconsin) 0123456789.
[0125] FIG. 89 is a representative screen capture depicting the
post implantation location, errors, and notes associated with the
procedure.
[0126] FIG. 90 is a representative screen capture depicting the
addition of a new neurostimulator pulse generator device and
associated linkages to brain implants.
[0127] FIG. 91 is a diagram depicting the onboard devices
envisioned within an ideal client device.
[0128] FIG. 92 depicts an individual with disease interacting with
a data exchange server environment with automated objective measure
extraction and with automated reporting.
[0129] FIG. 93 is depicts the simultaneous acquisition and
disbursement of data to be exchanged based upon permissions and to
separate sources.
[0130] FIG. 94 depicts multiple communications along a data
exchange bus according to an aspect of the present invention.
[0131] FIG. 95 depicts navigation steps within the implant section
of the representative database for defining the location of
implants or delivered therapy.
[0132] FIG. 96 is an example data exchange mapping matrix for users
to allow de-identified reporting to be identified or identified
data to be exchanged with healthcare providers.
[0133] FIG. 97 depicts synthetic data with 10 cycles of a sinusoid
having an amplitude of 10.
[0134] FIG. 98 depicts the Synthetic Data Set 1 in First Randomly
Chosen Coordinate System according to an aspect of the present
invention.
[0135] FIG. 99 depicts the Synthetic Data Set 2 in Second Randomly
Chosen Coordinate System according to an aspect of the present
invention.
[0136] FIG. 100 depicts the Error Between Original and
Reconstructed Maximum Signals--Case 1.
[0137] FIG. 101 depicts the Error Between Original and
Reconstructed Maximum Signals--Case 1.
[0138] FIG. 102 depicts a Computer Server Platform according to an
aspect of the present invention.
[0139] FIG. 103 depicts A Patient Based Mobile Health Linked
Information Exchange Supporting Client/Mobile and Implantable
Devices according to an aspect of the present invention.
[0140] FIG. 104 is a figure of a Sitting versus Standing Patient
showing locations where a mobile communications device for
transmitting OM and SM data or receiving control data may be
located according to an aspect of the present invention.
[0141] FIG. 105A is a drawing of wearable computers including a
neck worn device and a larger view of a typical
computer/transceiver device and FIG. 105B depicts other locations
on a body of a user for the device and onboard capabilities of a
wireless mobile health communications device and an exemplary
device according to an aspect of the present invention.
[0142] FIG. 106 depicts a method of sensing and transmitting
triangulation foot pressure via pressure transducers at locations
at the bottom of a foot and movement via a sock/glove for, for
example, gait correction and sensing movement according to an
aspect of the present invention.
[0143] FIG. 107 depicts a method of initiating events on the client
device via transmissions from a server in response to received OM
and SM data according to an aspect of the present invention.
[0144] FIG. 108A, B, and C depict an exemplary RNF database and RNF
codes providing the ability of field, report, task, and other
similar aggregate protocols and events to be queried and initiated
via a central codebook or lookup table.
[0145] FIG. 109 is a figure demonstrating a coronal MRI image
during the first of two collinear infusions of 0.017% bromophenol
Blue/2 mM gadoteridol within a formalin fixed human brain using the
MRI Interventions 14 guage SmartFlow Catheter.
[0146] FIG. 110 is a figure demonstrating a coronal MRI image
during the second of two collinear infusions of 0.017% bromophenol
Blue/2 mM gadoteridol within a formalin fixed human brain using the
MRI Interventions 14 guage SmartFlow Catheter.
[0147] FIG. 111 is a figure of catheter line pressure during the
infusion depicted in FIG. 109. Copyrights are claimed for all
figures of the Brief Description of the Drawings which are not
labeled Prior Art as of the date of filing of the present
application and their date of publication as a published US
application (if not earlier published).
DETAILED DESCRIPTION
[0148] Aspects of the present invention will now be described with
reference to FIGS. 1-109 wherein the first digits of a reference
numeral are intended to indicate the figure number wherein the
depicted element first appears. An aspect of the present invention
is to enable the individual with disease or their caregiver or
assistant to record objectively measured OM data, in addition to
subjectively measured (SM) data such as a diary of medications
taken or other observations, and to control the selective and
secure dissemination and sharing of the data to other parties such
as clinical or hospital facilities, pharmacies, insurance
providers, support or peer groups, and researchers. The invention
utilizes personal devices such as smart phones (FIG. 8) or other
wearable computers (FIG. 105), which may contain data acquisition
components such as gyroscopes, accelerometers, a universal time
clock, a GPS receiver coupled to the clock, and wireless network
transceivers (FIG. 52, FIG. 102), to acquire/transmit data using
these data acquisition components or other components such as a
touch screen 1020, physical or virtual buttons, a keyboard, a
temperature sensor, or an antenna (all collectively referred to
herein as "input components") and provide control data to an
individual user or an associated wireless device. Once the data are
acquired, or intermittently as the data are acquired, the data can
be transferred to a server computer using wired or wireless
networks or other communications media such as a SD memory card and
control data returned developing a special cohort database
permissively from EHR records in disbursed databases with
permissive data sharing.
[0149] Some input components, such as an antenna, may facilitate
communications with devices attached to or embedded within an
individual with disease in order to either collect data from the
device or to adjust parameters of the device to effect improvements
in the individual with disease's comfort, well-being, health, or
prognosis. For example, an embedded device can be a deep brain
stimulator or an implanted device to monitor neural activities,
levels or concentrations of oxygen or other dissolved gases,
nutrients, neurotransmitters or neurotransmitter by-products,
proteins, and therapeutic agents, temperature, or pressure within a
selected region of the brain or a muscle. As a second example, an
attached device can be a handheld device or device attached with
straps using Velcro or elastic to a limb 1140, the device
containing at least one of an accelerometer and a gyroscope 820,
which may be mechanical or optical and may be implemented using
micro-electronic mechanical systems (MEMS), where the device
executes a program stored in its memory to measure, for example,
rectilinear, angular, or both rectilinear and angular acceleration,
velocity, or position in one or more degrees of freedom as a
function of time. When the individual with disease performs a
defined movement or sequence of movements, such as movements of a
hand or walking, the attached device and executing program locally
or remotely controlled (FIG. 053A) can capture OM data that can be
used to monitor the progress or treatment of disease in the
individual with disease, and with a communications interface such
as a wireless interface 5235 to a WiFi, 3G, or 4G network, a tether
5245, which may be intermittently attached, or a removable memory
or storage device can transmit the OM data (FIG. 53B) to a server
computer with associated permissions.
[0150] It is desirable that OM data be collected on a regular or
periodic basis (FIG. 107), either by the individual with disease or
with the assistance of a caregiver, or in a clinical setting, and
that the collected OM data be analyzed (FIG. 92) to determine
long-term trends in the efficacy 2330 of treatment 2310 or disease
progress 2320 or to compare the OM data acquired from one 2240 or a
group of individuals diagnosed with a disease to another group of
individuals 2230 diagnosed with a disease using statistical
analysis. The stored program 175 in the device 180, 10330 or a
system generated request (FIG. 53A) causes the device to provide a
reminder to the individual with disease, a caregiver, or a
clinician, using for example a light generated by a LED or a
display 1020 or an audible or vibration alarm to perform a
specified protocol based upon internal software or in accordance
with protocols in an external server-linked database such as the
RNF database (FIG. 108A) in order to reliably collect a sequence of
OM or SM data sets (FIG. 107), where each OM data set can be
transmitted to a server computer. It is advantageous to have a
mechanism for time keeping in the device, or accessible by the
device via a wireless or wired communication medium, in order to
accurately associate with collected data a time stamp of when the
data are collected. It is further possible to associate additional
data such as geographic location data (if a GPS receiver is
included in or accessible from the device 5250), as well as data
such as from temperature and humidity measurements.
[0151] An individual with disease or a caregiver or assistant may
use the device, or a different device such as a desktop or laptop
computer, tablet, or smart phone, to access a server computer in
order to control access to stored information about or derived from
the individual with disease. The individual with disease may, for
example, instruct the server computer 10315 to provide controlled
access to all or a portion of this data by a third party such as a
clinic, hospital, doctor, or physical therapist via a user
agreement or a one time explicit permission (FIG. 108A). The
individual with disease may also instruct a server computer, not
necessarily the same server computer, to deliver records stored
about the individual with disease and related to the individual
with disease's care to the individual with disease, or to a server
computer for storage at that server on the individual with
disease's behalf where a cohort database for similarly situated
individuals may be generated from EHR records. Security may be
carefully controlled through both authentication of the individual
with disease or individual with disease's representative to each
server computer and encryption of data during transmission between
devices (whether server computers, devices under the control or
used by the individual with disease, or devices used by other
individuals such as personnel at a hospital or a clinic, in order
to ensure that access or use of the data is not consistent with the
individual with disease's directives. All individuals,
organizations, or computers or other devices may be properly
authenticated to establish their identity before access to the
individual with disease's data is permissively allowed as will be
further explained herein.
[0152] Many authentication, encryption, and secure data exchange
methods exist and are well known in the fields of computer science,
computer engineering, and computer security (or cyber security).
For example, public and private key pairs can be generated and used
to identify individuals, organizations, or devices prior to
exchange of sensitive data. These public/private key pairs can be
used to encrypt and exchange session keys for the exchange of
sensitive data in an encrypted form. A server computer can execute
a program to generate a public/private key pair and optionally a
session key to provide to a user or another device or computer. If
the program is designed and executed in such a way that the
public/private key pair is maintained only in the memory of the
server computer prior to transmission to the recipient, and if the
memory location or locations where the key data are stored is
erased following use, then there is a very small window of time
during which an unauthorized program might intercept the key data
and transmit it or use it in an unauthorized manner, significantly
diminishing the risk that the individual with disease's directives
for security, privacy, and information sharing might be
violated.
[0153] Such a public/private key pair may be utilized to maintain
sensitive data that are stored on the server in an encrypted form,
where the key data that are necessary to decrypt the information
are stored only by the owner of the data, which is normally the
individual with disease who is associated with that data. By not
storing key data within a server computer and storing sensitive
non-key data such as OM data on a server computer only in encrypted
form, such that the individual with disease or individual with
disease's representative provides the key data only when needed to
the server computer and the server computer decrypts sensitive
information only upon demand and does not store the decrypted data
in a persistent form (such as in a file or database), the risk of
compromise of the security of the data is substantially transferred
to the individual with disease or owner of the data. The method
outlined herein for the security of sensitive information is but
one method of many that are known in the field of computer
security; other methods may be utilized. For example, a public key
infrastructure (PKI) system can be utilized using signed
certificates, firewall rules such as those provided by the iptables
or ipchains interface and the kernel firewall in a Linux operating
system, or similar capabilities in a UNIX or Windows operating
systems, and methods such as those enabled by Security Enhanced
Linux (SELinux) can be utilized to control access to computer or
device resources, and secure data exchange mechanisms such as
secure shell (ssh), secure copy (scp), secure authentication
mechanisms such as SSL and TLS, and secure XML and HTTPS protocols
can be utilized. In addition, many encryption algorithms are well
known in the field, as are multiple algorithms for the generation
and exchange of key information, and can be used in place of
portions of the approach described herein.
[0154] The invention contemplates a network of server computers,
individuals diagnosed with a disease, caregivers and care
facilities, and devices that can each communicate with other
selected computers, individuals, facilities, and devices within the
network. A web of trust can be established by the participants in
the network to allow the selective exchange of or access to stored
data associated with individuals diagnosed with a disease, care
facilities, or insurance providers. In the medical field, the
individual with disease plays, or can play, a central role as a
broker of data because the individual with disease typically has
access to all data about himself or herself. Once the individual
with disease acquires data, by request, from, for example, a
hospital or other service provider, the individual with disease
typically has the right to do what he or she wishes with the data,
including causing it to be stored in a server computer, modified by
algorithms or other process, or creating new data or analyses from
the data. Exceptions to this do occur, for example, if the data (as
opposed to the form or vehicle used to collect the data) are
copyrighted, in which case a individual with disease's rights to
the use of the data may be curtailed by the terms of use of a
license agreement. In general, however, the individual with disease
can control who and what organizations can access and use the data,
and how the data can be used. This offers a mechanism to ameliorate
a severe problem in current medical practice, which is the
inability of caregivers to access data generated at or held in
another location when the data offers the potential for improved
individual with disease treatment outcomes so as to generate a
cohort database tuned to the needs of the individual user who may
be any one in a community (for example, per FIG. 15). The
digitization of data, and of medical records in particular,
provides the opportunity for the individual with disease to play a
much more active role in his or her treatment by controlling access
to data about the individual with disease and providing access for
his or her benefit to the appropriate caregivers and facilities.
The use of public/private key pairs offers a mechanism for
authentication of access rights and data transfers which allows the
data to remain encrypted and inaccessible to other parties.
[0155] A medical information delivery system as disclosed herein is
composed of at least a server, computer, or computer system (a
server) that stores data about more than one individual with
disease, where the data may be OM, SM, or a combination of data
types. This system has, at any given time, a state, which is
determined by the totality of the stored individual with
disease-related data, and implements a method to select a subset of
the data for further processing (cohort data) based upon one or
more criteria such as the age, gender, ethnicity, geographic
location, disease status, treatment or treatments applied, service
provider(s), services rendered, participation in a program,
duration and type(s) of data stored, devices or protocols used to
gather data, and time(s) or time interval(s) for diagnosis,
treatment, or participation in a program, for each individual with
disease for which data are stored. This method to select may be
implemented, for example, using a commercial off-the-shelf (COTS)
database product such as Oracle or My SQL or software developed for
this purpose that may utilize either a database or files to store
information for the server's use. MUMPS is a programming language
that originated in the 1970's and was developed for applications
within the medical community. MUMPS incorporates features of
databases within the language using global variables that persist
in a database. It is still heavily utilized in medical applications
1560; however, there has been significant divergence between the
development of mainstream business-to-business (B2B) applications
development environments and the MUMPS environment. As a result, it
is more likely that the medical information delivery system
disclosed herein will be designed to interface to other systems
implemented using MUMPS than that it will be implemented using
MUMPS. Multiple computer systems or processors may be utilized to
implement the server; for example, a processor may be used to
execute a stored program and implement the method to select, and a
second processor may be used to manage the storage of data. These
processors may execute within a single physical computer, or within
multiple computers that can communicate via a computer network, as
is well known in the art. Parallel programming paradigms such as
those using the Message Passing Interface (MPI) software library
and Hadoop may be used to coordinate the computing activities
across multiple processors and multiple physical computers.
[0156] The disclosed medical information system can differentiate
stored data into multiple groups of data, each group having
different privacy or security attributes used to control the
distribution or dissemination of data associated with that group,
and can implement a method to anonymize any selected subset of data
associated with a group, including all data associated with a
group, in a manner that precludes the identification of an
individual individual with disease from knowledge of the anonymized
data. This anonymization can be performed by, for example,
suppressing or removing fields of information within data records
that have been flagged as providing personally identifiable
information; anonymization can also be performed by encryption of
these fields using either a symmetric key encryption algorithm or
one key of a public/private key pair, or by application of a secure
cryptographic hash such as the MD5 hash algorithm to the data and
using the computed hash value in place of personally identifiable
information from one or more fields of a data record in subsequent
operations. When fields of information are suppressed or removed,
it is no longer possible to recover the suppressed information,
unless the remaining fields can be used to uniquely identify the
data record in the stored data. When encryption is used, an entity
can recover the suppressed information if the symmetric encryption
key or the other half of the public/private key pair is known by
that entity. When a secure cryptographic hash is used, and if the
hash values have been uniquely associated with the data record,
knowledge of this association allows access to the data record
personally identifiable information by an entity that has access to
the original stored data. These methods of anonymization or
protection of sensitive information are well known in the fields of
computer science, computer engineering, and computer security.
Anonymization may be performed on demand, or on an as-needed basis
in response to a request for information, or it may be performed as
data are received for storage by the system. The second method is
preferred, where one or more symmetric or public/private encryption
key(s) are utilized to control the anonymization process. In this
case, additional encryption keys may be utilized to either
distribute anonymized data to an entity that requests it by
re-encrypting the data or distribute encryption key information in
an encrypted form.
[0157] The disclosed medical information system also implements at
least one method of processing anonymized data produced by
anonymization of a selected subset of a group of data. The method
of processing creates aggregate data or information that is
representative of one or more characteristics of the selected
subset of data, where the aggregate data or information may be in a
computer-readable form such as a data structure stored within a
computer's memory or storage device, or it may be in a
human-readable form such as a graph, chart, or table displayed on a
display device or printed on paper. For example, the aggregate data
may be a timeline showing the anticipated or average progression of
a disease such as PD together with visual indicators, icons, or a
histogram or other graphic showing the distribution of individuals
diagnosed with a disease associated with the selected subset of
data with respect to the status or progression of the disease. A
table or tabular listing or a chart may be utilized in place of a
timeline. Optionally, additional information may be generated by
the method of processing such as a listing of service providers
utilized by individuals diagnosed with a disease at a selected
point or portion along the timeline, or a listing of options
considered by individuals diagnosed with a disease within a
selected portion of the timeline. The timeline may be presented to
an entity in a manner that allows the entity to query the medical
information system for additional information, such as the
distribution of outcomes, such as the mean or median time to
progression to the next stage of a disease, in response to the
possible selection of a treatment option or of an activity by a
individual with disease at a selected point along the timeline. The
timeline may include, in addition to information based upon
anonymized data, sensitive, private, or personally identifiable
information to which the entity has rights that include the right
to view or use such data. This allows, for example, the comparison
of a individual with disease's disease progress against information
derived from anonymized data related to a cohort or selected group,
subset, or population of other individuals diagnosed with a
disease.
[0158] The disclosed medical information system also implements at
least one method of processing use of an external table of tables
(by example the Restorative Neurosciences Foundation (RNF) codebook
(RNF-C). This disclosed reference repository of tables and
standards can be used for database queries and to build a tuned
cohort database for an individual user as well as for use in social
media to locate similarly situated and local individuals to an
individual diagnosed with a disease (FIG. 108A, 108B and 108C).
[0159] The timeline may be implemented and presented to an entity
such as a individual with disease as a software application that
can be executed on a computer such as a desktop, laptop, or tablet
or on a portable or handheld device such as a tablet, smart phone,
or game device, in which case it is preferable, but not required,
that the computer or device that executes the software has
communications components such as a network interface or a wireless
(WiFi, 3G, or 4G) interface that enables communications between
this computer or device and the medical information system. In this
manner, the timeline can be presented in an interactive manner to a
person, who can utilize the timeline to query the medical
information system for information related to the person's disease
or disease status and compare the person's own situation with the
selected group or cohort. If communication between this computer or
device and the medical information system is either intermittent or
not feasible (except for the initial delivery of the timeline
software application and anonymized data), then the user's queries
can be answered by the software application using the delivered
anonymized data, but it is preferable that the answers be provided
using current data, either by intermittently delivering new
anonymized data to the computer or device or by performing the
necessary computations within the medical information system and
delivering the answers to the computer of device, so that the
answers to the user's queries are consistent with data recently
stored in the medical information system.
[0160] The medical information system may consist of many servers,
computer, or computer systems that store data related to
individuals diagnosed with a disease, anonymize data, aggregate
anonymized data, and implement at least one method of processing to
generate and deliver information based upon the anonymized and
aggregated data to entities, which may be other servers or
computers, or humans, in either machine-readable or human-readable
form. Each server, computer, or computer system may perform one or
more of these functions, and there is no requirement that more than
one function must be performed by a single server, computer, or
computer system. One or more servers may also provide an interface
that can be used by a client data acquisition and/or interface
device to deliver individual with disease-related data to a server,
effecting the storage of the individual with disease-related data
within the medical information system. Such servers may also
provide, as a function of their interface(s), methods whereby a
individual with disease or authorized individual with disease's
representative can direct the exchange of individual with
disease-related data, including data that contain sensitive,
private, or personally-identifiable information, between servers,
computers, or computer systems using communications methods that
optionally implement authentication and/or non-repudiation
strategies, thereby implementing a data exchange among individuals
diagnosed with a disease, providers, and other entities. This
method enables individuals diagnosed with a disease to "own" their
data and effect the exchange of data relevant to the management of
the treatment and progression of their disease between their
medical service providers. A client data acquisition and/or
interface device may optionally be mobile and/or be able to
communicate wirelessly with another device. This provide the
opportunity to collect objective measurement (OM) data related to a
individual with disease's disease status and communicate that OM
data to a server, computer, or computer system.
[0161] Mobile Data Acquisition/Display
[0162] An example is the use of an on-board gyroscope or
accelerometer of a mobile device (FIG. 8) with sensors and
connectivity (FIG. 52, FIG. 91) such as a mobile phone or tablet
manufactured by Apple Computer, Blackberry (Research In Motion), or
Google, or a wearable device such as a watch or ankle bracelet or
glasses running the Android or other operating system to sense
angular or rectilinear acceleration or interpret motion from
processed visual data (video of movement), according to a protocol,
for calculating degree of Parkinson's symptoms (e. g., pronation
protocol). As an example, APDM, a corporation based in Portland,
Oreg., provides wearable inertial monitoring devices similar in
size and shape to a watch that have an accelerometer, a gyroscope,
and a magnetometer, and that also provide wireless communications
to other such devices (McNames et al. 2010, 2012).
[0163] A mobile data acquisition device can be secured to an
individual's limb, such as strapped to a wrist or ankle or hand or
foot, or held by a hand, in order to sense motion, or attached to
the neck or head to sense orientation or motion, preferably
including an acceleration or velocity around at least one axis of
motion, but other configurations sensing rectilinear acceleration
or velocity along another axis or direction of motion or any other
combination are possible (FIG. 105B). The device may include one or
more sensors, such as a gravitational sensor 5255 to determine the
direction of gravity (or an up-and-down axis) or a GPS receiver
5230 or other receiver to determine a coordinate frame of reference
with respect to the Earth's surface (consisting of at least a
horizontal plane or a vertical axis) in order to determine
orientation, velocity, and/or acceleration in one or more axes or
degrees of freedom with respect to that coordinate frame of
reference. Such sensed orientation or motion (acceleration and/or
velocity along one or more degrees of freedom or axis) can be
sampled using a program stored in the mobile or wearable device,
either on a periodic basis or intermittently, and may be
temporarily stored within the memory of the device 5210 and
optionally processed 5225 using the stored program 175 to obtain
objective measurement data 210, and uploaded to a computer server
910 using a communication link, which may be wireless or wired and
may only be connected intermittently to the mobile or wearable
device. A second example is a wireless or wired access device,
which may be mobile or wearable but may also be a less mobile
device such as a desktop computer, a workstation, or a dedicated or
specially designed device used in a clinic or home health care
setting for this purpose, with an algorithm for encoding data input
or received from a neurostimulator or embedded measurement device.
Such a device can also be utilized to modify the operation of the
neurostimulator or embedded measurement device according to
directions input or received from a medical provider, where the
directions may be communicated or transmitted to the device either
using a wired or wireless communication link, which may be
intermittent or continuously available. The modification of the
operation of or obtaining input or received data from the
neurostimulator or embedded measurement device is preferably
performed or directed by the execution of a stored program in the
memory of the wireless or wired access device, but may be performed
by a computer or other processor such as a programmable hardware
device (such as an application-specific integrated circuit) within
the neurostimulator or embedded measurement device, or performed
through coordination of the operation of the two devices by the
programming of each device. The disclosed GPS functionality also
serves to obtain universal time to coordinate multiple devices and
longitudinal analysis.
[0164] FIG. 9 depicts wireless transfer of user entered and
objectively measured data to a managed host or web environment
wherein client devices 920, 930 provide OM, SM to a server 910 and
the server returns, for example, data of a cohort database,
progress data, queried data or control data. A secure computer
server platform (Server) can provide storage of received data in a
file or database, and can use protocols such as HTTP and HTTPS to
communicate with one or more mobile devices, wearable devices, or
wireless or wired access devices 920, 930. FIG. 10 depicts a
wirelessly linked mobile health device displaying User Displayed
Content via wireless delivery: alarm data, implant control data,
medication protocol data, drug delivery implant data among other
feedback data from server 910 developing a cohort database and
automatically calculating such feedback data for storage, display
or control. The Server 910 can implement a data retrieval system
using, for example, web based protocols such as HTTP and HTTPS
(FIG. 9) to implement a web based display system or a statistical
analysis system of devices 920, 930. The Server 910 will have at
least a processor such as an Intel or AMD processor that executes
x86 instructions or an Oracle processor that executes SPARC
instructions, a computer bus that enables the processor to
communicate with other components of the Server, where such
communication may include communications across a network or
communications channel such as a parallel or serial communication
channel used to communicate with disk drives (using for example a
SATA or SCSI channel, or a virtualized communication channel such
as iSCSI across a communication network) or a keyboard (using for
example a PS/2 or USB communication channel) or display (using for
example a VGA, DVI, or HDMI communication channel), memory to store
a program that directs the execution of the Server and stores data
received from or transmitted to another device, a network interface
or other communications interface that enables communication with
another device such as one or more mobile devices, wearable
devices, or wireless or wired access devices or other Servers or
computers used either for the same or similar purposes as disclosed
herein or used for different purposes such as within a clinic or
hospital setting for individual with disease records or to support
medical procedures or treatments, or by an insurance company or
government agency for financial and/or medical treatment records,
or by an association formed for the benefit of either individuals
diagnosed with a disease, medical or clinical practitioners or
staff, or by one or more researchers, enabling the exchange of
information between the Server and other servers or computers to
support collaborative activities, a storage device such as a hard
disk drive (HDD), a solid state disk drive, or a memory card such
as a SD card, or a network-accessible storage device (NAS) or other
storage device that is used for long-term or persistent storage of
the program and data, and an interface to allow administration of
the Server by another computer or a human operator, the interface
being either at least a keyboard and display device, and optionally
a pointing device such as a mouse or a touch pad, or a virtual
interface such as a Lights Out Manager or an implementation of the
VNC or other remote desktop protocol that emulates at least a
keyboard and display device using another device such as a second
computer that can communicate with the Server using a network. If
the server uses a database to store data rather than files stored
within its filesystem, database software such as MySQL or Oracle
may be used and included in the Server. Communication protocols
such as HTTP, HTTPS, or other protocols using XML, can be
implemented using web server and/or business-to-business
communications software such as Apache, Tomcat, J2EE, or Java
Beans. The combination of the Server and the one or more mobile
devices, wearable devices, or wireless or wired access devices
enable monitored or unmonitored measurements in either the home or
a clinical environment.
[0165] Activities performed in the home environment by the
individual with disease or individuals diagnosed with a disease'
caregivers using one or more mobile devices, wearable devices, or
wireless or wired access devices support or perform the collection
of information from or about the individual with disease that
relate to the documentation of the status or progress of the
disease for which the individual with disease is being treated
and/or the individual with disease's response to such treatment.
These activities can utilize consumer devices such as smart phones,
tablets, laptops, desktop computers, wearable computer devices such
as watches, and one or more components of game devices, some of
which may contain sensors that can measure position or location
(such as GPS receivers or WiFi communications devices) or
acceleration and velocity (such as gyroscopes and accelerometers)
or receive data from an implanted medical device or device attached
to the individual with disease (such as neural activity, heart
rate, blood pressure, body temperature, respiration, and motion or
tremor). Such activities may be monitored or unmonitored, or may be
performed autonomously and preferably on a regular or periodic
basis by a device under the control of a stored program, or as
directed by data received or communicated from a Server or other
computer using a wireless or wired communication channel.
Activities can include tests performed in a home environment by a
individual with disease or a individual with disease's caregiver(s)
and may use a protocol such as, by example, a protocol described
herein for the collection of motion data using a wearable or
handheld device, where the device is attached to a hand, wrist,
ankle, foot, torso, limb, or the neck or head. The test activity
can result in the acquisition of objective measurement (OM) data
using, for example, an accelerometer or gyroscope or GPS receiver,
where the raw measurement data may optionally be processed using an
algorithm in order to obtain OM data.
[0166] Device for interrogating individual with disease on-board
medical devices: Examples of leading neurostimulators systems FDA
approved for implantation include Deep Brain Stimulators (DBS) [an
example is the Medtronic Activa series], Peripheral Nerve
Stimulators [an example is the Cyberonics Vagal Nerve Stimulators
(VNS)]. Others [Boston Scientific, NeuroPace, etc.] are nearing FDA
approval. Each of these systems has the potential of communicating
with a data exchange. Such devices may be in the position to report
metrics of health such as temperature, position, movement, or other
useful metrics. A cohort database may be generated of information
from these devices using sensors (magnetometers, or other sensors)
to scan for emitted signals and correlate with a subset of known
programming parameters, which correlate for several similarly
situated permission granting individuals with disease. In the event
device manufacturers wish to partner with the exchange, they could
provide access through their individual with disease device
interrogation systems to provide a complete dataset about the
delivered neuromodulation or other signals (EEG in the case of the
NeuroPace RNS device).
[0167] Device for holding multiple sensors on the foot: One or many
sensors (of an intelligent client device equipped with a
transceiver) may be located on the lower extremities (FIG. 105B,
106) in a position to be able to measure metrics of 1) gait 10430
and the relative difference between measurements from each leg to
determine the presence or absence of an asymmetric gait, for
example, or an antalgic gait, for example, or determine time of
walking, acceleration, turns, or other metric 2) pressure or
relative use of the anterior, posterior, medial, or lateral aspects
of the foot. Such devices are secured via connections to external
physical features of the foot covering device such as: 1) embedded
within a sock or foot worn device within a shoe, or 2) attached to
the shoe sufficiently to capture the movement of the foot, or 3) to
other external device with or without a strap attached externally
to the leg, 4) or in the form of an implantable sensor with
transmission to the external environment powered via primary cell
battery, rechargeable battery, or deriving power via regenerative,
ambulation based methods or via a rectified circuit method deriving
power from external sources such as power from cellular or other
transmissions.
[0168] Device for holding multiple sensors on the hand/wrist. One
or many sensors (of an intelligent client device equipped with a
transceiver) may be located on the upper extremities in the
position to be able to measure metrics of 1) arm swing and position
and the relative difference between measurements from each arm to
determine the presence or absence of an asymmetric arm swing, for
example, or determine time or velocity of arm swing, acceleration,
turns, or other metric 2) pressure or relative use of the hand.
Such devices are secured via connections to external physical
features of the hand covering device such as: 1) embedded within a
glove or hand/arm worn device within a clothing item such as a
jacket, or 2) attached to the arm/glove sufficiently to capture the
movement of the arm, or 3) to other external device (such as a
glove) with or without a strap attached externally to the arm, 4)
or in the form of an implantable sensor with transmission to the
external environment powered via primary cell battery, rechargeable
battery, or deriving power via regenerative, ambulation based
methods or via a rectified circuit method deriving power from
external sources such as power from cellular or other
transmissions.
[0169] Device for holding multiple sensors on the torso or head.
One or many sensors (of an intelligent client device equipped with
a transceiver) may be located on the torso or human body head in
the position to be able to measure metrics of 1) torso/head
movement (including capturing head movement gestures), postural
sway/head movement, for example, or determine time or velocity of
arm swing, acceleration, turns, or other metric 2) pressure or
relative use of the torso/head. Such devices are secured via
connections to external physical features of the torso/head
covering device such as: 1) embedded within a shirt or jacket or
sweater/hat, head mounted device or glasses like device mounted or
worn by on the head, or 2) attached to the torso or head/jacket or
hat sufficiently to capture the movement of the torso or head, or
3) to other external device (such as a strap or backpack or
headband) with or without a strap attached externally to the head,
4) or in the form of an implantable sensor with transmission to the
external environment powered via primary cell battery, rechargeable
battery, or deriving power via regenerative, ambulation based
methods or via a rectified circuit method deriving power from
external sources such as power from cellular or other
transmissions.
[0170] Client data acquisition/display device for use by a
individual with disease: An intelligent device with sensors may be
used to acquire diary or objectively measured data such as GPS
position, relative movement, motion data (accelerometer,
gyroscope), monitors speed of typing or other finger inputs, and
may be able to record speech (via a microphone) and facial
expressions of the user. Additionally, the device may be used in an
emergency to reach out for further help and assistance.
[0171] Client data acquisition/display device for use by a
healthcare professional: Such an intelligent device may be used to
display checklists and forms, progress reports, alarms and updated
drug regimen or implant control data such as the unified
Parkinson's disease rating scale for use in a clinical setting and
provide a display of the disease state of the index individual with
disease.
[0172] Client data acquisition/display device for use by a
researcher: Such an intelligent device may be used to acquire
non-health care data for the specific purpose of research acquired
in a meaningful way for aggregation and dissemination to others
based upon permissions and queries presented to develop a specific
cohort database. Data for use by a researcher may be obtained by
processing or aggregating data from individuals diagnosed with a
disease using a Server, or, in order to adequately safeguard the
privacy of individuals diagnosed with a disease, by a second Server
that obtains data from one or more Servers that have stored
individual with disease OM, CM, and/or SM data that, such obtained
data having been anonymized by, for example, removing, encrypting,
or hashing (using, for example a cryptographically secure hash such
as MD5) information that can be used to identify a individual with
disease. The processing or aggregating to form a specific cohort
database may be performed by, for example, providing one or more
graphs, reports or maps of individual with disease data for a group
of individuals diagnosed with a disease such as a subset of
individuals diagnosed with a disease selected by geographic region,
by age, gender, ethnicity, or occupation, or by the stage of a
individual with disease's disease or the type or types of
procedures that have been performed or devices that have been
implanted within the individuals diagnosed with a disease. Such a
map, graph, or report may be made accessible to researchers, to a
group such as individuals or organizations within a government, a
company, or an association, or to administrators or medical
professionals associated with clinical or hospital facilities using
a Server that implements a web site on which this information is
published, either without access controls, or disseminated
privately to individuals or groups using a secure web interface and
authentication by token, biometric such as a fingerprint or iris
scan, or user identifier and password. It may be preferable to
utilize multiple Servers to process and or aggregate individual
with disease data in the chain from the Server that initially
stored data received from a device used by the individual with
disease a individual with disease's caregiver, or a clinician or
other medical professional to perform the steps of anonymization,
analysis, which may included statistical modeling and analysis,
aggregation, generation of specific cohort database, preparation of
maps, graphs, or reports, and presentation or dissemination of the
prepared data to the public or for research purposes.
[0173] Objective Measures Via Mobile Medical Devices:
[0174] FIG. 11 specifies a novel data acquisition method for
obtaining clinically meaningful maximum effort data in measuring
forearm bradykinesia among other OM. Worn device 1140 may
communicate with another device 1160. Graphs 1100 may be generated
where a smaller signal inside larger signal 1130 may quantify a
tremor after start 1110. Both the protocol and sample data are
shown. Method of assessing physical movements bradykinesia with a
mobile phone, tablet, device manufactured or customized for this
application or market, or visual recognition of such movements
(such as with a Microsoft Kinect.TM. device), or devices
manufactured especially for this market. For example, a company
could produce a $50 device that connected to WiFi, contained a
gyroscope and an accelerometer, implemented the method disclosed
herein, and interacted with a server or other device by connecting
through a packet-switched network such as the Internet. This
embodiment involves objective and clinician measures within mobile
device applications: Examples include a method of performing a
forearm pronation/supination test for bradykinesia including
optimization for computer algorithm testing, objective measurement
(OMS) of forearm bradykinesia (pronation/supination) as a surrogate
for the clinician measured (CMS) Unified Parkinson's disease Rating
Scale (UPDRS) subscores, and measurements performed in varied
medication and neuromodulation states (ON MEDS/ON STIM, ON MEDS OFF
STIM, OFF MEDS ON STIM, OFF MEDS OFF STIM). A representative
physical test is as follows (Sillay mobile medical bradykinesia
test: Step 1--(optional but recommended for the clinical setting)
Position video camera 20 feet from subject sitting in an armless
chair against an appropriate background; Step 2--Subject applies
devices to both upper extremities (or to one upper extremity
followed by the other upper extremity in sequence for which steps
3-7 are repeated with the second extremity via a device--anchoring
system; Step 3--Subject holds arms toward the axis of videotaping
with palms facing down; Step 4--Subject performs one external
rotation maneuver as rapidly as possible with both instrumented
forearms; Step 5--Subject pauses for one second; Step 6--Subject
performs external then internal rotation with maximum speed for 10
repetitions; Step 7--Subject pauses for one second; Step 8--Test is
complete.
[0175] During the data processing and analysis, the following steps
are performed: Step 1--Determine maximum rate of angular
acceleration, degrees traveled per oscillation, peak angular
velocity, hesitations, fatiguing, and amplitude of angular
velocity. Step 2--Determine objective rating score, Step 3--Apply
reference algorithm to calculate the equivalent UPDRS (Fahn et al.
1987), or reference score (0-4, within 50% in a single individual
with disease and within 10% within a population) [Note here: the
reference information could be downloaded from a server or other
device with which the data acquisition device communicates, and
difference references could be used, for example, a reference
derived from data collected from a cross-section of a measured
population. This concept is possibly in addition to using a
standardized (for example, national) reference score. (Increased
maximum wrist rotation speed correlates with lower UPDRS scores
(FIG. 7) as calculated (FIG. 12), (FIG. 13)), between those with
neurostimulators activated 1460 and those with neurostimulators
deactivated 1470 (FIG. 14A and 14B), peak angular velocity
increases with stimulator activation and also correlates with the
UPDRS (FIG. 7); Step 4--Correlate to historic data: on/off
medication and on/off stimulation status in a wide cohort [again,
different cross-sections of individuals diagnosed with a disease
could be selected for the correlation or comparison study,
especially for research purposes] of individuals diagnosed with a
disease varying disease burden (Hohen and Yahr stage (II-V)).
[0176] A feedback path or an alarm path to the individual with
disease, for example, is provided to trigger to begin a Sillay test
at home, to take a prescribed medication at a particular level by
comparison of medication taken by the individual with disease with
cohort data or to provide real time control of DBS or
neurostimulation and/or a drug regimen.
[0177] Method of Securing Multiple Sensors on the
Foot--(Triangulation foot pressure and movement sock/glove).
Pressure sensors within a shoe or sock with or without a device
worn on the shoe (for example, secured to the shoelaces) in
combination with or without an accelerometer/gyroscope system on
the foot measure movements during gait in order to identify metrics
for speed and cadence as well as for measuring gait and
differential pressure. Differential pressure one extremity versus
the contralateral extremity is used to correlate with
symptomatology. An example of this is for individuals diagnosed
with a disease who state they are having gait problems, times of
the day are recorded and their reported symptoms can be benchmarked
against the objective measures.
[0178] It is desirable to align the mobile device in a manner that
is consistent between tests and that accurately captures the motion
(acceleration and/or velocity data) along the direction of maximum
motion of the limb (whether rotation or translation) in order to
minimize the effects such variations can have on the captured data
and any derived OM quantities. Alternatively, and preferably, it is
desirable to process the acquired data in a manner that minimizes
or removes these effects. The following approach discloses by
example one method that achieves this goal. Other methods and
variations may be employed. For example, the square root of the sum
of squares of all components of a 3-dimensional vector acceleration
or velocity measurement may be used, or the component having the
maximum magnitude, over the data collection time interval, may be
used. However, the sum of squares method incorporates the effects
in the measurements caused by the motions of joints or limbs other
than the one of primary interest, and the maximum magnitude method
assumes more precise alignment that is necessary using the
preferred method. During the data processing and analysis, the
following steps are performed: Step 1--Determine maximum rate of
angular acceleration, degrees traveled per oscillation, peak
angular velocity, hesitations, fatiguing, and amplitude of angular
velocity. Step 2--Determine objective rating score, Step 3--Apply
reference algorithm to calculate the equivalent UPDRS, or reference
score (0-4, within 50% in a single individual with disease and
within 10% within a population). The reference information could be
downloaded from a server or other device with which the data
acquisition device communicates, and difference references could be
used, for example, a reference derived from data collected from a
cross-section of a measured population. Alternatively, a
standardized, for example, national reference score could be used.
(Increased maximum wrist rotation speed correlates with lower UPDRS
scores, peak angular velocity increases with stimulator activation
and also correlates with the UPDRS; Step 4--Correlate to historic
data: on/off medication and on/off stimulation status in a wide
cohort [again, different cross-sections of individuals diagnosed
with a disease could be selected for the correlation or comparison
study, especially for research purposes] of individuals diagnosed
with a disease varying disease burden (H and Y stage (II-V)).
[0179] Again, it is desirable to align the mobile device in a
manner that is consistent between tests and that accurately
captures the motion (acceleration and/or velocity data) along the
direction of maximum motion of the limb (whether rotation or
translation) in order to minimize the effects such variations can
have on the captured data and any derived OM quantities.
Alternatively, and preferably, it is desirable to process the
acquired data in a manner that minimizes or removes these effects.
The following approach discloses a first preferred method that
achieves this goal; other methods may be utilized. A second
preferred method is the alignment of the device with the axis of
rotation or translation of a joint or limb so that it is sufficient
to sense the motion of a single axis of rotation or translation.
The first preferred method requires acquisition of data (whether
acceleration, velocity, or both, and whether rotation, translation,
or both) for three axes or coordinates in 3-dimensional space (for
example, in x, y, and z translational coordinates for translational
data, in theta_x, theta_y, and theta_z rotational coordinates
around x, y, and z axes for rotational data, or in all six
directions when both angular and translational data are captured).
The three (or six) coordinates do not have to be orthogonal, but
they must constitute a basis for 3-dimensional (or 6-D) space.
These coordinates form a coordinate system that is typically
determined by the physical characteristics of the measurement
device, and their relationship to a coordinate system defined by an
individual's joint, limb, head, or torso is typically determined by
the manner in which the device is attached to or connected with the
individual and any alignment procedure that has been utilized.
[0180] This method assumes acquisition of data at a sequence of
times within a desired time interval over which data are to be
acquired, where the sequence of times may or may not be equally
spaced. A goal is to estimate the variation present in the data,
for example, the difference between the maximum and minimum angular
accelerations around an axis that is not necessarily aligned with
one of the axes or coordinates used by a sensor. Other goals can be
applied, including the estimation of at least one spectral
component in the measured signals to produce an OM, estimation of
one or more parameters to provide an OM of repeatability of motion,
and estimation of the time or frequency signature of motion either
coincident with a primary axis of motion or perpendicular to a
primary axis of motion. An example of the last case is to estimate
or provide an OM related to tremor. Regardless of how well one may
attempt to align a mobile or wearable device with the axis of, for
example rotation of a individual with disease's wrist, it is
difficult or impossible to align the device with perfect accuracy
or to achieve the exact same alignment each time the device is
aligned. Any misalignment can introduce errors into the
measurements and adversely impact the quality of the acquired OM
data. If data are captured along three (or six) independent degrees
of freedom, then the effects of misalignment errors can be greatly
reduced, if not eliminated, by processing the acquired data using
the first preferred method disclosed herein, enabling the accurate
capture of OM data, for example of the maximum acceleration
achieved by the individual with disease when rotating his or her
wrist (FIG. 11). Alternatively, if the device is carefully aligned
so that a single sensor accurately measures the motion along a
coordinate defined by a joint or limb, or by the head, then the
measurement data provide by that single sensor can be utilized to
compute an OM (the second preferred method). The first preferred
method extends to the analysis of captured data that involves
simultaneous motion along multiple (3 or 6) degrees of freedom
using either velocity or acceleration data, or both. In effect,
alignment is achieved with a coordinate system that is orthogonal
and is selected so that the first, or a distinguished, coordinate
captures the greatest motion (velocity, acceleration, or both) and
subsequent coordinates are orthogonal to previously selected
coordinates and capture the greatest motion in the remaining data.
Because the relative positions of an individual's joints and limbs
change with movement, it may be desirable to utilize an additional
optional method to re-determine the chosen coordinate system on a
regular, periodic, or occasional basis, or to utilize a mounting or
positioning system that contains additional sensors to provide
information that can be utilized to re-determine or update or
estimate the chosen coordinate system. For example, a flexible
harness or strap can be utilized that incorporates sensors to
detect and measure the flexure or extension of a joint such as a
wrist, an ankle, a knee, a hip, or an elbow. The method can be
performed using a variety of computational algorithms, including
eigenvector and eigenvalue analysis and matrix factorizations such
as QR decomposition and SVD (singular value decomposition). SVD is
generally recognized as the most accurate and preferred algorithm
and will be used to illustrate the method herein, but another
method may be used because SVD requires more computation than some
alternatives. For example, a computational algorithm can be
utilized to estimate the first principal component or eigenvector
associated with the largest real eigenvalue of a matrix as an
alternative. The method is related to the methods of principal
component analysis and partial least squares methods and algorithms
used for data analysis, and SVD can also be used to solve problems
of those types. The method is described by example using by way of
illustration a synthetic data set.
[0181] Once raw measurement data have been collected using
accelerometers or gyroscopes, or an equivalent type of sensor, the
data can be organized or thought of as a matrix (referred to herein
as D for "data" matrix) having n rows and m columns, where n is 3,
6, 9, or 12 (corresponding to three degrees of freedom each in some
combination of rotational or angular velocity, rotational or
angular acceleration, translational velocity, and translational
acceleration measurement data), and where m is the number of
measurements. Each row corresponds to and contains measurement data
collected with respect to one access, coordinate, or degree of
freedom, and each column corresponds to and contains measurement
data collected as one measurement time or as a part of one
measurement. The functions of rows and columns can be exchanged,
and in this case the resulting method is fully equivalent to the
method described herein; the exchange being the same as using the
transpose of the matrix of data measurement. Furthermore, there is
not requirement that the data actually be stored or represented
within a computer's or device's memory as a matrix, such as within
contiguous elements of memory; it is only required that the
elements of the data be indexed by both a coordinate identifier and
a time. The i-th row of the matrix D will be represented in this
text as D(i,:) and will correspond to all measurement data in the
matrix D associated with the i-th axis, coordinate, or degree of
freedom, and the j-th column of the matrix D will be represented as
D(:, j) and will correspond to all measurement data in the matrix D
acquired at the j-th measurement time. There is no requirement that
the measurement times be ordered in ascending or descending order,
although any implementation may do so for convenience.
[0182] The objective of the method is to determine a direction of
maximum variation in the data as described by the measurement data,
and to use this direction to estimate one or more properties of the
measured data such as the maximum variation, which may for example
be the maximum and minimum angular or translational acceleration or
velocity of a individual with disease's joint, limb, hand, foot, or
head. Subsequent directions of maximum variation in the residual of
the data (after the components of maximum variation are removed by
subtraction from the data) may be computed in either a recursive or
iterative manner, and additional properties of the measured data
may be estimated using these directions, such as maximum and
minimum angular or translational accelerations or velocities of a
second joint or lateral motion of a foot, head, or leg. If multiple
types of measurements are available (acceleration, velocity,
angular, and translational), these measurements may be analyzed
using this method either in combination or in parts (individually
or with two or more types taken together). For the purpose of
example, a single type of data, which may be any one of these
types, is assumed and is therefore 3-dimensional.
[0183] The method used to determine the direction of maximum
variation may utilize either all of the columns (data from all
measurement times) in the matrix D, or any subset of the columns.
When the quantity of data is large it is preferable to sample the
data by selecting a subset of the columns to use in the
determination of the direction of maximum variation in order to
reduce the computational burden. There is, however, a trade-off
between accuracy (which increases as the number of samples utilized
increases) and the impact of measurement noise (which decreases as
the number of samples utilized increases) and sample size on the
quality of the estimate of the direction of maximum variation. For
the purpose of the example, a synthetic data set is created using a
sampled sinusoidal waveform having a period of one second and
including ten periods, where 20 samples per second are used. This
results in a 3-dimensional waveform of 201 samples. An amplitude of
10, corresponding to a maximum variation of 20 units, is chosen,
and the data are shown, along the direction of maximum variation,
showing variation between -10.0 and +10.0 units. A rotation matrix
is randomly generated and applied to these data values, assuming
the initial direction of maximum variation is in the third
dimension, resulting in synthetic measurement data with respect to
three coordinate axes, are shown. To demonstrate that the results
of the disclosed method's application are not dependent upon the
choice of rotation matrix, a second rotation matrix is randomly
generated and applied, and the resulting synthetic measurement data
are shown. If the data from the measurement axis that displays the
greatest variation are used to compute the range of variation, or
motion, the first synthetic data set produces an estimated range of
variation of approximately 13.7, while the second synthetic data
set produces an estimated range of variation of approximately 13.3
Both estimates are significantly below the actual range of
variation of 20, due to the lack of alignment between the (randomly
generated) measurement coordinate system and the coordinate or axes
of actual variation. This illustrates the problem that the method
addresses and solves: A method is desired that yields an estimated
range of variation, as an example of a property that can be
estimated from the measurement data, of approximately 20 rather
than the significantly lower values of 13.3 and 13.7.
[0184] As an optional step, relatively smaller subsets of the
columns of the two matrices D containing the synthetic measurement
data are randomly selected and used to estimate the range of
variation represented by each set of measurement data. Let this
subset of columns of D be represented by the matrix D_s. This
optional step reduces the amount of computation that is required
but increases the error in the estimate. For the first synthetic
data set, 22 rows are selected, and 23 rows are selected for the
second data set. The singular value decomposition (SVD) is used to
decompose the matrices D, as is well-known in the field of linear
algebra, into the products of three matrices USV.sup.T=D_s, where U
and V are orthogonal n.times.n and m.times.m matrices,
respectively, and S is a diagonal n.times.m matrix with
non-negative elements that appear in decreasing order along the
diagonal. Using this decomposition, the first column of U, U(:,1),
is the direction of maximum variation, as estimated using the
randomly selected columns in D_s from D. The maximum variation
present in the measurements (columns of the matrix D) can be
reconstructed, or estimated, by multiplying the columns of D on the
left by the transpose of U(:,1). When this is performed using the
two example cases presented herein, the maximum and minimum values
of the reconstructed signal are +10 and -10, for a total variation
of 20, within the precision of the computer used to perform the
computation. When the reconstructed signals are graphed, the
reconstructions lie on top of the actual (synthesized) signals of
maximum variation, and the errors between the original and
reconstructed maximum variation signals are shown in the FIG's. The
magnitudes of these errors, for these two simulated cases, are in
all cases less than 2.times.10.sup.15, or roughly the limit of
precision of the computer used to perform these computations. This
example demonstrates the effectiveness of the disclosed method in
the reconstruction of the signal and signal properties such as
amplitude associated with motion in a degree of freedom such as
rotation of a joint such as the wrist. The method can be applied to
accurately estimate other properties of motions (rotations or
translations) along one or more coordinate axes in a
straightforward manner using one or more columns of the matrix U
obtained using the SVD and the corresponding singular values, which
are the diagonal elements of the matrix S. For example, the
reconstructed data, along one or more axes of motion, can be used
to determine spectral estimates or estimate spectral components of
the data or to determine one or more measures of the repeatability
of motion. Other algorithms can be used in place of the SVD such as
algorithms based upon eigenvector and eigenvalue analysis or an
algorithm to estimate or determine only one or more selected
directions of maximum variation. The use of the sampled columns of
the matrix of measurement data D, D_s, is optional, as the same
method can be applied to the measurement date matrix D.
[0185] The method utilized to determine the direction of maximum
variation using SVD or another method can be implemented by a
computational algorithm encoded in a stored program within the
device used to acquire the data, or all or a portion of the
measurement data matrix D can be transmitted to a second device
from the data acquisition device, which can perform all or a
portion of the computational steps and either return the results to
the data acquisition device, store the results if the second device
is a Server, or forward the results to a third device or Server.
For example, the SVD algorithm can be implemented by a stored
program in a Server, which receives the data in the matrix D_s from
the data acquisition device and utilizes these data to determine
the direction of maximum variation. The Server can then communicate
this direction of maximum variation to the data acquisition device,
where a stored program can be executed to apply the direction of
maximum variation to the measurement data in the matrix D to
compute one or more OM from the measurement data. The data
acquisition device can subsequently transmit the one or more OM to
a Server or other computer, which may be the same Server used to
compute the direction of maximum variation or a different Server or
computer. This scenario is provided as an example; other variations
are possible. For example, a Server or computer other than the data
acquisition device can execute a stored program to calculate an OM
using an estimate of the spectrum of the data, where the estimate
can be computed either on the data acquisition device, on the
Server or computer, or on an additional Server or computer. In
these cases, each pair of devices (each one of a data acquisition
device, a Server, and a computer) must have components that enable
the communications between those two devices, such as a connection
to a wired network, a memory card such as a SD card or Compact
Flash card that can be removed and inserted in a memory card
interface attached to each device of the pair, a wireless network
interface using, for example, a WiFi, 3G, or 4G network, or a
serial communication interface. The devices of each pair need not
have the same type of components to enable their communications,
but the components must be sufficient to enable the necessary
exchange of data.
[0186] OBJECTIVE MEASURES BY INDIVIDUAL WITH DISEASE WEB PORTAL
(and mobile device): According to user consent, certain metrics
will be recorded during the use of the web portal and mobile
devices including decision-making speed when presented with a
question. In this example, the time to respond to a selection will
be aggregated by the position of the individual with disease on the
TIMELINE and by other factors and correlated to known
neurostimulator or other device states. Typing speed will be
monitored and correlated to known factors including medication,
sleep, and neurostimulator state. Time of use will be logged to
calculate objectively certain wake and sleep and other activity
states. Certain metrics will be obtained on the front end of the
site such as average typing speed and mouse click for all visitors
to the portal. Options may be made available to record samples of
video or speech or to have certain movements monitored via video
stream or via kinect or similar method of tracking movement. Order
of progression through a decision tree such as the site map will be
aggregated and correlated.
[0187] On Screen Display
[0188] A display 1020 (FIG. 10) may be used to present a series of
user interface screens whereby a person such as a trained nurse, a
helper or caregiver, the individual being measured or monitored, or
someone at home enters data such as individual with disease name,
date, time, address, doctor(s), clinic(s), or other medical or
assistive facilities that have provided treatment(s), contact
information of a caregiver, a helper, a friend, or one or more
family members, one or more diagnostic procedures or diagnoses that
have been applied to the individual with disease, records related
to the individual with disease's conditions that the patent has
acquired and for which the individual with disease has the right to
enter into an electronic or computer system, and other similar or
related information. The display is connected to a client device or
a device in a clinic, where the device (Client Interface Device)
has at least a processor such as an Intel or AMD processor that
executes x86 instructions or an ARM processor that executes ARM
instructions, a computer bus that enables the processor to
communicate with other components of the Client Interface Device,
where such communication may include communications across a
network or communications channel such as a parallel or serial
communication channel used to communicate with disk drives (using
for example a SATA or SCSI channel, or a virtualized communication
channel such as a software implementation of the SMB, CIFS, or NFS
storage access protocols across a communication network), an
interface having a keyboard (using for example a PS/2 or USB
communication channel or a virtual keyboard using a touch screen
display) and optionally having a pointing device such as a mouse or
a cursor on a display that can be manipulated by a wheel, a button,
or another type of device allowing user input as is well-known in
the field of computer engineering, a display which may be a touch
screen display and may use for example a VGA, DVI, or HDMI
communication channel, memory to store a program that directs the
execution of the Client Interface Device and stores data received
from or transmitted to another device, a network interface or other
communications interface that enables communication with another
device such as a Server or other computer, one or more mobile
devices, wearable devices, or wireless or wired access devices used
either for the same or similar purposes as disclosed herein or used
for different purposes such as within a clinic or hospital setting
for individual with disease records or to support medical
procedures or treatments, or by an insurance company or government
agency for financial and/or medical treatment records, or by an
association formed for the benefit of either individuals diagnosed
with a disease, medical or clinical practitioners or staff, or by
one or more researchers, enabling the exchange of information
between the Client Interface Device and one or more Servers or
computers to support the exchange of data or other information
related to a individual with disease, and a storage device such as
a hard disk drive (HDD), a solid state disk drive, or a memory card
such as a SD card, or a network-accessible storage device (NAS) or
other storage device that is used for long-term or persistent
storage of the program and data. The Client Interface Device may be
a tablet computer, a laptop computer, a notebook computer, a
desktop computer, a smart phone, a computer game console, a smart
phone, or a special-purpose or customized device containing a
processor and the other listed components that have been developed
for a medical application.
[0189] The Client Interface Device plays a central role that allows
a individual with disease or a representative of a individual with
disease to securely interact with one or more Servers or other
computer systems to access, acquire, and distribute or disseminate
information related to the individual with disease, the individual
with disease's disease, and treatments the individual with disease
has undergone or will undergo. US law and HIPAA regulations provide
for both the regulation and protection of medical records and
individual privacy and the control of information about a
individual with disease or related to a individual with disease by
the individual with disease. The individual with disease or an
authorized representative of the individual with disease always has
the right to obtain medical, insurance, or financial records
containing data about that individual with disease and in most
cases can use the information in those records in any manner he or
she wishes. The disclosed methods enable individuals diagnosed with
a disease to take an active role by controlling the exchange of
information related to their care and address significant current
problems where information that can beneficially influence the
outcome of individual with disease treatments such as surgical
procedures and therapy is not accessible to the providers or care
or services that need it.
[0190] The individual with disease has the right and the authority
to effect exchanges of information among the individual with
disease's caregivers and providers, as a individual with disease
can now do by obtaining physical records from one provider and
delivering those records, or copies thereof, to another provider.
The disclosed technologies enable construction of systems composed
of Client Interface Devices, Servers, and other computers or
computer systems that can communicate using communication channels
such as computer networks, mobile telephone/cellular data networks,
WiFi networks, metropolitan networks, serial communication links
and links enabled by wireless and wireline telecommunications
service providers (for example, fax machines and serial
communications protocols using modems), where such systems provide
methods for individual with disease-directed exchange of individual
with disease-related and health care information between or among
providers of services to the individual with disease. These systems
for permission based data advocacy on behalf of the participants
allow health linked information exchange and are capable of
interacting with existing electronic medical record systems,
cellular, wireless, and wired telecommunication and other
communication networks to support the exchange of health data from
existing electronic medical record systems and paper-based and
off-line record systems and to facilitate the exchange of data
between hospitals, clinics, public entities, private foundations,
insurers, vendors, sponsors, and other interested parties through a
individual with disease avadavat system linking home measurements,
recording, diary, and community and support group-based periodic
meeting acquired information. The exchanged information or data can
include both subjective measures such as diary data and diagnoses
or measures by clinicians grading the degree of, for example,
forearm slowness in PD, and objective measures of treatment and
individual with disease response or status such as during phases of
treatment such as preoperative symptomatology, probabilistic atlas
linked targeting for neuromodulation, accountancy for gravitational
effects of brain shift during surgery, measurements of movement and
quality of life during the perioperative and postoperative phases
of treatment and ongoing community and self-directed treatment. The
existence of the disclosed systems enables aggregation across
populations or selected subpopulations of individuals diagnosed
with a disease by disease, geographic area, ethnicity, age, gender,
occupation, treatment(s), or other categories and comparison of
objective or subjective measure data associated with one individual
with disease with aggregated data of similar types for the selected
population or subpopulations. Such comparisons can be performed by
the individual with disease, the individual with disease's
authorized representative, or, with appropriate authorization by
the individual with disease, medical or clinical personnel who
provide services to the individual with disease.
[0191] The Client Interface Devices can be mobile and can utilize
mobile networks such as 3G, 4G, WiFi, and metropolitan wireless
systems such as WiMAX to communicate with one or more Servers or
other computers or computer systems, and can thus be available for
use by the individual with disease or an authorized representative
of the individual with disease within clinics or other medical
facilities, enabling the individual with disease or representative
to provide and control access to data related to the individual
with disease whenever and wherever the need arises. Security
protocols such as the use of authentication and encryption methods
that are well-known in the art are preferably used to ensure
privacy, protection of sensitive data, appropriate levels of
authorization to data, and non-repudiation of access to,
modification of, or change of access rights to any protected
sensitive data. For example, certificates associated with Client
Interface Devices, Servers, other computer systems, and the
individuals (individuals diagnosed with a disease, representatives,
and care givers such as clinical or medical staff) ensure
appropriate access control and proper identification of individuals
and entities that access the data in this manner. Logs maintained
by Client Interface Devices, Servers, and other computers or
computer systems and logging facilities implemented by stored
programs within these devices, servers, and computers or computer
systems ensure the proper maintenance of audit trails to support
detection of data or data rights misuse and verification that
appropriate access rights were granted prior to data access.
[0192] A Client Interface Device that includes sensor components
such as a gyroscope, an accelerometer, or a GPS can utilize a
stored program to acquire measurement data such as the motion of a
joint, limb, head or torso, or the orientation of a head, in order
to determine objective measures related to a individual with
disease's condition or disease status. The Client Interface Device
is preferably mobile, handheld, or wearable, and preferably
contains one or more components such as a transceiver,
software-defined radio, or wireless or cellular communication
interface to enable the Client Interface Device to communicate with
a Server as or soon after measurement data are acquired, but this
is not required. For example, the Client Interface Device can be a
smart phone such as an Apple iPhone running the Apple iOS operating
system or a tablet such as the Apple iPad, also running the Apple
iOS operating system, or a smart phone or tablet running the
Android operating system available from Google, such as Android
smart phones or tablets manufactured by Samsung. The Client
Interface Device can contain a removable memory card such as a USB
memory device, a SD memory card, or a Compact Flash memory card on
which acquired measurement data can be stored by the Client
Interface Device under the direction of a stored software program
residing either within the memory of the Client Interface Device or
on the removable memory card or other memory or storage device, and
the measurement data can be transferred to a Server or another
computer or computer system by the physical removal of the memory
card from the Client Interface Device and insertion of the memory
card into an appropriate interface component such as a memory card
reader connected to the Server or other computer / computer system.
Alternatively, an interface cable such as a USB cable or a directly
connected interface such as a USB interface can be used to connect
the Client Interface Device to the Server or other
computer/computer system to effect the transfer of the measurement
data. The Client Interface Device may also have a camera, which can
acquire either still or motion (video) image data, or both, and one
or more stored programs that can be selectively executed by a user
to acquire still or motion image data to be used or evaluated,
either by a person or using a computer algorithm, and from which
objective or subjective measurement data can be derived. A stored
program in the memory of the Client Interface Device can be
utilized to record symptom data or objective measurement data using
the disclosed user interface components such as a display, which
may be a touch screen display, a keyboard such as a virtual
keyboard displayed on a touch screen display, or a graphical user
interface containing fields and selection buttons or check boxes
that a user can manipulate using, for example a touch screen
display or a pointing device such as a mouse, a virtual input
device such as, for example, displayed touch-sensitive icons
corresponding to directional pointers that cause a cursor to move
on the display, or a track ball, which may be associated with a
button or other component to enable the selection or checking of an
item or may be depressed to selects or check an item. The Client
Interface Device's communications or networking component(s) can,
under the direction of a stored program executed by the processor,
upload data to a medical records system implemented, by example, on
a Server or other computer or computer system adapted to receive
the data into a individual with disease's file via a communications
interface.
[0193] Connectivity:
[0194] The Client Interface Device enables individuals diagnosed
with a disease, or other groups having similar interests related to
management of disease such as clinical staff members, physicians,
physical therapists, researchers, government employees,
contractors' employees, or employees within the insurance or
financial sectors, to utilize social networking technologies and
social networking sites on the Internet such as Facebook, Google+,
and Linkedln to share information related to individual with
disease management. While social networking and social networking
sites share problems and issues related to computer security and
privacy, the Client Interface Device, and Servers or other
computers and computer systems with which the Client Interface
Devices communicate, can overcome many of these problems by using a
pointer system that provides links to information related to
individuals diagnosed with a disease and disease management or
treatment that resides on protected infrastructure such as Servers,
or other computers and computer systems that provide additional
privacy and security safeguards.
[0195] The pointer system can be as simple as a uniform resource
locator (URL), which may indicate the use of a web protocol such as
HTTP or HTTPS but may also utilize other protocols such as
Extensible Markup Language (XML) or Subversion (SVN) for
version-controlled information and secure communications or data
transfer protocols such as secure shell (SSH) and secure copy
(SCP). The URL can contain an encrypted key or identifier field
that can be understood (decrypted) only by a device containing the
private key of an intended recipient or group of recipients. For
example, the encrypted key or identifier may be understood and
correctly interpreted by a Server or another Client Interface
Device having the correct recipient's private key. Decryption of
the key then provides access to addition information, which may
include information that allows other recipients to access
protected information. The pointer system could use other methods
of pointing to protected information content instead of or in
addition to a URL; for example, a one-dimensional or
two-dimensional bar code can be used, or an image can be used that
contains encrypted data that can be utilized in much the same
manner as an encrypted key field. In this manner, an individual or
an organization can post information relating to disease status,
disease management or services related to disease management on
social networking sites that are accessible and readable only by
individuals, Servers, Client Interface Devices, or organizations
having access to an appropriate private key. Other methods of
secure information exchange can be used, such as a shared symmetric
encryption key that is provided, usually in the payload of a
message protected by encryption using a public/private key pair, to
a group or population of individuals or organizations.
[0196] A key feature of this method is that knowledge of the URL,
bar code, image, or other device or object obtained from a social
network or social networking site on the Internet confers no
information about the underlying identity or identities of
individuals or organizations, or of the protected stored
information, when such individuals or organizations participate in
the services that implement and practice the disclosed method. In
each instance before the information to which the URL or other
device or object references can be accessed or used, in the
preferred embodiment a user is directed to a permission affidavit
specifying the terms and conditions under which the information can
be accessed or used, and to which the accessing entity must agree.
Such agreement can be indicated by a digital signature that can not
be repudiated and as associated with a private encryption key
assigned to the entity.
[0197] Data Exchange:
[0198] FIG. 16 provides details of a DATA TRANSMISSION PROTOCOL for
transmitting an encoded permissions affidavit along with data and
with an identifier and a checksum. This embodiment describes a
process for enabling cross-institutional rapid exchange of
information to the furtherance of rapid assembly of research
questions (FIG. 14A and FIG. 14B). Preferably, a individual with
disease information exchange affidavit is used, which may be a
written document signed by the owner(s) or other individual(s)
having rights to exchange or access the data, and which optionally
may be implemented using a private key. Exchanged data will be
associated with a unique individual with disease exchange affidavit
(FIG. 15). A unique data structure element is to be encoded in the
data structure used by all exchange partners. This facilitates the
addition of future modules within the exchange structure. There are
shown person with disease having a client device 1570, a clinical
EHR 1560, a public or private entity such as a hospital database
1550, an insurance entity 1540, the government represented, for
example, by the National Institutes of Health and the Center for
Disease Control 1520 and an industry interface 1510 representing,
for example, device manufacturers and programmers, all
communicating to form a community registry 1500 for sharing data on
a permissive basis whereby the common EHR may generate specific
cohort databases for specific purposes responsive to the querying
entity. Consents are shown as 1, 2, 3, 4 and 5 identified.
(Industry interface 1510 is, for example, tightly controlled with
explicit consent).
[0199] Method of enabling public private data exchange.
[0200] Method of organizing data for exchange, query, and hosted
collaborative research.
[0201] Information that can be exchanged includes tables of
reports, tables of fields, and previous searches or "bundles". A
permission form for the data exchange is contained within the
"bundle". The data field structures can contain objects such as, by
example, an identifier, a number of elements, an element
declaration, and a type (such as a question, report, calculation,
or request for data). Exchange and use of data are defined via a
private license for outcomes measures by individuals diagnosed with
a disease within the data affidavit. Data available for exchange,
query, or hosted collaborative research can be stored in a Server
or computer or computer system in either memory or persistent
storage such as a hard disk drive, a network attached storage
device, or a solid-state drive. A data-mapping matrix or database
is utilized to associate data with the appropriate party for
exchange and can reside on the same Server or computer or computer
system as is used to store the data made available, or on a
separate Server, computer, or computer system.
[0202] Method of Interface for Upgrade or Downgrade or Information
From Protected Health and Reporting
[0203] A method of verifying permissions of aggregate reports is
disclosed in the form of a reporting permissions matrix (FIG. 17),
database, or similar method of organizing data with permissions for
reporting. Participants can be presented with a permissions matrix
using a graphical user interface implemented by a Client Interface
Device or other computer or device with a radio or check box.
Preferably, the left side of the graphical user interface displays
example data, and the right side shows one or more possible uses;
the roles of the left and right sides can be reversed in an
equivalent implementation. Multiple user verifications are
necessary if items are to be upgraded to the release of granular
data for "profit".
[0204] Method of tracking release or data exchange for the possible
reimbursement of participants
[0205] A Server or other computer or device that stores data for
exchange, query, and hosted collaborative research can preferably
implement a method for a user to obtain permission to use a
particular rating scale and then grant a limited power of attorney
for the use of the rating scale for a defined purpose of
associating exchanged fields with permissions of user and
participant.
[0206] Analytics and Learning Datbase:
[0207] In the reduced case of a single site, the data exchange with
objective measures is represented as (FIG. 18). Even in the case of
data exchange within a single medical center, the exchange and or
blending and or combined reporting of protected and non-protected
health care data may be accomplished (FIG. 19). A method of
developing a learning cohort database is disclosed as follows.
Standard queries, reports, and searches are contained in a master
data table for reporting. In a second table, aggregate "learning"
matrices are populated. Population queries create averages for
recent searches and provide the basis for new tools to be utilized.
Users may create their own search and may also choose from recent
searches or reports. Only responses found to be statically
significant are added to the calculation list. Community partners
and others providing feedback may tailor the interface for
registrants as well as provide a non-computerized modality for
interacting with the registry through the setting of community
outreach events and conjoint volunteers. Objectively measured and
diary data are imported and processed for 1) report generation, and
2) internal use as part of the base of data for which abstractions
occur from the cohort (FIG. 20).
[0208] Data Visualization
[0209] Timeline Individual with Disease to Cohort Assessment
Report:
[0210] A timeline visualization (FIG. 21) is presented and serves
as a reference of where the participant is in the disease process.
Answers to several questions are correlated with others in the
cohort or a selected population to give a relative position of the
subject on the timeline. The timeline can begin with the first
symptom, progress to the first treatment, include when the first
treatment becomes ineffective and a second treatment is added and
then include when medication treatments have failed and then when
surgical treatments have failed, and then when a individual with
disease passes several milestones of loss of ability to participate
in activities of daily living and then progresses to end of life
care and wishes. Based upon aggregate answers to the quality of
life questions of other participants, a range of improvement in
symptoms of the "index individual with disease" is predicted for
the individual with disease. Examples of aggregate answers include:
(for example, for PD: 1) diagnosis of PD, 2) onset of levodopa use,
3) medication refractory status, 4) date of first consideration of
surgery as a next step in treatment, 5) surgery, 6) falls, 7)
meaningful work/leisure activity engagement, 8) independent
living).
[0211] TEST PERFORMANCE: An aim of this embodiment is to enable
youthful and progressed participants to visualize their disease
state progress within the cohort in relative performance of a test
(FIG. 22), for example, a simple motor test, objectively obtained
with respect to medication intake and surgical treatment. Aggregate
results are plotted in time with respect to significant
interventions such as neuromodulation (FIG. 23).
[0212] COMPARE: A method of examining data clustering around Native
American or other cultural/genetic/social factors is provided.
Queries are enabled across multiple sites for maximum analysis
power of the numerator and denominator for a given metric (FIG.
24). Data aggregation is facilitated based upon a permission based
exchange (FIG. 25) and the intended use/user of the data. A unique
identifier 2510 identifies an entity providing encoded permissions
2520, a permissions affidavit 2530, data 2540 and a checksum for
the data transmission for a permission based exchange via allow or
not 2590 so that a query by another 2560 may be responded to with
data 2580 responsive to permission 2590. Statistical measures of
predictive quality, such as sample variance or standard deviation,
can optionally be computed using the data from a cohort or selected
population, and can optionally be visualized using a graphical user
interface. Access to the examination of data clustering can be
enabled using a Client Interface Device or other computer or device
having a user interface.
[0213] A Server, computer, or computer system can implement a
database of providers and provide information on providers
accessible to or appropriate for a individual with disease or
authorized representative of a individual with disease given a zip
code, an address, or information about the individual with disease,
such as gender, age, ethnicity, membership in an association or
other group, or disease status or progression. The database can be
collected from providers or can be derived from an aggregation of
data collected from users who access the Server, computer, or
computer system.
[0214] ENCOUNTER REPORT: An encounter report can be generated by a
Server or Client Interface Device that is a downloadable or
printable progress report germane to a given physician's visit.
Expected outcomes can be included. For example, a representative
method includes a summary with the reporting and or graphical
display of metrics to provide a clear understanding of individuals
diagnosed with a disease progression with medical or surgical
intervention in the setting of a fluctuating disease process. Such
a report may contain, for example items such as: 1) Medication
data, TIMELINE data, TEST PERFORMANCE data, as well as diary data.
Another example of an encounter report would contain aggregate data
relevant to the cohort of those with similar encounters or based
upon the reported data within the system could provide the known
cohort reference data for the provider where the individual with
disease is undergoing the visit. By example, individuals diagnosed
with a disease often ask the provider how individuals diagnosed
with a disease treated by them or with a similar treatment modality
perform on certain outcomes measures or with reference to certain
benchmarks. By example here the individual with disease could
arrive at such an encounter for a surgical procedure with a report
of symptoms before and after treatment by the 1) provider, 2)
institution, 3) other cohort and could ask the question of how
their treatment would compare to the known outcomes of the cohort
or could ask why their case or treatment was similar to or
dissimilar to the cohort group. Should there be a mismatch or
objection of the provider to the denominator chosen or the cohort
chosen to represent the analysis, feedback could be provided to
update the algorithm. By example, should the individual with
disease attend a visit with cohort data showing a 5% infection rate
for a surgical implant and ask if this rate applied to their case,
the provider could state that they expected a 2% infection rate due
to the choice of a lower volume implanted stimulator device and
cite literature linking the overall volume of an implanted device
to the infection rate. The individual with disease could, by
example, return from the visit with comments that the provider
informed them at the visit that the provided cohort data was 1)
valid, however 2) for a different cohort, and 3) could generate a
new cohort analysis by model of implant and location of implant to
associate with the provider's practice over the past, by example 24
months. Therefore the algorithm would "learn" by knowing the
practice pattern of implant and risks. The volume of implant data
is available from the device manufacturer. To the extent that
enrollees grant the retrieval of specific model and serial number
information from the manufacturer or medical repository record of
implants, the determination of device volume in this example would
occur with little effort on behalf of the individual with disease.
There are many other examples of report learning. For example, the
fields requested within a report can be displayed by example on
with use statistics. For example, under this system, individuals
diagnosed with a disease would be shown the most "popular" or most
often selected report based upon the TIMELINE algorithm and
learning to suggest which treatments may be needed in the disease
process. By example, in the case of the surgical implant, such a
individual with disease is more likely to have failed medical
management and would be placed in a different location based upon
the TIMELINE process. In the case of a newly diagnosed individual
with disease, the report may contain, by example, information such
as the percentage of individuals diagnosed with a disease with a
given treatment paradigm who are started on a particular medication
as initial treatment. One could alert individuals diagnosed with a
disease and insurers if there appeared to be a trend for care to be
directed based upon insurance status or other factors and that
questions could be asked. By example, individuals diagnosed with a
disease with insurance status (A) may be started on a dopamine
agonist or other more expensive treatment whereas a self-pay or
uninsured individual with disease may be started on levodopa or
other medication. This example would not be to determine which is
more appropriate medically, as physicians make such informed
decisions with their individuals diagnosed with a disease with a
balance of coverage and resulting expense to the individual with
disease. In this example, however a individual with disease with a
certain insurance status with a statistically known likelihood of
resulting in a certain therapy could be informed of possibilities
for lower cost medication offers from the insurance provider or
pharmaceutical provider or from foundation or private financing to
assist in bridging the gap of treatment cost. By example, there may
be a trial medication offer by a pharmaceutical company for xxx
years of treatment at a reduced price. Such an offering may not be
widely known within the treatment community at large or within the
provider community. Should a report show that individuals diagnosed
with a disease on the TIMELINE or given a certain set of criteria
are asking for their information to be sent to company yyy or
foundation zzz or state government or federal government program
123 in order to facilitate altering the treatment from one pathway
to another, they may ask about this with their provider or inquire
directly with the company to their benefit. Such a report could, by
example, state that 35% of individuals diagnosed with a disease
matching your profile are taking advantage of a free medication
trial by company yyy. This offering and the suitability of the
treatment for the individual with disease could then be discussed
with the care provider during the visit. One can envision many
similar variations of individual with disease information
empowerment within the setting of a brief report provided prior to
a physician encounter.
[0215] INDIVIDUAL WITH DISEASE TO INDIVIDUAL WITH DISEASE
DISCUSSION REFERRAL REPORT: Potential referrals can be displayed on
a Client Interface Device, computer, or other device having a user
interface in response to a request by a individual with disease or
an authorized representative of a individual with disease.
Referrals can be based upon the disease burden of the individual
with disease and upon responses from the cohort. This method
facilitates participant referral for further clinical care or
non-clinical activities modified by responses from the cohort.
[0216] PROVIDER VISIT SUMMARY: This summary includes medication
changes, recommended activity goals, neurostimulation changes with
visualization of new areas of stimulation and advice of data to
log. The home logging can be enabled if the individual with disease
or authorized representative chooses to, and the desired metrics
will then be acquired according to the listing on the individual
with disease visit summary using the user interface capabilities of
the Client Interface Device, computer or other device to which the
individual with disease or representative has access. The collected
data are protected as confidential data owned by the individual
with disease and may be stored within the Client Interface Device,
computer or other device used by the individual with disease or
individual with disease's representative, or may be stored on a
Server with which the Client Interface Device, computer or other
device can communicate. Any exchange of data across public or
shared communications channels or networks is protected from
unauthorized access or use by encryption using one or more
encryption key(s) and method(s) known to the Client Interface
Device, computer or other device and Server.
[0217] Participants Portals:
[0218] Individual with Disease Home Data Entry/Use Portal:
[0219] Method of Entry points for participants include the home
environment as well as in the setting of community regional support
meetings. Technology such as the Client Interface Device, a
computer or computer system, or a device such as a tablet computer
or smart phone (FIG. 8) empowers disease society representatives
(APDA) with linked tools while traveling to attend regional support
meetings. A method enabling participants to visualize their
progress within the cohort based upon participant delivered content
is provided. A method is provided for organizing individual with
disease data for the treatment of Parkinson's disease in an
efficient manner. The method enables participants to visualize
their progress within the cohort in relative performance of a
simple motor test objectively obtained with respect to medication
intake and surgical treatment.
[0220] Reports available for the individual with disease portal
include an INDIVIDUAL WITH DISEASE ENCOUNTER REPORT, INDIVIDUAL
WITH DISEASE TO INDIVIDUAL WITH DISEASE DISUCSSION REFERRAL REPORT,
and INDIVIDUAL WITH DISEASE TO COHORT ASSESSMENT REPORT.
[0221] SOCIAL: Significant hurdles exist for the wide adoption of
social media and connectivity within technology non-savvy
population such as the elderly PD population. To circumvent this, a
data advocate serves as a surrogate for adoption and interaction at
regional group support meetings such as the (APDA). The data
advocate provides ongoing feedback on the 1) data fields collected,
2) reports generated (such as FIG. 3) for participants and partners
in community health, 3) the participant feedback for the ease of
use, 4) the relative impact of in person, kiosk or paper interface
with the registry versus independent access. A method, within the
registry, is provided for displaying potential referrals given the
disease burden of the individual with disease based upon responses
from the cohort or a selected population. Individuals diagnosed
with a disease are able to indicate an interest in participating in
individual with disease referrals and being in contact with others
of a similar representative data profile. A method of utilizing and
determining the impact of social networking on how individuals
diagnosed with a disease feel about their progress with with/out
treatment is provided. The individual with disease or authorized
representative of the individual with disease can utilize these
methods using the Client Interface device, computer, computer
system, or other device such as a tablet computer, a laptop
computer, a desktop computer, or a smart phone or game console.
[0222] Community Support Group Data Portal:
[0223] A method of standardizing, simplifying, and objectifying
clinical outcomes tracking, culminating in population health
measurements of PD individuals diagnosed with a disease in the home
and in the setting of support group-based periodic meetings is
disclosed. The method includes determination of entry points for
participants include the home environment as well as in the setting
of community regional support meetings. Together with community
partners (APDA), the interface for registrants can be tailored and
a non-computerized modality can be provided for interacting with
the registry through the setting of community outreach events and
conjoint volunteers. Specific entry points for participants include
the home environment as well as in the setting of community
regional support meetings. For example, with the partnership of the
APDA, the research coordinator could travel to attend regional APDA
meetings throughout the year as well as monthly meetings within a
city, county, region, or state.
[0224] The disclosed method includes developing a system for state,
national, or global population health able to address diseases
within the restorative neurosciences (such as multiple sclerosis,
essential tremor, dystonia, normal pressure hydrocephalus, spinal
and gait disorders) and beyond. Entry points for participants
include the home environment as well as in the setting of community
regional support meetings.
[0225] Workflow of the embodiment includes: a regional support
group meeting; for example: A data advocate may travel and attend
regional support group meetings. The support network provides
ongoing feedback on: 1) Data fields collected, 2) Reports generated
(for example, FIG. 3) for participants and partners in community
health, 3) Participant feedback related to ease of use, and 4)
relative impact of in person, kiosk or paper interface with the
registry versus independent access. The method includes tailoring
community partner registry interfaces as well as providing a
non-computerized modality for interacting with the registry through
the setting of community outreach events and conjoint
volunteers.
[0226] ASSESS: An aim of an embodiment is to enable youthful and
progressed participants to visualize their disease state progress
within their cohort in relative performance of a simple motor test,
objectively obtained with respect to medication intake and surgical
treatment. Early and late stage disease individuals diagnosed with
a disease are identified, and through a questionnaire, a history of
diagnoses and treatments, or other means individuals diagnosed with
a disease are associated with a position on a timeline is presented
utilizing relevant factors (e.g. for PD: 1) diagnosis of PD, 2)
onset of levodopa use, 3) medication refractory status, 4) date of
first consideration of surgery as a next step in treatment, 5)
surgery, 6) falls, 7) meaningful work/leisure activity engagement,
8) independent living. A visualization of the disease burden is
optionally provided using a display of a Client Interface Device or
computer (FIG. 8). Methods of ensuring early and late stage disease
individuals diagnosed with a disease have meaningful access and
derive meaningful utility from the tools are implemented using, for
example, designated or authorized individual with disease
representatives, or, with appropriate privacy and security
safeguards and permissions, reporting of test result using a Server
or other computer or computer system.
[0227] Population Health and Comparative Effectiveness Research
[0228] The disclosed method influences individual with disease care
with monitored quality metrics and provides a method of
understanding the impact of emerging therapies on limiting human
suffering within the disease (PD) population. The method of OMS
based comparative effectiveness research (CER) aims to empower
individuals diagnosed with a disease, providers and community
partners (APDA/NPF) in identifying and reversing treatment
disparities in PD healthcare delivery in a selected PD
population.
[0229] The disclosed embodiments provide a method of expanding
early pilot study data though individual with disease rapid
participant recruitment to facilitate highly powered inquiries with
broad application in local, regional, state, national, and global
public health CER inquiries The method of providing reports aims to
lowering the cost of understanding treatment differences and
increase the velocity of validating new treatments for the clinic.
By example, a research associate or individual with disease, or
physician may identify a trend in diagnosis or measurement or
treatment of disease. By example, should a physician propose a
method of performing a fifteen-minute objective test to be
performed using devices freely available within the individual with
disease and provider community, allowing unprecedented ease of
participation for longitudinal testing over time, such a proposal
could be a target for rapid dissemination. By this example, the
proposal could be posted within a research portal with
advertisement of the proposal guided by the selection criteria of
the investigator. Users could affirm or vote in favor of the
project and to the extent the project could be performed outside
the clinical environment, data could be aggregated quickly. By
example, users could organize under a proposal that individuals
diagnosed with a disease would perform a pronation/supination
bradykinesia test on a daily basis for a period of time, such as
six months, while various objective data were recorded. Health data
such as medication intake, visits to providers, quality of life
information, travel information, physician measured metrics could
be aggregated to answer questions about treatment during the year.
For example around the time of surgical intervention such as deep
brain stimulation. The method facilitates early adoption of new
therapy such as deep brain stimulation through the use of monitored
quality metrics.
[0230] An aspect of the present invention is a method of social
media monitoring and integration utilizing analysis of public data
such as twitter, Facebook, and similar open and publicly reported
events. For example, the reporting fields and aggregate data fields
are searched with a search engine and other technologies as in the
following example of cohort database permissive generation. In
cooperation with such a data provider, for example Google, a report
is generated regarding the frequency and location of searches
similar to a individual with disease's location or placement on the
TIMELINE. Given a cohort location of, for example 250 miles from
home, a distance an individual with disease may reasonably travel
for regional care, location of search term density can be
displayed. For example, if it could be known that a certain
population of individuals diagnosed with a disease resided within a
community with two treatment centers located 250 miles apart along
an interstate distance, one could combine density of search data of
those within the intervening lenticular shaped 250 mile driving
distance arc from both centers. One could then determine the
frequency of twitter feed and Internet searches based upon location
by IP address or GPS location during the search and process the
relationship between cost, quality, and travel for the cohort. One
could report based upon these aggregate data and transmit the
results over mobile or other networks for reporting and assistance
in presenting data surrounding the choices that individuals
diagnosed with a disease with similar characteristics are making.
One can combine the clustering of the individuals diagnosed with a
disease in a population map with the clustering of providers and
with a heat map of activity of search terms to demonstrate activity
within a region. Additionally, active research or publications by
physicians or others treating individuals diagnosed with a disease
at the centers can be selectively added to the cohort database
based upon impact factor and regency of the publication and NIH or
other funding awarded as well as preclinical, clinical, or other
research provided. An overall population treatment impact factor
can be computationally determined. The algorithm can be tuned via
neural network or other learning algorithm by the actual responses
of the subset of individuals undergoing treatment by inquiries as
to their relative weighting of cost, travel, and import of the
factors involved in the algorithm. A suggestion item could be added
and a calculation of the most frequently suggested addition could
be added to determine when and if further inquiries should be
added. For example: Treatment Impact Factor (provider) is derived
from weight 1.times.(average publication impact
factor).times.average number of publications.times.average number
of citations.times.[1/(current year--average publication
year)]+weight 2.times.(NIH funding dollars average per year of
practice)+weight 3.times.number of active, enrolling clinical
trials+weight 4.times.number of preclinical trials active+weight
5.times.number of collaborators named on publications since
beginning practice in this location+weight 6.times.number of known
outreach speaking engagements outside the host institution in past
2 years+weight 7.times.(multiple other factors).
[0231] Factors measured from an institutional ranking perspective
include: number of physicians treating a disease process, average
wait time for clinic appointment, number of regional offerings
unique to the institution, number of voids of service or offerings
causing travel to the adjacent facilities. These are example
factors to be placed in the learning algorithm similar to that for
the individual provider.
[0232] Public Health Protal/reporting
[0233] Public health reports are provided based upon the permission
matrix to enable determinations of numerators and denominators of
the population with disease or undergoing therapy as well as
density and provider/resource availability by zip code, an address,
or information about the individual with disease, such as gender,
age, ethnicity, membership in an association or other group, or
disease status or progression. CER of medical and surgical
interventions is possible by zip code.
[0234] An aspect of the disclosure provides a method of improving
the health of the people in a selected population by quantifying
results of health care intervention. To the extent treatment
changes occur over time, an analogy can be drawn to continuous
quality improvement. Individuals diagnosed with a disease in the
community could benefit from avoiding randomization to a
non-treatment arm under the models of evidence-based medicine
employing randomized trials. Methods of developing and validating
tools for measuring the improvement in the health of the target
population may be expanded through the use of the community based
registry system. For example, after deep brain stimulation surgery,
someone may read a report of concerns regarding traveling in a
hybrid electric vehicle or other vehicle with an electromagnet such
as driving a ferryboat with electric motors driven by motors or
turbines such as electric trains. Such an evaluation of automobile
travel, by example, could occur by the method of an application for
mobile health with connectivity such as Bluetooth, which wirelessly
paired with the host automobile or otherwise determined the travel
device. Aggregate GPS data and other data from a device such as a
wristwatch device able to perform measurements in the background
could determine through aggregate algorithms if a user of the
registry system were driving the target automobile based upon wrist
and arm motion or based upon visual input from devices such as
Google glass or other similar device and determine position within
the vehicle based upon arm movement and magnetometer date. Knowing
the model number of the automobile and interfacing with the
automobile manufacturer, one could obtain electrical field maps
from the automobile testing and understand the relative location of
the device within the automobile. Combined with surgical
information regarding unilateral versus bilateral implantation of
the cranial devices and implantable pulse generators in the case of
DBS, one could determine the likelihood of an open "loop" allowing
for an inductive energy transfer. Given that 1% of the population
over 60 has Parkinson disease and many drive a Prius with Bluetooth
pairing technology, and a subset of those have DBS neuromodulation
where the device and stimulation information can be known from
medical records, one could see by this example, how a community
based approach allowing the blending of medical and non-medical
data on behalf of the participant could yield a significant number
of individuals diagnosed with a disease in the numerator and
denominator of a question such as "does one reasonably feel safe in
an electric car with DBS for PD?". The alternative in this example
is that there is a single case report of such potential
interference with the individuals diagnosed with a disease, device
manufacturers, physicians, and automobile manufacturers with no
clear way to easily answer a question about the possible effects of
these interactions in the community despite a large cohort of
potentially affected participants in a time when neurostimulation
in the retiring population is rising concomitant with the use of
electric motor-containing vehicles. By example linking to other
sections in the current patent application, one could envision a
report of the most actively participated or recruited to studies
given a position in the TIMELINE. There is reasonable expectation
that industry or investment such as "kickstarter" and other
"croudfunding" modalities could be linked to this method. One could
establish a baseline in those PD individuals diagnosed with a
disease driving electric motor powered vehicles and then seek
funding based upon preliminary data for the next phase of the
study. Supposing such an inquiry led to a significant finding,
further randomized trials could be planned resulting in a finding
which may influence automobile or neurostimulator design.
Additionally, an alert could be set if the client user device
magnetometer 5265 detects magnetic fields associated with the
electromotor above and beyond an average acquired within the cohort
(FIG. 22). Such an App based approach could alternatively gather
background magnetometer data aggregated by type of automobile and
upload to the central server for further governmental and industry
reporting.
[0235] In summary, the several embodiments propose methods of
developing and validating tools for measuring the improvement in
health of the target population, methods of rapid integration of
global micro-research tools into the clinical and community
settings, method of facilitating participant/individual with
disease inquiries within the dataset, methods of collaboration with
academic medical centers, method of collaborating with state and
federal government, method of collaborating with PD community
centers, method of developing objective measures (OMS) of the
"health" of the disease cohort (e.g. regional PD population),
method of developing a system for statewide population health to
address diseases such as multiple sclerosis, essential tremor,
dystonia, normal pressure hydrocephalus, spinal and gait disorders,
method of Expanding pilot studies expected to have broad
application in public health CER, lowering the cost of
understanding treatment differences and increasing the velocity of
validating new treatments for the clinic, method of creating
public/private hybrid partnerships for CER, method of advancing
this modality rapidly to the national scale through collaboration
with the NPF QII database and the neurosurgical N2QOD database in
accordance with the principles of the present invention.
[0236] Financial:
[0237] Method of supporting insurance approval of treatments:
Method(s) of permission-based interfacing with either insurance
carriers' data systems or hospital data systems permit selected
extraction of information for insurance purposes, with individual
with disease consent with appropriate security controls. The
disclosed system, implemented by one or more Servers and accessed
by Client Interface Devices or other computers or computer systems,
supports insurance approval of treatments and also supports
feedback or rebates which individuals diagnosed with a disease me
subscribe to in order to bargain directly with insurers for their
current or future care future care. An example of this would be an
individual with disease who consents to monitoring for a period of
six months in exchange for a reduction in premiums.
[0238] Academic:
[0239] Method of facilitating a clinical validation and
translational comparative effectiveness research (CER) though a
community registry environment: Clinical validation and
translational research and CER are facilitated by a
permission-based release of the data and a portal for pre-approved
data aggregation and publication without the need for a new
institutional board review of each subset of the inquiry. Specific
individual with disease consent can be obtained to reach out to
state and hospital databases on their behalf for the specific
purpose of research. The interface can be implemented using the
Client Interface Device and digital certificates or public/private
keys, where a Server can act on the individual with disease's
behalf and request and obtain data from another computer or
computer system. Included in the embodiment is a method of allowing
trial data or implementation of data specific requests to be widely
distributed by the use of a single study number representing the
encoded methods of research. Individuals diagnosed with a disease
can participate from home using Client Interface Devices or other
computers or devices to facilitate this research if needed.
Specific entry points for participants include the home environment
as well as in the setting of community regional support meetings.
For example, with the partnership of the APDA, the research
coordinator will travel to attend regional APDA or similar meetings
throughout the year as well as monthly meetings within the
individual with disease's region. The APDA or a similar group can
provide ongoing feedback on the 1) data fields collected, 2)
reports generated (FIG. 3) for participants and partners in
community health, 3) the participant feedback for the ease of use,
4) the relative impact of in person, kiosk or paper interface with
the registry versus independent access. Methods for feedback to the
individuals diagnosed with a disease are allowed; including
tracking of which research protocol the individuals diagnosed with
a disease' data was contributed to in the end. Additional feedback
is provided to allow a participant to know where they reside in the
midst of an ongoing research program. These algorithms are then
"published" internally for individuals diagnosed with a disease to
select to ask questions of their location within a specific
cohort.
[0240] The method and system provides individuals diagnosed with a
disease an ability to visualize their progress within a selected
cohort or population by providing and optionally comparing
objective measurements of performance of a simple motor test,
obtained with respect to medication intake and surgical
treatment.
[0241] PROVIDER: Method of decreasing health care provider burden
in assessments: An example of this method is the movement disorders
outcomes report (FIG. 26) generated for the provider. A reports
screen guides the user to the appropriate report. Reports are
generated for age and gender breakdown of surgical implants (e.g.
DBS, FIG. 27), anatomic target and entry points (e.g. DBS, FIG.
28), Consent Report (FIG. 29), Surgery Report (FIG. 30), Calculated
Active X/Y/Z (FIG. 31), Reports--Left and Right with Distance from
Ave Target (FIG. 32), Active Implant Report (FIG. 33), Outcomes
Report 1 (FIG. 34A and FIG. 34B), All active implants with
impedances (FIG. 35). A provider can access an INDIVIDUAL WITH
DISEASE ENCOUNTER REPORT, INDIVIDUAL WITH DISEASE TO INDIVIDUAL
WITH DISEASE DISUCSSION REFERRAL REPORT, and INDIVIDUAL WITH
DISEASE TO COHORT ASSESSMENT REPORT. A physician may generate a
PROVIDER VISIT SUMMARY.
[0242] DECISION SUPPORT: The disclosed method provides use metrics
such as: 1) Time from diagnosis to significant milestones including
in the case of PD segment 1 (first medication administration until
adding second medication: length of time in this segment, number of
health care provider visits, number of visits to physical therapy
or exercise modalities, average travel during this segment,
medication use during this period), segment 2 (adding of second
medication [often levodopa] until considered medically refractory:
length of time in this segment, number of health care provider
visits, number of visits to physical therapy or exercise
modalities, average travel during this segment, medication use
during this period), segment 3 (medication refractory until
decision for restorative neurosurgery: length of time in this
segment, number of health care provider visits, number of visits to
physical therapy or exercise modalities, average travel during this
segment, medication use during this period), segment 4
(perioperative: length of time in this segment, number of health
care provider visits, number of visits to physical therapy or
exercise modalities, average travel during this segment, medication
use during this period, target selection, days in hospital,
insurance provider, hospital visited, compilation, implant location
(ac/pc xyz), activated at time of hospitalization (yes/no), initial
active stimulation parameters including location, estimated volume
of tissue activated at time of activation, impedance pairwise and
monopolar of all contacts, rechargeable vs. primary cell
technology, simultaneous bilateral vs. staged bilateral
implantation vs. unilateral implantation with planned interval
greater than 6 months between implantation, preoperative
neuropsychometric testing including mini-mental status exam
results, diary results including questionnaire data such as
Parkinson's disease questionnaire 8 and 39, Hamilton depression
score preoperatively, unified Parkinson disease rating scale total
and motor (1987 Fahn) on and off medication preoperatively,
objective measures preoperatively on and off medication including,
timed up and go, bradykinesia assessment including finger tapping,
pronation supination (gyroscope), berg balance test, and other
metrics), segment 5 (post discharge until 3 months follow-up:
length of time in this segment, number of health care provider
visits, number of visits to physical therapy or exercise
modalities, average travel during this segment, medication use
during this period, target selection, days in hospital, insurance
provider, hospital visited, compilation, implant location (ac/pc
xyz) on follow-up scan if available, device battery status and
voltage, active stimulation parameters including location,
estimated volume of tissue activated at time of activation,
estimation of energy delivered (to assess battery life), impedance
pairwise and monopolar of all contacts, preoperative
neuropsychometric testing including mini-mental status exam
results, diary results including questionnaire data such as
Parkinson's disease questionnaire 8 and 39, Hamilton depression
score preoperatively, unified Parkinson disease rating scale total
and motor (1987 Fahn) on and off medication preoperatively,
objective measures preoperatively on and off medication including,
timed up and go, bradykinesia assessment including finger tapping,
pronation supination (gyroscope), berg balance test, and other
metrics), segment 6 (3 months follow-up until 6 months: length of
time in this segment, number of health care provider visits, number
of visits to physical therapy or exercise modalities, average
travel during this segment, medication use during this period,
target selection, days in hospital, insurance provider, hospital
visited, compilation, implant location (ac/pc xyz) on follow-up
scan if available, device battery status and voltage, active
stimulation parameters including location, estimated volume of
tissue activated at time of activation, estimation of energy
delivered (to assess battery life), impedance pairwise and
monopolar of all contacts, preoperative neuropsychometric testing
including mini-mental status exam results, diary results including
questionnaire data such as Parkinson's disease questionnaire 8 and
39, Hamilton depression score preoperatively, unified Parkinson
disease rating scale total and motor (1987 Fahn) on and off
medication preoperatively, objective measures preoperatively on and
off medication including, timed up and go, bradykinesia assessment
including finger tapping, pronation supination (gyroscope), berg
balance test, and other metrics), segment 7 (6 months until 1 year:
length of time in this segment, number of health care provider
visits, number of visits to physical therapy or exercise
modalities, average travel during this segment, medication use
during this period, target selection, days in hospital, insurance
provider, hospital visited, compilation, implant location (ac/pc
xyz) on follow-up scan if available, device battery status and
voltage, active stimulation parameters including location,
estimated volume of tissue activated at time of activation,
estimation of energy delivered (to assess battery life), impedance
pairwise and monopolar of all contacts, preoperative
neuropsychometric testing including mini-mental status exam
results, diary results including questionnaire data such as
Parkinson's disease questionnaire 8 and 39, Hamilton depression
score preoperatively, unified Parkinson disease rating scale total
and motor (1987 Fahn) on and off medication preoperatively,
objective measures preoperatively on and off medication including,
timed up and go, bradykinesia assessment including finger tapping,
pronation supination (gyroscope), berg balance test, and other
metrics, stimulation induced side effects including speech,
balance, cognitive changes including executive function changes),
segment 8 and beyond (yearly intervals: length of time in this
segment, number of health care provider visits, number of visits to
physical therapy or exercise modalities, average travel during this
segment, medication use during this period, target selection, days
in hospital, insurance provider, hospital visited, compilation,
implant location (ac/pc xyz) on follow-up scan if available, device
battery status and voltage, active stimulation parameters including
location, estimated volume of tissue activated at time of
activation, estimation of energy delivered (to assess battery
life), impedance pairwise and monopolar of all contacts,
preoperative neuropsychometric testing including mini-mental status
exam results, diary results including questionnaire data such as
Parkinson's disease questionnaire 8 and 39, Hamilton depression
score preoperatively, unified Parkinson disease rating scale total
and motor (1987 Fahn) on and off medication preoperatively,
objective measures preoperatively on and off medication including,
timed up and go, bradykinesia assessment including finger tapping,
pronation supination (gyroscope), berg balance test, and other
metrics, estimated device battery life remaining, complications,
stimulation induced side effects including speech, balance,
cognitive changes including executive function changes). These
metrics may be stored in one or more Servers, which may communicate
with Client Interface Devices or other computers or computer
systems or devices to implement upload, download, viewing, and
access control features of the method such as authentication,
granting and revocation of access privileges, non-repudiation,
logging, and audit trail records.
[0243] A computerized system integrating data transmitted over
wireless or wired or tethered communication systems to aggregate
data from the clinic to treatment facilities, to the home and or
community environments. The proposed connected and mobile
embodiments facilitate cross referencing with internal and external
databases including the Medicare database to establish cost for the
each individual with disease, segment of care, category, and
potential therapy. By example, while evaluating the six-month
improvement of individuals diagnosed with a disease with deep brain
stimulation or other intervention, medication use is a valid
outcome measure. To the extent a rigorous and reliable medication
history is not available, or in addition to aggregate data on
mediation use, the payer could provide reimbursement data for
medications. One could receive data from such an inquiry on a
spectrum of coarse to granular data level such as the reimbursement
of a medication for a individual with disease (boolean0 [coarse] to
number of refills of a medication, doses, dates and times of
refills to actual cost information. Length of stay inquiry as well
as the neurostimulator implantations equipment and implantation
dates are used to calculate average reimbursement based upon
available payer data. Other quality of life metrics document impact
on quality of life such as quality metrics supporting the expense
of the surgery including return to work, quality improved life
years, improvement in functional scales, improvement in objective
measures, and improvement in social medial and other reports of
happiness and quality of life. Metrics of comparative effectiveness
are established based upon the above stated and other metrics and
statistical methods of power analysis and other analysis are
provided to establish scientific and other validity for treatment
modalities. In the event of non-powered results, and establishment
of recommended number of numerator or denominator additions are
included to assist with recruitment In support of clinical trials
and quality improvement metrics, estimates of time and cost are
used to power a realistic number of individuals diagnosed with a
disease and expense required to achieve certain follow-up goals. A
drop-out rate is calculated at different points in therapy and in
follow-up, and methods including telephone calls, reminder e-mails,
and direct mailings are used both the attempt to assess the reasons
for follow-up loss, make changes to ensure compliance and
retention, and add feedback to the improvement of the system. The
data advocate will review these results on a periodic basis for
integration in quality and other initiatives.
[0244] Details of the Neurosurgical Database Embodiment:
[0245] Deep brain stimulation (DBS) is a form of neuromodulation
used within the restorative neurosciences and has been widely used
as a strong therapeutic measure for various movement disorders and
psychiatric deficits, and the treatment of epilepsy. Notably, the
location of DBS implant is crucial to the efficacy of the surgery.
The full knowledge of implant leads relative to the brain
anatomical structures is critical for surgery quality control and
future improvement as well as for clinical outcomes of
postoperative stimulator programming. The complexity of
surgery-data production and management has been a major barrier for
the surgeons to effectively improve the surgery quality and to
communicate with the individuals diagnosed with a disease regarding
the surgery quality. Systematic methods are needed to help the
neurosurgeons and members of the treating neuromodulation team with
the implant lead-location data input, analysis, and display. This
disclosure presents a connected system to meet and integrate
multiple DBS surgery-related data processing and analysis needs.
This refined care management database and method is targeted at
providing metrics to enable decision support allowing treatment
quality improvement and thereby clinical practice outcome
improvement.
[0246] This embodiment addresses workflow and data transfer hurdles
impeding the analysis of implant efficacy at the level of the
individual surgeon or institution, yet forms a data structure basis
for multi-site access. The flowchart below is a brief summary of
the surgery data acquisition, storage, analysis, and display. There
have not been any commercial programs, automated methods, or any
systematic procedures available for the surgeons to manage the
surgery data. This system develops and integrates the following
components to a plug-and-use system: web based data acquisition
system, wireless access device or Client Interface Device with
algorithm for encoding data input from neurostimulator device,
secure database, data structure, web based data retrieval system or
Server, web based 3D display system using a Client Interface
Device, and statistical analysis system with presentation of
results using a Client Interface Device. Further, the application
features include a web based data acquisition system using a Client
Interface Device, and wireless, web-enabled device entry using a,
possibly second, Client Interface Device. In all cases, the Client
Interface Device may be a special-purpose or customized device
designed for the indicated purpose or a computer or computer
system, including consumer-grade devices such as tablet computers,
laptops, and smart phones running one or more stored programs to
implement the stated purpose(s). A matrix of matrix concept will be
used to order data for acquisition, display, and analysis. N
dimensional registration will be used.
[0247] The following primary data input and storage format is
implemented in the system:
[0248] Object Oriented Data Structure for Functional Neurosurgery
for the Electronic Medical Record
[0249] Deep brain stimulation (DBS) has been widely used as a
strong therapeutic measure for various movement disorders and
psychiatric deficits. Notably, the accuracy of DBS implant location
is crucial to the efficacy of the surgery. The full knowledge of
implant leads relative to the brain anatomical structures is
critical for surgery quality control and future improvement as well
as for clinical outcomes of postoperative stimulator programming.
However, there have not been systematic methods to help the
surgeons with the implant lead-location data input, analysis, and
display.
[0250] Individual with Disease Tracking Moduel:
[0251] A surgical tracking module to allow the user to understand
one component of the timeline. An input screen tracks factors
important to surgical perioperative care (FIG. 36). A report of the
individual with disease-tracking module (FIG. 37) allows the user
to review the cohort with granularity and understand the metrics of
flow of the cohort through the surgical procedure. Alternatively,
the TREATMENT TIMELINE will visualize the cohort as individual dots
or items where one can hover or click on the dot for further
information. The travel along the surgical pathway of the cohort
can be compared across sites for quality improvement and throughput
considerations. An automated aggregate report automatically
calculates the mean time from first contact or similar event to the
next metric such as date of surgical consideration to the date
surgery is planned to the date the surgery is completed. This
algorithm takes into account all required steps within the protocol
such as in the case of DBS surgery, preoperative cognitive and
neuropsychometric evaluations, physical therapy evaluations,
objective measures evaluations, and other similar metrics.
Cross-institutional benchmarks can be used in insurance or
government reporting to demonstrate efficiency of care delivered.
When available, cost data associated with each step and with the
aggregate treatment are reported and able to be compared across
institutions.
[0252] Surgical Module:
[0253] The following primary data input and storage format is
implemented in the system: (FIG. 38) allowing the tracking of
individual individuals diagnosed with a disease from planning to
scheduling to surgical completion outcome.
[0254] The Surgery Scheduler Screen (FIG. 39) allows all pending
surgeries to be seen across the collaborative cohort. Providers
from different specialties view and plan metrics for the upcoming
surgery including: Surgery ID, Surgery Date, Availability of
Selected Resources, Hospital, Individual with disease, Procedure,
Referring Physician, DOB, Age, Record locator numbers, and
Diagnosis.
[0255] The Surgery Record interface appears as in (FIG. 40) and
(FIG. 41) with a Surgery Record detail having the overall data
structure organization described in (FIG. 42).
[0256] The Surgery Record example data structure is currently
implemented as follows: Surgery Record Data Structure:
{Stereotactic Information (FIG. 43), Brain Metrics (FIG. 44), Brain
Imaging Data (FIG. 45), Surgery Data--Preoperative (FIG. 46),
Surgery Data--Diagnostic Studies (FIG. 47), Surgery
Data--Intraoperative (FIG. 48), Surgery Data--Complications (FIG.
49), Programming Information--Including active implants/contacts
and outcome measures (FIG. 50), Outcomes Rating Subscores in
Different Conditions (Examples of rating subscores, including but
not limited to: PDQ 39, UPDRS III; (FIG. 51))}:
[0257] INTRAOPERATIVE TRAJECTORY LOGGING: Tracking of implant
trajectories planned (FIG. 53), and actual (FIG. 52) including
microelectrode recording is provided as follows: Given these
objects:CRW Frame (Frame Space): Always: Frame space (x, y, z,
ring, arc) [4 degrees of freedom]; a neuro-surgical drive, for
example, an Alpha Omega LTD of Nazareth, Israel NeuroNav Drive.TM.
microdrive (Perpendicular to Trajectory): XY offset+depth [3
degrees of freedom]; BenGun insert (Perpendicular to Trajectory,
x=0, z=0 lines of microdrive and Ben-gun are parallel): Orientation
+5 options. Intracranial trajectories may be used to deliver single
or multiple payloads or implants or therapies along linear or
curved or via ultrasonic or radiosurgery methods. Examples of
delivered therapies with an equation describing the therapy or
implant include, but are not limited to implantable electrodes via
the frame based, MRI guided (FIG. 54), or other approach (DBS,
cortical and surface electrodes (FIG. 55), (FIG. 56), (FIG. 57),
(FIG. 58)), delivered therapy via infusion via the vertex approach
(FIG. 59), trans-frontal approach (FIG. 60) or other approaches
involving the delivery of single or multiple (FIG. 61) or shaped
(FIG. 62A-C) infusion payloads, used for gene therapy, protein
delivery and other therapeutics, light beam therapy such as laser
ablation, stereotactic radiosurgery delivering single or multiple
doses of beam radiation or fractionated and tailored radiation as
well as other delivered therapies which may be tracked and
analyzed.
[0258] The following mathematical calculations may be built into
the system for the purpose of data transformation, analysis, and
output: ACPC xyz off pre-op MM, Choose Initial Anatomic Target, CT
Scan with Frame Fiducials, Fusion of MRI to CT Scan; Derivation of
Initial Anatomic Target in Frame Space (x, y, z), Trajectory
Planning in Frame Space (ring, arc), Intra-Operative Microelectrode
Recording Passes (CRW frame x, y, z, ring, arc; micro-drive xy
stage; Ben-gun orientation and 1 of 5 pre-determined Ben-gun
slots), Derivation of Final Anatomic Target in Frame Space,
Post-Operative Mill or CT Scanning (this scan has brain shift due
to post-operative changes), Re-determine ACPC on Post-Operative
Scan, Measure Post-Operative Electrode Location with T1 (MM
parameters: GE 1.5 Tesla, TE, TR, Voxel size, spin, flip angle),
Determine Errors, 3D Visualization of Microelectrode Recording
Passes (Initial Anatomic Trajectory, Intra-Operative MER
Trajectories, Final Anatomic Trajectory, Final Trajectory); Updated
Current Active Contact(s) and Volume of Tissue Responding
Calculations,; Integration of MER Trajectories and DBS Implant
Location into Individual with disease Specific Atlas with Segmented
Nuclei; Population Atlas with Segmented Nuclei; Overlay of Volume
of Tissue Response on Segmented Tissue Atlas and Population Atlas,
Correlation of Electrode Location and VTR to Individual with
disease Clinical Outcome, Statistical Modeling to Suggest Best
Future Implant.
[0259] Use of This Target for Implantation without MER under Real
Time Imaging such as the Interventional Mill Suite
[0260] Correlation of electrode parameters and outcomes or physical
measures. In the case of implanted devices such as deep brain
stimulator implants, the parameters of stimulation are used to
calculate a tissue activation volume map overlaid with relevant
anatomical correlation in order to derive the stimulation related
effect within the cohort of and the efficacy of the location and
programming based effects. In the case of measures of physical
changes such as drug delivery, a record of parameters associated
with delivery are correlated with known local changes over time to
generate a delivery map related to the therapy showing that
delivery to a certain location appears more efficacious than to
another. In the case of fluidic delivery along a linear trajectory,
a specific technique associated with multiple collinear infusions
has been reported as novel and related to outcome, namely the
technique of delivering multiple trajectories with sequential
advancements of the catheter versus retractions. As we have shown
this technique in gel (SILLAY 2013) and animal models is more
spherically round and delivered in accordance with desired infusion
clouds, this is a specific example of a recorded volume of
distribution over time. We describe this strategy as novel for the
first time and believe the technique of infusion, also known as the
infusion protocol or strategy warrants inclusion within the data
structure. Additionally, any preoperative infusion planning and
modeling in 3D warrants recording as well as the differences
between the delivery plan and that which was delivered. Metrics for
delivered substrate density can be recorded in a normalized or
individual with disease specific atlas and referenced to internal
landmarks and internal functional anatomical structures to
correlate differences in delivery over a 3D space to individual
with disease specific and cohort outcome over time.
[0261] The report data structure is summarized as follows: 3D Plot
of location of implant; 3D plot of active stimulation parameters;
3D Plot of location of active contacts; 3D Plot of location of DBS
electrodes; 3D Plot of location of any forms of surface electrodes;
Data summary (variance of implants).
[0262] Surgical Implant Analysis with Respect to Gravitatinal
Effects:
[0263] DETERMINING AC/PC POSITION WITH RESPECT TO GRAVITY. Method
of measuring the relative position of the subject's brain to
gravity using a handheld device: Head position accounting for
gravity: Head position is an important factor in the degree and
direction of intracranial brain shift during stereotactic surgery.
A Client Interface Device containing appropriate sensors, such as
an Apple iPhone or iPad running the iOS operating system and a
stored software program (app) with a stored Transform matrix from a
surgical planning station can be utilized. The relative force of
gravity on the brain can be derived from a reference scan with a
known orientation to gravity (iMRI surgery, (FIG. 63)). Documenting
brain position over time is possible with additional assistance of
the gravity component of surgery during the implantation. Figure
(FIG. 64) demonstrates the relationship of internal landmarks of
the brain and head position relative to gravity.
[0264] Accomodation for Intracranial brain Shift:
[0265] Background and Technical aspects of the embodiment: Deep
brain stimulation (DBS) has been widely used as a strong
therapeutic measure for various movement disorders and psychiatric
deficits. Its neural mechanisms still have remained uncertain.
Notably, the accuracy of DBS implant location is crucial to the
efficacy of the surgery and implant variance has been reported
(FIG. 65). DBS lead location errors are closely related to
postoperative clinical outcomes, surgery complication, and
long-term individual with disease satisfaction. Error is introduced
with the shifting brain during intracranial surgery. Regarding the
implant accuracy, it has been commonly observed of the discrepancy
between the presumed final anatomical target and the measured final
target. These differences may represent aggregate errors including,
but not limited to, (1) frame error, (2) intra-operative brain
shift (FIG. 66), calculation errors of lead offset [in the plane of
AC/PC internal landmarks (FIG. 67), with respect to the relative
depth of the electrodes with respect to the intended trajectory
depth (FIG. 68), and as radial error with respect to the intended
trajectory (FIGS. 69)] and (4) MRI distortion due to lead location
artifact. How these individual factors, however, influence the lead
location errors has been the subject of recent study in the
literature, however further work is warranted. Notably, it has not
been systematic methods for the precise evaluation of lead location
errors. Error is commonly measured either as XY error (within the
AC/PC plane, (FIG. 67), RADIAL error (FIG. 69), or DEPTH error
(FIG. 68). Existing methods have not addressed several errors
sources. We describe novel algorithms for the calculation of brain
and implant movement with respect to internal and external
landmarks (implant error). A high resolution CT scan acquired in
two dimensions and added stack-wise to create a 3D volumetric scan
or a de novo acquired 3D scan is obtained (alternatively, an MRI
scan of the brain can be obtained) on of lead location errors.
Illustration of brain implant with respect to landmarks associated
with the stereotactic frame as well as bony landmarks of the
individual with disease (FIG. 70) (adapted from Sillay, Kumbier,
Ross et al. 2012, FIG. 5)). In particular, radial error is the one
of the major factors affecting therapy as the electrode must be
removed and re-inserted to correct for radial error, however
stimulation programming changes are able to adjust stimulation
within a multi-contact montage. In the absence of correct coverage
of error sources, the existing scarce algorithms may not generate
the accurate DBS lead location errors.
[0266] Method of determining the position of the brain at the time
of implantation of a rigid device, which becomes flexible over
time. Participants are able to upload a standard DICOM image set
from a Client Interface Device or a computer or computer system
over a web based acquisition system or alternatively instruct a
Server or other computer system to transfer images to the registry.
The representative images are noted as to the time with respect to
the intracranial surgery as well as the expected implants. Manual
or automatic segmentation of the brain electrodes is performed. The
tip of the electrode and trajectory of the active electrode montage
is calculated. The entirety of the electrode is segmented in order
to determine the relative retraction of the electrode during the
time of resolution of intracranial changes. The eigenvector of the
implant with origin at the tip is calculated. The active
stimulation parameters are applied to the eigenvector and electrode
configuration to determine the location of stimulation (described
separately). The brain shift calculated retraction of the electrode
is added in a cranial direction along the eigenvector in the event
intracranial pneumocephalus was noted on the scan. The degree of
this change applied is described separately and related to the time
since implantation of the device.
[0267] Method of accounting for motion of the brain within the
skull and deviation of the brain implant with reference to internal
and external landmarks: The anterior commissure, posterior
commissure, and midline point at the cranial vertex are identified
to establish the relationship of image space to AC/PC space. This
is performed either with internal or external calculations.
Calculations are performed to record the gravitational vector at
the time of surgery when within an optical tracking environment,
frame-based environment (FIG. 71) or other environment using a
smart-phone or other gravitational sensor containing unit (FIG.
72). In the case of a more relative recumbent position (FIG. 73),
versus a more upright position (FIG. 74) the risks of air embolism
(a surgical risk) are increased, while the more recumbent position
may be associated with more antero-posterior brain shift.
[0268] Amnulatory Care Clinical Model
[0269] The system provides aggregate clinical and device
programming and outcomes measures as well as provision for
subjective measures and objective measures of treatment to be
included, and reported. When objective measurements are
transferred, a checksum is provided and incoming data are pooled
for review if there is any question regarding the information
destination (FIG. 75). The summary screen provides the report
summary (FIG. 76A-D) and (FIG. 77) for further navigation. The
programming visit screen is selected (FIG. 78) and (FIG. 79).
Alternatively, the surgical treatment summary is reviewed (FIG. 80;
FIG. 81A-B).
[0270] Determining Location of Stimulation:
[0271] In order to prepare for stimulation versus location analysis
and potential closed loop stimulation algorithms, the location of
stimulation within a given coordinate system is determined. An
implantable brain device may have multiple electrodes of a given
confirmation and orientation (A Medtronic 3387 quadrapolar lead has
a symmetric quadrapolar montage 1.5 mm in height, 1.5 mm in
interspace, and 1.27 mm in diameter) with the ability of activation
of one or many electrodes. To obtain the optimal clinical outcomes
after DBS surgery, individuals diagnosed with a disease are
required to undergo stimulation programming by the medical care
providers by changing programming of one or more of the parameters
within a possibility of may thousands of selections: (1) active
contact(s) combinations, (2) monopolar contact versus bipolar
contacts, (3) voltage, (4) frequency, and (5) pulse width. The
centroid of active stimulation is determined from the lead tip
given implant geometry and calculated (FIG. 82).
[0272] Stimulation Versus Lead Location Analysis
[0273] An accurate location of implants and active contact(s) is
correlated with clinical outcomes (e.g., the Unified Parkinson's
Disease Rating Scale scores, UPDRS) according to the following
workflow (FIG. 83). We establish the correct algorithms for lead
and active contact locations and build them into the program with
the database for processing of data. These algorithms are used to
calculate important quality control information, such as mean
errors, standard deviations, overall individual with disease
complications, and the correlation between locations and UPDRS
scores. Other quality control information may be calculated or
used.
[0274] Reports
[0275] Additional reports are provided to assist in the navigation
of the modules. Report examples include (FIG. 84).
[0276] Other Examples of Implantsto be Tracked and Therapy to be
Monitored:
[0277] For the purposes of documentation of location of delivered
therapy at a given point, consider Figure (FIG. 85). Also, shown in
FIG. 86 is a data relationship between patient records on the left
(FIG.'s 76A-D) and additional surgery, visits and such on the right
via a data identifier, general history, UPDRS scores, implants and
such shown in the center. FIGS. 88A, 88B, and 88C are screen
captures from a representative database for the capturing of
perioperative trajectories and associated metrics. FIG. 89 is a
representative screen capture depicting the post implantation
location, errors, and notes associated with the procedure. FIG. 90
is a representative screen capture depicting the addition of a new
neurostimulator pulse generator device and associated linkages to
brain implants. FIG. 91 is a diagram depicting the onboard devices
envisioned within an ideal client device. FIG. 92 depicts an
individual with disease interacting with a data exchange server
environment with automated objective measure extraction and with
automated reporting. FIG. 93 depicts the simultaneous acquisition
and disbursement of data to be exchanged based upon permissions and
to separate sources. FIG. 94 depicts multiple communications along
a data exchange bus according to an aspect of the present
invention. FIG. 95 depicts navigation steps within the implant
section of the representative database for defining the location of
implants or delivered therapy. FIG. 96 is an example data exchange
mapping matrix for users to allow de-identified reporting to be
identified or identified data to be exchanged with healthcare
providers. FIG. 97 depicts synthetic data with 10 cycles of a
sinusoid having an amplitude of 10.
[0278] With rigid, semi-flexible, and flexible implants, variation
of therapeutic device location may move over time with respect to
external and internal anatomy. In the case of thin-film electrodes,
location of actual implantation is recorded for the montage and
contacts based upon automated or semi-automated interpretation of
imaging studies or magnetometer or similar data. The location of
the device at subsequent time periods is automatically replaced
within the database calculations to ensure the most accurate
systems location is used for therapy delivery calculations. For
example, a 100.times.100 contact thin-film electrode array with a
250 micron spacing grid overlying a horizontally situated cortical
sulcus may be deployed and found to be at the coronal suture of the
skull in an anteroposterior location with zero degrees of rotation
and 4 centimeters from the midline and then at the six month
imaging timeframe, be found to have moved anterior by 5 mm. The
reporting system will alert the practitioner of the abnormality and
provide a correlation of the impedance mapping heat map of the grid
before and after the suspected change as well as the longitudinal
change over time. To the extent the impedance of the montage has
stabilized over time and the relative impedance signal of the
underlying sulcus is unchanged, an alert will advise the user that
the device and brain are hypothesized to have migrated together.
Should a trend in change of impedance mapping be shifted with the
direction of the implant, an alert of the more likely fixation of
the electrode to the external anatomy of skull, dura, and scar with
underlying shift over the cortex will be given. The impedance map
will be used to report in an automated way the likely programming
alterations needed to deliver comparable stimulation to the
affected areas. Similarly in the case of recording electrode data
acquired through the montage, an alert will be given to show a
likely spatial fidelity of the recordings or a recommended
automated recalibration of the electrode signals to relevant
cortical anatomy.
[0279] In the case of fluidic delivery, thermal, radiation, or
other therapy delivered along a linear or curved intraparenchymal
trajectory, external cortical trajectory, or via an endovascular or
other fluid space delivery method, the target and entry points are
defined based upon anatomical landmarks and the implant 3D
structure is segmented to derive a resulting equation of the
implant trajectory an resulting therapy with reference to the tip
of the device or center of the target, or therapy. Metrics
associated with these findings at the time of surgery and at later
times are associated computationally to outcomes measures and an
alert results for those statistically significantly outside of the
cohort and trends between cohorts with differing techniques is
calculated.
[0280] An example of this is in the delivery of multiple collinear
fluidic infusions along a single trajectory. The novel reporting of
a technique contrary to the historically performed technique has
been reported, namely successive advancements of a catheter or
delivery system to delivery multiple payloads of fluidic delivery
versus the historic retraction technique. In the case of multiple
deliveries of therapy, the multiple deliveries of therapy are
captured and automatically segmented and added to the surgical plan
in the case of image guided surgery, real-time impedance
measurements or other metrics such as ultrasound or microelectrode
recording or impedance spectroscopy are alternatively used to
characterize the environment and progression of the implant or
delivery system through the tissue. In the case of retraction
versus further advancement, an alert is provided to indicate to the
proceduralist that the best practice advancement technique is not
being used.
[0281] Another example is in the case of multiple catheter delivery
where a similar technique is used as above, however further mapping
of impedance or imaging data is possible in association with
imaging sequences, including imaging sequences obtained along the
axis of or perpendicular to the axis of the delivery implant with
MM or other imaging modalities. An automated alert is provided if
therapy is reaching a predefined infusion border, therapy
concentration limit, outflow or loss pathway, or if an individual
with disease outcome measure threshold is reaching a limit. An
example of this would be to ensure the plan of n number of infusion
clouds in a triangular or other arrangement were being delivered
based upon the monitoring of Mill or ultrasound or another similar
technique
[0282] A further example of this technique is to deliver a shaped
infusion with real-time monitoring and closed loop delivery similar
to a 3d printer technology where along one or multiple trajectories
infusion pumps in the case of fluidic delivery are independently
controlled and hydraulic advancement mechanisms are independently
controlled. The hydraulic advancement system or other method of
advancing a rigid device such as mechanical push pull cabling,
screw rotation along a base with a fixator or other method is used
to advance the device. Recordings of impedance, impedance
spectroscopy, MRI, CT, or other imaging modalities as well as
catheter impedance, pressure, line infusion pressure, and optical
properties of transmittance and other methods of determining tissue
type, location, presence or absence of factors such as swelling,
necrosis, or other damage as well as methods of measuring tissue
concentrations of substances such as using voltage amperometry or
other methods such as microdialysis or other means of determining
tissue factors. The automated system will alter flow or delivery in
the event of changes in an individual with disease outcome, vital
signs, temperature, findings on imaging or by other means to detect
a complication such as stroke or hemorrhage or other finding. The
relative rate of advancement of the device(s) and the relative rate
of infusion are altered to provide a shaped infusion result in an
automated way based upon such factors as change in line pressure
over time, maximum line pressure, external catheter measured
pressure with single or multiple sensors, or with minimum and
maximum insertion rate, change in volume delivered over time,
volume of distribution versus infusion, change in volume of
distribution versus infusion over time, distance from relative
structures such as blood vessels, ventricular anatomy, white matter
versus gray matter tracts, other infusion or other trajectories
during the present or during previous infusions, body temperature,
line infusate temperature, molecular weight or other
characteristics of the infusate such as heparin sulfate binding or
other factor which may portend a more favorable rapid infusion
versus slower infusion for a longer period of time, infusion rate,
change in infusion rate over time, presence of catheter port
occlusion, status of catheter port occlusion mitigation strategy
algorithm implantation.
[0283] Outcomes measures and real-time assessment are used to
inform closed-loop or feedback controlled therapy such as the
controlling of an infusion pump, delivering continuous levodopa or
other medication therapy in the case of Parkinson disease. For
example, the wristwatch or other similar device or devices mounted
on one or more limbs or trunk or clothing device or shoes or hat or
head or face or backpack like device or hip or belt mounted device
will monitor for movement for detecting relevant events such as
time of waking, and state of wakefulness, movement, medication
intake via oral or other infusion, presence of medication-induced
side effects such as levodopa induced dyskinesias, presence of
paucity of medications such as resting tremor, and GPS or other
movement metrics to determine activity level and type. Combined
with known stimulation or other therapy metrics, and computation of
recommended further adjustment or therapy will be made and an alert
given to the user or to the relevant care provider. In the case of
a fluid filled delivery pump, the pump will be instructed or
instructions displayed for increasing or decreasing the level of
delivered therapy. Should other testing be indicated, an alert will
sound asking the user to perform a test or take a measurement.
Examples of such tests include weight, blood pressure, reaction
time or other physical coordination or balance test, bradykinesia
assessment such as finger tapping, or pronation supination of the
extremity, or to perform a cognitive test. These aggregate results
of background and alerted testing are provided to the data
wherehouse for reporting to stakeholders as well as for further
programming or informing alerts for programming devices. Another
example of an alert testing is to ask the user to ensure the device
is activated and to enter parameters measured with an individual
with disease controller such as battery life, impedance
measurements, neurostimulator settings, GPS location, activity
level, diary data, cognitive data, medication use data, or other
metric.
[0284] Alerts are additionally provided for the user to upload body
weight, and height as well as age, gender, and sex.
[0285] Implants communicate via wired and wireless protocols
powered by primary cell, and rechargeable technologies including
through aggregation of background energy derived from ambient
cellular and other electromagnetic transmissions. Neurostimulation
can be shaped and altered via feedback mechanisms from the
objective and subjective measures included within the aggregate
system.
[0286] Alerts are additionally provided for the user to upload body
weight, and height as well as age, gender, and sex.
[0287] Implants communicate via wired and wireless protocols
powered by primary cell, and rechargeable technologies including
through aggregation of background energy derived from ambient
cellular and other electromagnetic transmissions. Neurostimulation
can be shaped and altered via feedback mechanisms from the
objective and subjective measures included within the aggregate
system.
[0288] Content-based recognition (CBIR) is used for brain implant
error measurement using the anterior and posterior commissures,
midline point, brain width, theird ventricular width, maximum brain
length and parasagittal brain length and other measurements.
[0289] Multiple Collinear Infusion Clouds are possible to be
created with advancement rather than retraction (FIGS. 109-111;
Sillay, 2012 and 2013), however the technique of advancement rather
than retraction has not been previously described (Sillay, 2013)
and can be automated with a hydraulic or other computer controlled
advancement system (Sillay WARF IDR 2011) and could be used to
shape infusions with a single or with multiple array(s) of
catheters (SILLAY WARF IDR 2012) in order to provide computerized
feedback controlled 3D infusion shaping to a predetermined desired
infusion shape). CBIR image processing combined with microelectrode
recording as well as impedance tomography provide registration for
this computerized registration algorithm and system.
[0290] The device represented by FIG. 8 may have short range,
non-FCC controlled frequency transmission to implants and other
local devices and also have long range frequencies (FCC approval)
for communication with our medical database hierarchy. Time of day
and date can be important so that periodic measurements may be
collected into a cohort database during sleep and other typically
unmonitored times of the day (except in a hospital setting where an
individual with disease is woken every three hours to take
temperature and BP) of body temperature, blood pressure and our
device may monitor restless sleep syndrome (night tremors) and the
like. Sensors may measure and the processor software determine
asymmetric gait versus antalgic gait (see, for example, FIG.
106).
[0291] The individual with disease or the doctor may store/download
to the local device (FIG. 8) what medication treatment protocol the
individual with disease is personally using to be able to develop a
true cohort database with other similarly situated individuals
diagnosed with a disease.
[0292] All U. S. patents, published applications and articles
referenced herein should be deemed incorporated by reference herein
as to their entire contents. The claims which follow are merely
exemplary of the many claims that may be made to aspects of the
present invention. Indeed, there may be multiple inventions
disclosed in the present discussion and will be claimed in
continuation and divisional applications as deemed appropriate.
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