U.S. patent application number 13/743982 was filed with the patent office on 2013-07-25 for unified healthcare intelligence, analytics, and care management.
This patent application is currently assigned to OptumInsight, Inc.. The applicant listed for this patent is OptumInsight, Inc.. Invention is credited to Daniel M. Diman, Kristy B. Drollinger, Kristen C. Edsall, Eric J. Eiden, Glen P. Eiden, M. Evan Hetu, Colleen Thilgen, John L. Wilson.
Application Number | 20130191157 13/743982 |
Document ID | / |
Family ID | 48797970 |
Filed Date | 2013-07-25 |
United States Patent
Application |
20130191157 |
Kind Code |
A1 |
Eiden; Glen P. ; et
al. |
July 25, 2013 |
UNIFIED HEALTHCARE INTELLIGENCE, ANALYTICS, AND CARE MANAGEMENT
Abstract
Healthcare intelligence and analytics may be improved by
combining sets of disparate healthcare records and matching records
between patients. The matched records may then be analyzed by
identifying relevant individuals and providing information to a
user containing the combined sets of healthcare records and the
analysis. The information may be customized for the user after
identifying the user accessing the interface. Additionally, rules
may be applied to the analyzed data to enhance the data when viewed
by the user.
Inventors: |
Eiden; Glen P.; (Forest
Lake, MN) ; Wilson; John L.; (Minneapolis, MN)
; Drollinger; Kristy B.; (Bloomington, MN) ; Hetu;
M. Evan; (Fresno, CA) ; Edsall; Kristen C.;
(Minneapolis, MN) ; Eiden; Eric J.; (Stacy,
MN) ; Thilgen; Colleen; (Oakland, CA) ; Diman;
Daniel M.; (Columbus, OH) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
OptumInsight, Inc.; |
Eden Prairie |
MN |
US |
|
|
Assignee: |
OptumInsight, Inc.
Eden Prairie
MN
|
Family ID: |
48797970 |
Appl. No.: |
13/743982 |
Filed: |
January 17, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61587514 |
Jan 17, 2012 |
|
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Current U.S.
Class: |
705/3 |
Current CPC
Class: |
G06F 19/00 20130101;
G16H 10/60 20180101 |
Class at
Publication: |
705/3 |
International
Class: |
G06F 19/00 20060101
G06F019/00; G06Q 50/24 20060101 G06Q050/24 |
Claims
1. A method of providing healthcare intelligence and analytics,
comprising: receiving a plurality of sets of healthcare data
records; matching at least one healthcare data record from each set
of the sets of healthcare data records to each of a plurality of
individuals; identifying a healthcare data record from at least one
of the sets of healthcare data records that is relevant to a target
individual; analyzing the result of associating each individual of
the plurality of individuals with at least one healthcare data
record from at least one set of healthcare data records and the
result of identifying the health care data record relevant to the
target individual; and outputting information to a user interface
display based, in part, on the analysis.
2. The method of claim 1, further comprising allowing management of
the target individual's care and wellbeing through processes and
user interfaces.
3. The method of claim 2, wherein the step of allowing management
comprises allowing viewing of clinical, financial and
administrative data for a target patient to assist in their health
care and allowing capture of additional data and activities
associated with that care.
4. The method of claim 1, further comprising applying a rule to the
analyzed data to identify data from the plurality of sets of
healthcare data records relevant to a condition of the target
individual.
5. The method of claim 4, wherein the rule is at least one of a
clinical, financial, and administrative rule.
6. The method of claim 1, wherein the step of receiving comprises
receiving at least two of a set of claims healthcare data records,
a set of clinical healthcare data records, a set of billing
healthcare data records, and a set of patient report outcomes
healthcare data records, wherein each set of healthcare data
records comprises a plurality of healthcare data records.
7. The method of claim 1, further comprising identifying a user
accessing the user interface display, wherein the information
output to the user interface display is unique for the user
accessing the user interface display.
8. The method of claim 1, wherein analyzing comprises: grouping the
plurality of individuals into separate population cohorts; and
identifying the population cohorts to which the target individual
is grouped.
9. The method of claim 1, wherein analyzing comprises attributing
clinical conditions and classifications to the target individual
using at least one of a predictive model and a clinical-based
rule.
10. The method of claim 1, wherein analyzing comprises calculating
historic costs and estimating predictive costs of treatment for the
target individual.
11. The method of claim 1, wherein analyzing comprises identifying
clinical and financial risks associated with the target
individual.
12. The method of claim 1, wherein analyzing comprises generating a
care plan for the target individual.
13. The method of claim 1, wherein analyzing comprises calculating
and displaying a confidence level for a healthcare decision made
available to the user of the user interface display, wherein the
healthcare decision is associated with the target individual.
14. The method of claim 1, further comprising receiving a query in
a domain specific language (DSL), wherein analyzing comprises
analyzing according to the query.
15. The method of claim 1, wherein outputting comprises displaying
at least one of tabular, graphical, and textual information.
16. An apparatus, comprising: a memory; and a processor coupled to
the memory, in which the processor is configured to execute the
steps comprising: receiving a plurality of sets of healthcare data
records; matching at least one healthcare data record from each set
of the sets of healthcare data records to each of a plurality of
individuals; identifying a healthcare data record from at least one
of the sets of healthcare data records that is relevant to a target
individual; analyzing the result of associating each individual of
the plurality of individuals with at least one healthcare data
record from at least one set of healthcare data records and the
result of identifying the health care data record relevant to the
target individual; and outputting information to a user interface
display based, in part, on the analysis.
17. The apparatus of claim 16, in which the processor is also
configured to execute the step of allowing management of the target
individual's care and wellbeing through processes and user
interfaces.
18. The apparatus of claim 17, in which the processor is also
configured to execute the step of allowing viewing of clinical,
financial and administrative data for a target patient to assist in
their health care and allowing capture of additional data and
activities associated with that care.
19. The apparatus of claim 16, in which the processor is also
configured to execute the step of applying a rule to the analyzed
data to identify data from the plurality of sets of healthcare data
records relevant to a condition of the target individual.
20. The apparatus of claim 19, wherein the rule is at least one of
a clinical, financial, and administrative rule.
21. The apparatus of claim 16, wherein the step of receiving
comprises receiving at least two of a set of claims healthcare data
records, a set of clinical healthcare data records, a set of
billing healthcare data records, and a set of patient report
outcomes healthcare data records, wherein each set of healthcare
data records comprises a plurality of healthcare data records.
22. The apparatus of claim 16, in which the processor is also
configured to execute the step of identifying a user accessing the
user interface display, wherein the information output to the user
interface display is unique for the user accessing the user
interface display.
23. The apparatus of claim 19, wherein analyzing comprises:
grouping the plurality of individuals into separate population
cohorts; and identifying the population cohorts to which the target
individual is grouped.
24. The apparatus of claim 19, wherein analyzing comprises
attributing clinical conditions and classifications to the target
individual using at least one of a predictive model and a
clinical-based rule.
25. The apparatus of claim 19, wherein analyzing comprises
calculating historic costs and estimating predictive costs of
treatment for the target individual.
26. The apparatus of claim 19, wherein analyzing comprises
identifying clinical and financial risks associated with the target
individual.
27. The apparatus of claim 19, wherein analyzing comprises
generating a care plan for the target individual.
28. The apparatus of claim 19, wherein analyzing comprises
calculating and displaying a confidence level for a healthcare
decision made available to the user of the user interface display,
wherein the healthcare decision is associated with the target
individual.
29. The apparatus of claim 16, in which the processor is also
configured to execute the step of receiving a query in a domain
specific language (DSL), wherein analyzing comprises analyzing
according to the query.
30. The apparatus of claim 19, wherein outputting comprises
displaying at least one of tabular, graphical, and textual
information.
31. A computer program product, comprising: a non-tangible computer
readable medium comprising code to perform the steps comprising:
receiving a plurality of sets of healthcare data records; matching
at least one healthcare data record from each set of the sets of
healthcare data records to each of a plurality of individuals;
identifying a healthcare data record from at least one of the sets
of healthcare data records that is relevant to a target individual;
analyzing the result of associating each individual of the
plurality of individuals with at least one healthcare data record
from at least one set of healthcare data records and the result of
identifying the health care data record relevant to the target
individual; and outputting information to a user interface display
based, in part, on the analysis.
32. The computer program product of claim 31, in which the medium
further comprises code to perform the step of allowing management
of the target individual's care and wellbeing through processes and
user interfaces.
33. The computer program product of claim 32, in which the medium
further comprises code to perform the step of allowing viewing of
clinical, financial and administrative data for a target patient to
assist in their health care and allowing capture of additional data
and activities associated with that care.
34. The computer program product of claim 31, in which the medium
further comprises code to perform the step of applying a rule to
the analyzed data to identify data from the plurality of sets of
healthcare data records relevant to a condition of the target
individual.
35. The computer program product of claim 34, wherein the rule is
at least one of a clinical, financial, and administrative rule.
36. The computer program product of claim 31, wherein the step of
receiving comprises receiving at least two of a set of claims
healthcare data records, a set of clinical healthcare data records,
a set of billing healthcare data records, and a set of patient
report outcomes healthcare data records, wherein each set of
healthcare data records comprises a plurality of healthcare data
records.
37. The computer program product of claim 31, in which the medium
further comprises code to perform the step of identifying a user
accessing the user interface display, wherein the information
output to the user interface display is unique for the user
accessing the user interface display.
38. The computer program product of claim 31, wherein analyzing
comprises: grouping the plurality of individuals into separate
population cohorts; and identifying the population cohorts to which
the target individual is grouped.
39. The computer program product of claim 31, wherein analyzing
comprises attributing clinical conditions and classifications to
the target individual using at least one of a predictive model and
a clinical-based rule.
40. The computer program product of claim 31, wherein analyzing
comprises calculating historic costs and estimating predictive
costs of treatment for the target individual.
41. The computer program product of claim 31, wherein analyzing
comprises identifying clinical and financial risks associated with
the target individual.
42. The computer program product of claim 31, wherein analyzing
comprises generating a care plan for the target individual.
43. The computer program product of claim 31, wherein analyzing
comprises calculating and displaying a confidence level for a
healthcare decision made available to the user of the user
interface display, wherein the healthcare decision is associated
with the target individual.
44. The computer program product of claim 31, in which the medium
further comprises code to perform the step of receiving a query in
a domain specific language (DSL), wherein analyzing comprises
analyzing according to the query.
45. The computer program product of claim 31, wherein outputting
comprises displaying at least one of tabular, graphical, and
textual information.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 61/587,514 to Glen P. Eiden, et al. entitled
"Apparatus, System, and Method for Healthcare Intelligence and
Analytics" and filed Jan. 17, 2012, which is hereby incorporated by
reference.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] This invention relates to apparatuses, systems, and methods
for healthcare intelligence and analytics, and more particularly
relates to analyzing disparate healthcare data to provide health
intelligence to healthcare team members and patients for making
better healthcare decisions and systems designed to assist in that
care management.
[0004] 2. Description of the Related Art
[0005] Decisions regarding the healthcare of an individual are
often made by a healthcare team of individuals, physicians, and
organizations. In order to make the proper decisions, a healthcare
team must rely on a variety healthcare data records, and each of
the healthcare data records may include different information. A
drawback of providing a variety of disparate healthcare data
records to the healthcare team members is that they may not be able
to interpret all the disparate data or the ability to display it in
one unified way. As a consequence, providing all the healthcare
data records directly to the healthcare team members leads to
additional administrative expenses to sift through disparate
healthcare data records and identify the healthcare data records
that each member can interpret. In some instances, the lack of
coordinated data can compromise the health and wellbeing of
patients.
[0006] Conventional patient healthcare systems attempt to solve the
problem by providing different healthcare data records to different
members of the healthcare team to aid in the decision making. For
example, a physician may often rely on only past clinical
healthcare data records about a particular patient in making
healthcare decisions for the patient. Conversely, healthcare
companies may rely on only claims healthcare data records about the
patient in providing advice to the patient. In this instance, the
health plan and the physician have different data on the patient,
which may or may not be coordinated or show the whole picture of
the patient's activities.
[0007] However, the disconnect between information relied upon and
the lack of collaboration when using a conventional patient
healthcare system results in sub-optimal healthcare for an
individual. Additionally, the healthcare decisions made with the
aid of conventional systems must be made on only partial data
because only part of the entire list of healthcare data records was
made available to each healthcare team member, which further leads
to sub-optimal healthcare.
SUMMARY OF THE INVENTION
[0008] Apparatuses, systems, and methods for analyzing and
displaying disparate healthcare data may provide health
intelligence to healthcare team members and patients, which enables
better healthcare decisions. Rather than providing separate data to
different members of a healthcare team, a single system may receive
all the disparate healthcare data records, process the disparate
healthcare data records, and present the results in a manner that
is easily interpreted and accessed by each member of a patient's
healthcare team through an interface that is accessible to each
member. Such a system allows members of a patient's healthcare team
to make fully-informed decisions based on a variety of disparate
healthcare data records, and not only a portion of the disparate
healthcare data records. The system may also provide a platform
upon which health care team members can add additional data on
activities they are providing to the patient.
[0009] Rapidly expanding use of health electronic health record
(EHR) and health information exchange (HIE) technology is unlocking
rich information on patient clinical experiences that has
traditionally been confined to paper records. In a secure
environment that protects patient privacy, applications of this
apparatus and method of this disclosure marry this data with
related health claims, patient-reported outcomes information, and
analytics capabilities, and delivers it to the point of care
through user-friendly applications. This makes it easier for care
team members and patients to access health intelligence that
supports better care decisions and patient-centered collaboration.
The solutions can also automatically gather performance metrics
essential to supporting cost-risk bearing medical organizations,
such as Accountable Care Organizations, achieving health-quality
objectives and meeting regulatory compliance reporting
requirements, which often drive compensation to providers.
[0010] The system for analyzing healthcare data disclosed here
makes meeting the complex requirements of the health system simple
for those expected to make the most important decisions about
patient care. It is tailored to the needs of end-users to make it
easier for them to access health intelligence for their patients
and communities, and to remove the administrative and technological
barriers to delivering better, more transparent and more
patient-centric health care.
[0011] In one embodiment, the system may include a Pathways
application for the enrichment of data to augment what is already
known about the patients. This application may aid in the
development of customized, multi-provider care plans for patients
based on patient's individual needs. The system may also include a
Care coordination application that provides tools that closely
track and document patient care across settings and providers, thus
enhancing visibility into diagnoses and treatments and facilitating
team-based interventions for patient care. The system may further
include a Quality application that organizes and leverages claims,
clinical and outcomes data in real-time, providing reporting and
analytics to those who need that information. The system may also
include a Population application that improves upon existing
registries or lists of people with common needs and helps health
executives and other stakeholders understand the health of entire
populations of patients.
[0012] Data accumulated and analyzed from multiple sets of
healthcare records from disparate sources may be used to identify
and deliver clinically relevant information to the stakeholders of
a member's circle of care in a highly relevant, timely, actionable
and meaningful way. Data may also displayed through relevant
reporting to assist in the administration of the financial aspects
of healthcare. This information may describe a member's array of
clinical conditions and the factors contributing to the likelihood
of poor future outcomes. This information may share gaps in care,
clinical alerts and other opportunities that can be addressed by a
physician, other providers and patients.
[0013] According to an embodiment, a method of providing healthcare
intelligence and analytics may include receiving a set of claims
healthcare data records, a set of clinical healthcare data records,
a set of billing healthcare data records, and a set of patient
report outcomes healthcare data records, wherein each set of
healthcare data records includes a plurality of healthcare data
records. The method may also include matching at least one
healthcare data record from each set of healthcare data records to
each of a plurality of individuals so that each individual of the
plurality of individuals is associated with at least one healthcare
data record from at least one set of healthcare data records. The
method may further include identifying a healthcare data record
from at least one of the sets of healthcare data records that is
relevant to a target individual. Additionally, the method may also
include analyzing the result of associating each individual of the
plurality of individuals with at least one healthcare data record
from at least one set of healthcare data records and the result of
identifying the health care data record relevant to the target
individual. The method may further include outputting information
to a user interface display based, in part, on the analysis, and
identifying a user accessing the user interface display, wherein
the information outputted to the user interface display is unique
for the user accessing the user interface display.
[0014] According to another embodiment, the method may also include
grouping the plurality of individuals into separate population
cohorts and identifying the population cohorts to which the target
individual is grouped.
[0015] In one embodiment, the method may include attributing a
clinical condition to the target individual using a predictive
model and/or clinically-based rules. In a separate embodiment, the
method may further include calculating the historical cost or
estimating the predicted cost of treatment for the target
individual.
[0016] In yet another embodiment, the method may also include
identifying a clinical and financial risk associated with the
target individual. The method may further include generating a care
plan for the target individual. According to another embodiment,
the method may include calculating and displaying a confidence
level for a healthcare decision made available to the user of the
user interface display, wherein the healthcare decision is
associated with the target individual.
[0017] The foregoing has outlined rather broadly the features and
technical advantages of the present disclosure in order that the
detailed description of the disclosure that follows may be better
understood. Additional features and advantages of the disclosure
will be described hereinafter which form the subject of the claims
of the disclosure. It should be appreciated by those skilled in the
art that the conception and specific embodiment disclosed may be
readily utilized as a basis for modifying or designing other
structures for carrying out the same purposes of the present
disclosure. It should also be realized by those skilled in the art
that such equivalent constructions do not depart from the spirit
and scope of the disclosure as set forth in the appended claims.
The novel features which are believed to be characteristic of the
disclosure, both as to its organization and method of operation,
together with further objects and advantages will be better
understood from the following description when considered in
connection with the accompanying figures. It is to be expressly
understood, however, that each of the figures is provided for the
purpose of illustration and description only and is not intended as
a definition of the limits of the present disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] The following drawings form part of the present
specification and are included to further demonstrate certain
aspects of the present invention. The invention may be better
understood by reference to one or more of these drawings in
combination with the detailed description of specific embodiments
presented herein.
[0019] FIG. 1 is a schematic block diagram illustrating one
embodiment of a system for providing health intelligence.
[0020] FIG. 2 is a schematic block diagram illustrating one
embodiment of a database system for providing health
intelligence.
[0021] FIG. 3 is a schematic block diagram illustrating one
embodiment of a computer system that may be used in accordance with
certain embodiments of the system for providing health
intelligence.
[0022] FIG. 4 is a schematic logical diagram illustrating one
embodiment of abstraction layers of operation in a system for
providing health intelligence.
[0023] FIG. 5 is a schematic block diagram illustrating one
embodiment of a distributed system for providing health
intelligence.
[0024] FIG. 6 is a schematic block diagram illustrating one
embodiment of an apparatus for providing health intelligence.
[0025] FIG. 7 is a flow chart illustrating one embodiment of a
method for providing health intelligence.
[0026] FIG. 8 is an illustration showing a result of an analysis to
generate a patient history according to one embodiment of a method
for providing health intelligence.
[0027] FIG. 9 is an illustration showing a result of an analysis to
estimate a cost of treatment according to one embodiment of a
method for providing health intelligence.
[0028] FIG. 10 is an illustration showing a result of an analysis
to create population cohorts according to one embodiment of a
method for providing health intelligence.
[0029] FIG. 11 is an illustration showing a result of an analysis
to a care plan according to one embodiment of the disclosure.
[0030] FIG. 12 is an illustration showing a system diagram
including data inputs and segmentation of functionality across the
system according to one embodiment of the disclosure.
[0031] FIG. 13 is an illustration showing a result of analysis to
create historical cost and expenditure by clinical category
according to one embodiment of the disclosure.
[0032] FIG. 14 is an illustration showing a result of displaying
multiple data sources on a geographical map according to one
embodiment of the disclosure.
DETAILED DESCRIPTION
[0033] Various features and advantageous details are explained more
fully with reference to the non-limiting embodiments that are
illustrated in the accompanying drawings and detailed in the
following description. Descriptions of well-known starting
materials, processing techniques, components, and equipment are
omitted so as not to unnecessarily obscure the invention in detail.
It should be understood, however, that the detailed description and
the specific examples, while indicating embodiments of the
invention, are given by way of illustration only, and not by way of
limitation. Various substitutions, modifications, additions, and/or
rearrangements within the spirit and/or scope of the underlying
inventive concept will become apparent to those having ordinary
skill in the art from this disclosure.
[0034] In the following description, numerous specific details are
provided, such as examples of programming, software modules,
software applications, user selections, network transactions,
database queries, database structures, hardware modules, hardware
circuits, hardware chips, etc., to provide a thorough understanding
of disclosed embodiments. One of ordinary skill in the art will
recognize, however, that embodiments of the invention may be
practiced without one or more of the specific details, or with
other methods, components, materials, and so forth. In other
instances, well-known structures, materials, or operations are not
shown or described in detail to avoid obscuring aspects of the
invention.
[0035] A program may be any predefined interaction with a target
population aimed at increasing clinical compliance, patient care or
satisfaction, and/or quality health initiatives.
[0036] A care opportunity or gap in care may be defined as a
clinical action that would typically be beneficial to a patient but
has yet been performed. An example of this would be an annual
cervical cancer screening which has yet to be performed for a
patient would be considered a gap in that patient's care. Closing a
`gap` is performed when a clinician performs a required service for
a patient that was previously not performed.
[0037] FIG. 1 illustrates one embodiment of a system 100 for
providing health intelligence. The system 100 may include a server
102, a data storage device 106, a network 108, and a user interface
device 110. In a further embodiment, the system 100 may include a
storage controller 104, or storage server configured to manage data
communications between the data storage device 106, and the server
102 or other components in communication with the network 108. In
an alternative embodiment, the storage controller 104 may be
coupled to the network 108.
[0038] In one embodiment, the system 100 may receive a set of
clinical healthcare data records, where the data may include
clinical information about an individual, such as medical
treatment. The medical treatment may be, for example,
prescriptions, instructions from a physician, physical treatments
or the like that patient receives from healthcare physicians. The
received data may also include a set of claims healthcare data
records. According to another embodiment, other healthcare data
that the system 100 may receive includes a set of billing
healthcare data records. As another example, the healthcare data
received may include a set of patient report outcomes healthcare
data records.
[0039] Each set of healthcare data records may include a plurality
of healthcare data records. The system 100 may further match at
least one healthcare data record from each set of healthcare data
records to each of a plurality of individuals. Each individual of
the plurality of individuals may be associated with at least one
healthcare data record from at least one set of healthcare data
records. Healthcare data records most relevant to a target
individual may be identified from the sets of healthcare data
records. The system 100 may analyze the results of matching
healthcare data records to individuals and identifying healthcare
data records relevant to a target individual. The information may
be output to a user interface display device 110 through the
network 108. The device 110 may display the analysis of the results
of matching healthcare data records to individuals and identifying
healthcare data records relevant to a target individual. The user
interface display device 110 may enable the user to perform
analytics, communication, and management. The user accessing the
user interface display device 110 may also be identified so that
the information output is unique for the user accessing the user
interface display device 110.
[0040] The user interface display device 110 is referred to broadly
and is intended to encompass at least a suitable processor-based
device such as a desktop computer, a laptop computer, a Personal
Digital Assistant (PDA), a mobile communication device, an
organizer device, or the like. In a further embodiment, the user
interface display device 110 may access the Internet to access a
web application or web service hosted by the server 102 and provide
a user interface for enabling a user to enter or receive
information. For example, a user may enter clinical and/or
non-clinical information about an individual, such as a patient.
When the user is a patient, the patient may also enter patient
report outcomes data, such responses to questions regarding a
particular treatment the patient received.
[0041] The system 100 may include a central store of information,
such as the storage device 104, that contains patient-centric
information that enables analytics and communications (messages,
alerts, workflow). The analytics and communications, or messaging,
may be timely and updated when new information is available and/or
only on a set schedule. The messaging may also be focused and
targeted by audience to support attention to those opportunities
with the greatest potential to improve health and outcomes.
[0042] The network 108 may facilitate communications of data
between the server 102 and the user interface device 110. The
network 108 may include any type of communications network
including, but not limited to, a wireless communication link, a
direct PC to PC connection, a local area network (LAN), a wide area
network (WAN), a modem to modem connection, the Internet, a
combination of the above, or any other communications network now
known or later developed within the networking arts which permits
two or more computers to communicate with another.
[0043] In one embodiment, the server 102 may be configured to
receive a set of claims healthcare data records, a set of clinical
healthcare data records, a set of billing healthcare data records,
and/or a set of patient report outcomes healthcare data records.
The server 102 may also be configured to match at least one
healthcare data record from each set of healthcare data records to
each of a plurality of individuals. Each individual of the
plurality of individuals may be associated with at least one
healthcare data record from at least one set of healthcare data
records. Furthermore, the server 102 may be configured to identify
a healthcare data record from at least one of the sets of
healthcare data records that is relevant to a target individual.
The server 102 may also identify the user accessing the user
interface display device 110 and enable the user to perform
analytics, communication, and management on the user interface
display device 110. The server 102 may access healthcare data
records stored in the data storage device 104 via a Storage Area
Network (SAN) connection, a LAN, a data bus, a wireless link, or
the like.
[0044] The data storage device 106 may include a hard disk,
including hard disks arranged in a Redundant Array of Independent
Disks (RAID) array, a tape storage drive comprising a magnetic tape
data storage device, an optical storage device, or the like. In one
embodiment, the data storage device 104 may store healthcare
related data, such as clinical data, insurance claims data, billing
data, patient report outcome data, or the like. The data storage
device 104 may also store non-clinical data. The data may be
arranged in a database and accessible through Structured Query
Language (SQL) queries, or other data base query languages or
operations.
[0045] The server 102 may execute applications for access data,
such as sets of healthcare data records, stored on the data storage
device 106. In one embodiment, the server 102 may execute a
pathways application, which provides a rich domain specific
language (DSL) supporting logic executing in a broad healthcare
context, an event processing engine that enables real-time
execution of point-of-care clinical decision support, and an
intuitive and context sensitive interface that allows business
users to author rules and events using natural language
construction to describe complex business processes.
[0046] The Pathways application may execute logic that takes the
previously gathered data and enhance the data available to a user
by passing it through various clinical, financial or administrative
rules. For example, when a patient is identified as having a
simple, but chronic, medical condition, the Pathways application
may identify lab data, or other administrative records, that
identify the patient as having a potentially more complex version
of that condition, thereby enhancing the user's ability to make
good clinical choices.
[0047] The Pathways application may support the execution of rules
and events against multiple forms of source data: provider EMR and
billing data, provider cost accounting data, payer claim data
sources, administrative data, and third party data sources.
Further, Pathways may integrate rules governance, versioning, and
content control with the rules and event authoring platform. The
Pathways application may be configured to deliver provider
analytics and data enrichment that supports reporting and patient
care management, to create rules and events that will support care
population and care coordination, to develop a set of business
logic using a DSL and business object model that is flexible,
reusable, to support analysis of provider EMR, lab results, and
traditional US professional, facility and pharmacy claims data
sources, to process rules execution requests in `relevant time,` to
ensure efficient execution of rules in a scalable architecture that
can be used to process large quantities of healthcare data, and to
integrate rules governance with rules authoring by linking
supporting evidence to measures, assigning review dates, and
enabling measure identification with the organization that owns the
definition (HEDIS, NQF, etc.).
[0048] The server 102 may also execute a Quality application, which
allows providers and payers to view reports across clinical and
financial dimensions based on data from all healthcare sources and
can support flexible, dimensional exploration of measures with the
ability to hone in drivers and identify actionable opportunities.
The Quality application may leverage cascading metrics that
establish clear connections between operational-, program-, and
executive-level results. The Quality application may be configured
to study performance against shared savings contracts, specifically
targeting Medicare shared savings, to understand the drivers
underneath shared savings performance (population, cost, and
quality), and to use an integration of financial and quality data
to drill deeper into performance, to discover opportunities to
increase performance and to support the development of programs to
increase quality and financial performance
[0049] The server 102 may further execute a Care coordination
application. The Care coordination application may improve
individual and population health by better informing and attributed
providers, care teams and patients about conditions, the available
treatments and provider/patient interactions, promote more
efficient and effective communication by providing information
(analytics-driven out reach, education and care messaging) in an
automated, real time manner and integrating it into the provider
and consumer workflow, lower medical costs thru timely intervention
with patients and healthier populations, establish high performance
provider networks and accountable entities by providing actionable
information on quality, cost and utilization, and align the efforts
above with value-based measurement and incentives/payments to the
providers. The Care coordination application may be implemented for
patient management, such as adding temporary patients if the
patient is not in the client environment and later make them
records, providing the ability to add, edit, and search for
patients, and adding demographics to the patient record. The Care
coordination application may be implemented for work queue
management, such as providing the ability for the care manager to
view, assign, and prioritize her/his work load, and displaying a
care manager's patient workload, alerts, activities, upcoming
appointments, and tasks to be completed, completed tasks, and
future tasks.
[0050] The Care coordination application may be implemented for
program, opportunity, and gap determination in care management,
such as assigning patients to clinical outreach programs based on
analytic and clinician input, discretely tracking patient status
within a program across points in time from an initial call, to
engagement, to closure, creating care manager opportunities, and
reassigning opportunities by the care manager or user. The Care
coordination application may also be implemented for tracking
outcomes, such as setting goals and activities for patients,
ensuring adherence and completion of activities, and viewing
activity outcomes. The Care coordination application may further be
implemented for assessing patients, such as assessing patient
status, acuity, risk, and health management status through discrete
answers to predefined questions.
[0051] The Care coordination application may further be implemented
for presenting clinical data, such as searching for medications,
adding medications to a patient record, adding a provider or a
facility to a patient record, providing searching for provides or
facilities within a patient's network, viewing loinc codes for
laboratory and clinical results, providing display imaging,
tracking patient biometric information from self-reported data and
devices in the patient's home or hospital, and setting up alerts
that are displayed when biometric data is abnormal. The Care
coordination application may also be implemented for care planning,
such as unified presentation of program, opportunity, and gaps in
care across a system within a consolidated view, editing the data,
and adding patient care notes. The quality application may further
be implemented for managing a patient registry, linking to outside
tools, reporting data, accepting program nominations from the
pathways application, tracking patient engagement, identifying
opportunities, tracking outcomes, assessing patients, and planning
care.
[0052] The Care coordination application may create enhanced data
sets that are used by the other applications to display the
content. For example, the Pathways application may identify a
patient who has a condition. In another example, the Population
application may display cohorts of patients who have that
condition. The Pathways application may identify the provider who
is most likely to be the main provider of care for the patient and
display that in many other areas of the application such as
reporting and care management. In a display from the Care
coordination application the data may display as a primary
provider. In other reports, the data may display as the provider
who is incentivized for care for that patient.
[0053] The server 102 may also execute a Population application,
which allows payers and providers to identify population cohorts
and risk across clinical and financial dimensions based on data
from all healthcare sources as well as deliver analytics (e.g.,
interactive analytics) that allows actions to be taken
automatically or manually. For example, the application may perform
categorization of a population into disease registries, and one may
perform a stratification of risk within a population. The
Population application may be configured to integrate clinical data
with claims data, to analyze specific disease risks and registries
from that combined data based on the Medicare Shared Savings ACO
measures, to provide relatively basic analytics across that data,
to allow Care coordination to assign a set of patients from
Population to a Care coordination program.
[0054] FIG. 2 illustrates one embodiment of a data management
system 200 configured to store and manage data for providing
healthcare intelligence and analytics. In one embodiment, the
system 200 may include a server 102. The server 102 may be coupled
to a data-bus 202. In one embodiment, the system 200 may also
include a first data storage device 204, a second data storage
device 206, and/or a third data storage device 208. In other
embodiments, the system 200 may include additional data storage
devices (not shown). In such an embodiment, each data storage
device 204-208 may host a separate database of a set of healthcare
data records and/or programs to execute providing healthcare
intelligence and analytics. The storage devices 204-208 may be
arranged in a RAID configuration for storing redundant copies of
the database or databases through either synchronous or
asynchronous redundancy updates.
[0055] In one embodiment, the server 102 may submit a query to
selected data storage devices 204-208 to collect a consolidated set
of data elements associated with a healthcare data records. The
server 102 may store the consolidated data set in a consolidated
data storage device 210. In such an embodiment, the server 102 may
refer back to the consolidated data storage device 210 to obtain a
set of healthcare data records associated with a specific patient
or a plurality of patients. Alternatively, the server 102 may query
each of the data storage devices 204-208 independently or in a
distributed query to obtain the set of healthcare data records
associated with a specific patient or a plurality of patients. In
another alternative embodiment, multiple databases may be stored on
a single consolidated data storage device 210.
[0056] In various embodiments, the server 102 may communicate with
the data storage devices 204-210 over the data bus 202. The data
bus 202 may comprise a SAN, a LAN, a wireless connection, or the
like. The communication infrastructure may include Ethernet,
Fibre-Chanel Arbitrated Loop (FC-AL), Small Computer System
Interface (SCSI), and/or other similar data communication schemes
associated with data storage and communication. For example, the
server 102 may communicate indirectly with the data storage devices
204-210 by first communicating with a storage server or the storage
controller 104.
[0057] In one example of the system 200, the first data storage
device 204 may store clinical healthcare data records associated
with individuals. The clinical healthcare data may include the type
of treatments or procedures being performed, and in what
distribution they are being performed. The clinical healthcare data
may also indicate who provided the treatment, such as a medical
doctor, nurse, dentist, or other healthcare professional. As
another example, the clinical healthcare data may include the types
and volumes of drugs being dispensed by pharmacists. The clinical
healthcare data corresponding to the types of procedures being
performed may include extraction, surgery, orthodontia, etc.
[0058] The second data storage device 206 may include clinical
information about the healthcare providers, such as medical
treatment. The medical treatment may be, for example,
prescriptions, instructions, physical treatments or the like that
the healthcare providers provide to patients. The third data
storage device 208 may include a set of billing healthcare data
records or a set of patient report outcomes healthcare data
records. According to one embodiment, the data stored in the data
storage devices 204-208 may also be stored in one data storage
device instead of separate data storage devices 204-208.
[0059] The server 102 may host a software application configured
for providing healthcare intelligence and analytics. The software
application may further include modules for interfacing with the
data storage devices 204-210, interfacing a network 108,
interfacing with a user, and the like. In one embodiment, the
server 102 may host an engine, application plug-in, or application
programming interface (API). In another embodiment, the server 102
may host a web service or web accessible software application.
[0060] FIG. 3 illustrates a computer system 300 according to
certain embodiments of the server 102 and/or the user interface
device 110. The central processing unit (CPU) 302 is coupled to the
system bus 304. The CPU 302 may be a general purpose CPU or
microprocessor. The present embodiments are not restricted by the
architecture of the CPU 302, so long as the CPU 302 supports the
modules, applications, and operations as described herein. The CPU
302 may execute various logical instructions according to disclosed
embodiments.
[0061] The computer system 300 may include Random Access Memory
(RAM) 308, which may be SRAM, DRAM, SDRAM, or the like. The
computer system 300 may utilize RAM 308 to store the various data
structures used by a software application configured for providing
healthcare intelligence and analytics. The computer system 300 may
also include Read Only Memory (ROM) 306 which may be PROM, EPROM,
EEPROM, optical storage, or the like. The ROM may store
configuration information for booting the computer system 300. The
RAM 308 and the ROM 306 hold user and system 100 data.
[0062] The computer system 300 may also include an input/output
(I/O) adapter 310, a communications adapter 314, a user interface
adapter 316, and a display adapter 322. The I/O adapter 310 and/or
user the interface adapter 316 may, in certain embodiments, enable
a user to interact with the computer system 300 in order to input
information such as patient outcome report data. In a further
embodiment, the display adapter 322 may display a graphical user
interface associated with a software or web-based application for
providing healthcare intelligence and analytics.
[0063] The I/O adapter 310 may connect to one or more data storage
devices 312, such as one or more of a hard drive, a Compact Disk
(CD) drive, a floppy disk drive, a tape drive, to the computer
system 300. The communications adapter 314 may be adapted to couple
the computer system 300 to the network 108, which may be one or
more of a wireless link, a LAN and/or WAN, and/or the Internet. The
user interface adapter 316 couples user input devices, such as a
keyboard 320 and a pointing device 318, to the computer system 300.
The display adapter 322 may be driven by the CPU 302 to control the
display on the display device 324.
[0064] Disclosed embodiments are not limited to the architecture of
system 300. Rather, the computer system 300 is provided as an
example of one type of computing device that may be adapted to
perform functions of a server 102 and/or the user interface device
110. For example, any suitable processor-based device may be
utilized including, without limitation, personal data assistants
(PDAs), computer game consoles, and multi-processor servers.
Moreover, the present embodiments may be implemented on application
specific integrated circuits (ASIC) or very large scale integrated
(VLSI) circuits. In fact, persons of ordinary skill in the art may
utilize any number of suitable structures capable of executing
logical operations according to the disclosed embodiments.
[0065] FIG. 4 illustrates one embodiment of a network-based system
400 for providing healthcare intelligence and analytics. In one
embodiment, the network-based system 400 includes a server 102.
Additionally, the network-based system 400 may include a user
interface device 110. In still a further embodiment, the
network-based system 400 may include one or more network-based
client applications 402 configured to be operated over a network
108 including a wireless network, an intranet, the Internet, or the
like. In still another embodiment, the network-based system 400 may
include one or more data storage devices 104.
[0066] The network-based system 400 may include components or
devices configured to operate in various network layers. For
example, the server 102 may include modules configured to work
within an application layer 404, a presentation layer 406, a data
access layer 408 and a metadata layer 410. In a further embodiment,
the server 102 may access one or more data sets 418-422 that
comprise a data layer or data tier 413. For example, a first data
set 418, a second data set 420, and a third data set 422 may
comprise a data tier 413 that is stored on one or more data storage
devices 204-208.
[0067] One or more web applications 412 may operate in the
application layer 404. For example, a user may interact with the
web application 412 though one or more I/O interfaces 318, 320
configured to interface with the web application 412 through an I/O
adapter 310 that operates on the application layer. In one
embodiment, a web application 412 may be provided for providing
healthcare intelligence and analytics that includes software
modules configured to perform the steps of receiving a plurality of
disparate healthcare data records, matching healthcare data records
to individuals, identifying healthcare data records relevant to a
target individual, analyzing the results of matching healthcare
data records to individuals and identifying healthcare data records
relevant to a target individual, outputting information to a user
interface display device based, in part, on the analysis, and
identifying a user accessing the user interface display device.
[0068] In a further embodiment, the server 102 may include
components, devices, hardware modules, or software modules
configured to operate in the presentation layer 406 to support one
or more web services 414. For example, a web application 412 may
access or provide access to a web service 414 to perform one or
more web-based functions for the web application 412. In one
embodiment, web application 412 may operate on a first server 102
and access one or more web services 414 hosted on a second server
(not shown) during operation.
[0069] For example, a web application 412 for providing healthcare
intelligence and analytics may access a first web service 414 to
receive a set of claims healthcare data records, a set of clinical
healthcare data records, a set of billing healthcare data records,
and a set of patient report outcomes healthcare data records,
wherein each set of healthcare data records may include a plurality
of healthcare data records. A second web service 414 may be
accessed to match at least one healthcare data record from each set
of healthcare data records to each of a plurality of individuals so
that each individual of the plurality of individuals is associated
with at least one healthcare data record from at least one set of
healthcare data records, and to identify a healthcare data record
from at least one of the sets of healthcare data records that is
relevant to a target individual. In another embodiment, separate
web services may be used to analyze the results of matching
healthcare data records to individuals and identifying healthcare
data records relevant to a target individual, to output information
to a user interface display based, in part, on the analysis, and to
identify a user accessing the user interface display. One of
ordinary skill in the art will recognize various web-based
architectures employing web services 414 for modular operation of a
web application 412.
[0070] In one embodiment, a web application 412 or a web service
414 may access one or more of the data sets 418-422 through the
data access layer 408. In certain embodiments, the data access
layer 408 may be divided into one or more independent data access
layers 416 for accessing individual data sets 418-422 in the data
tier 413. These individual data access layers 416 may be referred
to as data sockets or adapters. The data access layers 416 may
utilize metadata from the metadata layer 410 to provide the web
application 412 or the web service 414 with specific access to the
data set 412. For example, the data access layer 416 may include
operations for performing a query of the data sets 418-422 to
retrieve specific information for the web application 412 or the
web service 414.
[0071] For example, the data access layer 416 may include
operations for performing a query of the data sets 418-422 to
retrieve specific information for the web application 412 or the
web service 414. In a more specific example, the data access layer
416 may include a query for healthcare data records that may
include claims, clinical, billing, and patient outcome report
data.
[0072] FIG. 5 illustrates a further embodiment of a system 500 for
providing healthcare intelligence and analytics. In one embodiment,
the system 500 may include a service provider site 502 and a client
site 504. The service provider site 502 and the client site 504 may
be separated by a geographic separation 506.
[0073] In one embodiment, the system 500 may include one or more
servers 102 configured to host a software application 412 for
providing healthcare intelligence and analytics, or one or more web
services 414 for performing certain functions associated with
providing healthcare intelligence and analytics. The system may
further comprise a user interface server 508 configured to host an
application or web page configured to allow a user to interact with
the web application 412 or web services 414 for providing
healthcare intelligence and analytics. In such an embodiment, a
service provider may provide hardware 102 and services 414 or
applications 412 for use by a client without directly interacting
with the client's customers.
[0074] FIG. 6 illustrates one embodiment of an apparatus 600 for
providing healthcare intelligence and analytics. In one embodiment,
the apparatus 600 is a server 102 configured to load and operate
software modules 602-610 configured for providing healthcare
intelligence and analytics. Alternatively, the apparatus 600 may
include hardware modules 602-610 configured with analog or digital
logic, firmware executing FPGAs, or the like configured to receive
a plurality of disparate healthcare data records, match healthcare
data records to individuals, identify healthcare data records
relevant to a target individual, analyze the results of matching
healthcare data records to individuals and identifying healthcare
data records relevant to a target individual, output information to
a user interface display device based, in part, on the analysis,
and identify a user accessing the user interface display device. In
such embodiments, the apparatus 600 may include a processor 302 and
an interface 602, such as an I/O adapter 310, a communications
adapter 314, a user interface adapter 316, or the like.
[0075] In one embodiment, the processor 302 may include one or more
software defined modules configured to receive a plurality of
disparate healthcare data records, match healthcare data records to
individuals, identify healthcare data records relevant to a target
individual, analyze the results of matching healthcare data records
to individuals and identifying healthcare data records relevant to
a target individual, output information to a user interface display
device based, in part, on the analysis, and identify a user
accessing the user interface display device. In one embodiment,
these modules may include an interface module 602 to provide a user
with access to the apparatus 600, as well as to output information
and identify a user accessing the interface module 602. Other
modules may include a receive module 604 to receive a plurality of
disparate healthcare data records, a match module 606 to match
healthcare data records to individuals, an identify module 608 to
identify healthcare data records relevant to a target individual,
and an analyze module 610 to analyze the results of matching
healthcare data records to individuals and identifying healthcare
data records relevant to a target individual.
[0076] The sets of healthcare data records received by receive
module 604 according to an embodiment of the present disclosure may
include claims, clinical, billing, or patient outcome report data.
A set of healthcare data records may include clinical information.
As one example, healthcare data records may, in certain
embodiments, include clinical information about individuals, such
as medical treatment. The medical treatment may be, e.g.,
prescriptions, instructions, physical treatments or the like that
patients receive from healthcare physicians.
[0077] Although the various functions of the server 102 and the
processor 302 are described in the context of modules, the methods,
processes, and software described herein are not limited to a
modular structure. Rather, some or all of the functions described
in relation to the modules of FIG. 6 may be implemented in various
formats including, but not limited to, a single set of integrated
instructions, commands, code, queries, etc. In one embodiment, the
functions may be implemented in database query instructions,
including SQL, PLSQL, or the like. Alternatively, the functions may
be implemented in software coded in C, C++, C#, php, Java, or the
like. In still another embodiment, the functions may be implemented
in web based instructions, including HTML, XML, etc.
[0078] Generally, the interface module 602 may provide a user with
access to the apparatus 600, as well as to output information and
identify a user accessing the interface module 602. For example,
the interface module 602 may display information related a target
patient and allow the user to provide input to manipulate the
information displayed via the interface module 602. In a further
embodiment, the interface module 602 may display healthcare
intelligence and analytics, and allow the user to communicate with
other members of an individual's healthcare team or manage the
individual's healthcare. For example, healthcare intelligence
outputted via the interface module as a result of the analysis
performed on the results of matching healthcare data records to
individuals and identifying healthcare data records relevant to a
target individual may include statistics, tables, charts, graphs,
recommendations, and the like.
[0079] Structurally, the interface module 602 may include one or
more of an I/O adapter 310, a communications adapter 314, a user
interface adapter 316, and/or a display adapter 322. The interface
module 602 may further include I/O ports, pins, pads, wires,
busses, and the like for facilitating communications between the
processor 302 and the various adapters and interface components
310-324. The interface module may also include software defined
components for interfacing with other software modules on the
processor 302.
[0080] In one embodiment, the processor 302 may load and execute
software modules configured to receive a plurality of disparate
healthcare data records, match healthcare data records to
individuals, identify healthcare data records relevant to a target
individual, analyze the results of matching healthcare data records
to individuals and identifying healthcare data records relevant to
a target individual, output information to a user interface display
device based, in part, on the analysis, and identify a user
accessing the user interface display device for providing
healthcare intelligence and analytics. These software modules may
include a receive module 604 to receive a plurality of disparate
sets of healthcare data records, a match module 606 to match
healthcare data records to individuals, an identify module 608 to
identify healthcare data records relevant to a target individual,
and an analyze module 610 to analyze the results of matching
healthcare data records to individuals and identifying healthcare
data records relevant to a target individual. In one embodiment,
the interface module 602 may be used to output information based,
in part, on the analysis of the results of matching healthcare data
records to individuals and identifying healthcare data records
relevant to a target individual, and to identify a user accessing
the user interface display device.
[0081] In a specific embodiment, the processor 302 may load and
execute computer software configured to receive a set of claims
healthcare data records, a set of clinical healthcare data records,
a set of billing healthcare data records, and a set of patient
report outcomes healthcare data records. For example, the receive
module 604 may receive, from a plurality of healthcare data
sources, the set of claims healthcare data records, the set of
clinical healthcare data records, the set of billing healthcare
data records, and the set of patient report outcomes healthcare
data records. The set of clinical healthcare data records may
include, for example, the type of procedures or medical treatments
being performed on individuals or it may include the types and
volumes of drugs being dispensed by pharmacists to the individual.
The medical treatment may be, e.g., prescriptions, instructions,
physical treatments or the like that the healthcare providers
provide to patients. The set of claims healthcare data records may
include, for example, dates of medical services, payment amounts
for services, procedure and diagnostic codes, and/or various
identification numbers for patient, provider and facility. The set
of billing healthcare data records may include, for example,
information about the encounter with the provider, such as place of
service, billing amounts, and/or payment amounts for those
services. The set of patient reported outcomes healthcare data
records may include, for example, pre- and post-service quality of
life, range of motion for joint issues, and/or general health
perceptions from the patient's viewpoint.
[0082] The match module 606 may, in one embodiment, be configured
to match at least one healthcare data record from each set of
healthcare data records to each of a plurality of individuals so
that each individual of the plurality of individuals is associated
with at least one healthcare data record from at least one set of
healthcare data records. According to yet another embodiment, the
identify module 608 may be configured to identify a healthcare data
record from at least one of the sets of healthcare data records
that is relevant to a target individual.
[0083] The analyze module 610 may, according to an embodiment,
analyze the result of associating each individual of the plurality
of individuals with at least one healthcare data record from at
least one set of healthcare data records and the result of
identifying the health care data record relevant to the target
individual. For example, as shown in FIG. 8, analyzing may result
in the generation of a complete patient history. In one embodiment,
the analyze module 610 may include grouping the plurality of
individuals into separate population cohorts and identifying the
population cohorts to which the target individual is grouped, as
shown in FIG. 10. In another embodiment, the analyze module 610 may
include attributing a clinical condition to the target individual
using a predictive model, while in another embodiment, the analyze
module 610 may include estimating a cost of treatment for the
target individual, as shown in FIG. 9. According to one embodiment,
the analyze module 610 may further include identifying a clinical
and financial risk associated with the target individual or
generating a care plan for the target individual. In yet another
embodiment, the analyze module 610 may include calculating and
displaying a confidence level for a healthcare decision made
available to the user of the user interface display, wherein the
healthcare decision is associated with the target individual.
[0084] FIG. 7 illustrates one embodiment of a method 700 for
providing health intelligence. In one embodiment, the method 700
starts at block 702 with receiving multiple sets of healthcare data
records. In one embodiment, the multiple sets of healthcare data
records may include claims, clinical, admin, billing, patient
reported outcome healthcare data records, and/or other data records
for a plurality of individuals. FIG. 12 is an illustration showing
a system diagram including data inputs and segmentation of
functionality across the system according to one embodiment of the
disclosure.
[0085] At block 704, the method 700 may include matching at least
one healthcare data record from each set of healthcare data records
to each of a plurality of individuals. Each individual of the
plurality of individuals may be associated with at least one
healthcare data record from at least one set of healthcare data
records.
[0086] The method 700 may further include, at block 706,
identifying a healthcare data record from at least one of the sets
of healthcare data records that is relevant to a target individual.
In one embodiment, the method 700 may further include, at block
708, analyzing the result of associating each individual of the
plurality of individuals with at least one healthcare data record
and the result of identifying the health care data record relevant
to the target individual.
[0087] For example, as shown in FIG. 8, analyzing may result in the
generation of a complete patient history. The complete patient
history may include personal information such as date of birth,
gender, preferred language, a calculated risk score, a payer, an
attributed provider, and an appointment schedule. The complete
patient history may also include a list of problems and whether the
problems were resolved, a list of prescribed medications and
filling dates, and vital signs and other clinical information such
as weight, height, and blood pressure measurements. The analysis
performed to obtain the patient summary displayed in FIG. 8 is made
possible by receiving data records from multiple sources and
matching records between the sources. For example, the problem list
may be assembled from patient diagnosis, the medication list from
patient records, and the information regarding when the
prescriptions was refilled from billing information.
[0088] In one embodiment, analyzing may include grouping the
plurality of individuals into separate population cohorts and
identifying the population cohorts to which the target individual
is grouped, as shown in FIG. 10. Grouping on a patient dashboard
may be accomplished by applying filters, such as a provider filter,
a reason for contact filter, and/or a status filter. The list of
patients matching the applied filters may include data regarding
and/or be sorted by patient, provider, reason for contact, status,
details, and/or contact priority. In one embodiment, the display
may illustrate care coordination measures including CHF admissions,
readmissions, COPD admissions, and medication reconciliation.
[0089] In one embodiment, analyzing may include grouping the
plurality of individuals into reporting categories such as
location. For example, a graphical display, such as a geographical
map separated into geographical regions, may illustrate data
obtained from multiple sources, as shown in FIG. 14.
[0090] In another embodiment, analyzing may include attributing a
clinical condition to the target individual using a predictive
model, while in another embodiment, analyzing may include
estimating a cost of treatment for the target individual, as shown
in FIGS. 9 and 13. For example, an encounter history of FIG. 9 may
include recent visits to medical providers, clinical values from
those visits, and calculated costs. The information may be
compiled, for example, from clinical health care records and
billing health care records. The information may also be computed
for a particular provider. For example, FIG. 13 illustrates
performance of a provider with respect to particular patients. That
is, outcomes and costs for treating particular patients by a
particular provider may be graphically illustrated, as shown in
FIG. 13. The patients for a provider may be filtered by, for
example, preventative care, care coordination, diabetes management,
and/or patient experience. Results for the provider in treating a
group of patients matching the filter may include calculating an
average risk score, calculating a P4P performance forecast, and/or
calculating outcomes for the patients compared to system averages.
For example, the display of FIG. 13 may report the number of the
provider's patients matching the filter criteria having a blood
pressure greater than 140/90 compared to a system average.
[0091] In another embodiment, analyzing may include defining a
patient care plan for the target individual using the
classifications and categories defined by the Pathways application,
allowing clinical staff to define new care plans based on
historical information, as shown in FIG. 11. A clinical staff
member may draw a pathway of care for an individual to include
steps of care, such as obtaining prescriptions, obtaining vaccines,
receiving educational materials, scheduling follow-up calls, and/or
scheduling follow-up appointments. The pathway may be drawn by
dragging and dropping available boxes into the flow of the pathway.
The display may identify specific opportunities and actions
available for a particular patient by analyzing data from multiple
sources. For example, when drawing a care pathway for a patient
with asthma or a patient at risk for asthma, a "medication
education" box may appear in a list of opportunities to add to the
care pathway.
[0092] According to one embodiment, analyzing may further include
identifying a clinical and financial risk associated with the
target individual or generating a care plan for the target
individual. In yet another embodiment, analyzing may include
calculating and displaying a confidence level for a healthcare
decision made available to the user of the user interface display,
wherein the healthcare decision is associated with the target
individual.
[0093] Referring back to FIG. 7, the method 700 may further
include, at block 710, outputting information to a user interface
display based, in part, on the analysis, and identifying a user
accessing the user interface display.
[0094] All of the methods disclosed and claimed herein can be made
and executed without undue experimentation in light of the present
disclosure. While the apparatus and methods of this invention have
been described in terms of preferred embodiments, it will be
apparent to those of skill in the art that variations may be
applied to the methods and in the steps or in the sequence of steps
of the method described herein without departing from the concept,
spirit and scope of the invention. In addition, modifications may
be made to the disclosed apparatus, and components may be
eliminated or substituted for the components described herein where
the same or similar results would be achieved. All such similar
substitutes and modifications apparent to those skilled in the art
are deemed to be within the spirit, scope, and concept of the
invention as defined by the appended claims.
[0095] Although the present disclosure and its advantages have been
described in detail, it should be understood that various changes,
substitutions and alterations can be made herein without departing
from the spirit and scope of the disclosure as defined by the
appended claims. Moreover, the scope of the present application is
not intended to be limited to the particular embodiments of the
process, machine, manufacture, composition of matter, means,
methods and steps described in the specification. As one of
ordinary skill in the art will readily appreciate from the present
processes, disclosure, machines, manufacture, compositions of
matter, means, methods, or steps, presently existing or later to be
developed that perform substantially the same function or achieve
substantially the same result as the corresponding embodiments
described herein may be utilized according to the present
disclosure. Accordingly, the appended claims are intended to
include within their scope such processes, machines, manufacture,
compositions of matter, means, methods, or steps.
* * * * *