U.S. patent application number 11/077728 was filed with the patent office on 2005-07-21 for patient data mining for clinical trials.
Invention is credited to Best, Linda, Krishnan, Arun, Misra, Satrajit Chandra, Rao, R. Bharat.
Application Number | 20050159654 11/077728 |
Document ID | / |
Family ID | 23312212 |
Filed Date | 2005-07-21 |
United States Patent
Application |
20050159654 |
Kind Code |
A1 |
Rao, R. Bharat ; et
al. |
July 21, 2005 |
Patient data mining for clinical trials
Abstract
The present invention provides a system and method for selecting
prospective patients for a clinical trial. In various embodiments,
a clinical trials brokerage is configured to receive requests from
drug companies for lists of persons meeting specified criteria for
clinical trials. Patient records are retrieved from a structured
computerized patient record (CPR) data warehouse populated with
comprehensive patient information mined from unstructured hospital
records. A list of persons for whom consent was obtained can be
outputted and forwarded to the entity interested in performing the
clinical trial and which requested the list. Anonymity of a patient
can be maintained until the patient provides consent to participate
in the clinical trial.
Inventors: |
Rao, R. Bharat; (Berwyn,
PA) ; Misra, Satrajit Chandra; (Fremont, CA) ;
Best, Linda; (Antioch, CA) ; Krishnan, Arun;
(Exton, PA) |
Correspondence
Address: |
SIEMENS CORPORATION
INTELLECTUAL PROPERTY DEPARTMENT
170 WOOD AVENUE SOUTH
ISELIN
NJ
08830
US
|
Family ID: |
23312212 |
Appl. No.: |
11/077728 |
Filed: |
March 11, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11077728 |
Mar 11, 2005 |
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10287098 |
Nov 4, 2002 |
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60335542 |
Nov 2, 2001 |
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Current U.S.
Class: |
600/300 ; 705/3;
707/E17.005; 707/E17.058 |
Current CPC
Class: |
G16H 50/30 20180101;
G16H 10/60 20180101; G06F 16/30 20190101; G16H 40/63 20180101; G16H
10/20 20180101; G16H 50/20 20180101; G16H 70/60 20180101; G16H
40/20 20180101; Y10S 128/92 20130101; G16H 15/00 20180101; G16H
50/70 20180101; G16H 50/50 20180101; G06Q 10/10 20130101 |
Class at
Publication: |
600/300 ;
705/003 |
International
Class: |
G06F 017/60; A61B
005/00 |
Claims
What is claimed is:
1. A method for maximizing patient opportunity to participate in
clinical trials, the method comprising: (a) maintaining by a
brokerage a list of patients administered a placebo in a first
clinical trial; and (b) including by the brokerage the patients of
the list for consideration of a second clinical trial, the second
clinical trial different than the first clinical trial.
2. The method of claim 1 wherein (a) and (b) are preformed with a
machine.
3. The method of claim 1 further comprising: (c) determining with a
machine whether the patients meet criteria for the second clinical
trial.
4. The method of claim 1 further comprising: (c) retrieving patient
information with a machine from multiple, different types of data
sources; and (d) determining whether the at least one patient meets
criteria for the second clinical trial as a function of the patient
information and inclusion on the list.
5. The method of claim 1 wherein (b) comprises including where a
first drug for the first clinical trial is similar to a second drug
for the second clinical trial.
6. A system for maximizing patient opportunity to participate in
clinical trials, the system comprising: a database of a list of
patients administered a placebo in a first clinical trial; and a
machine operable to determine eligibility of the patients for a
second clinical trail as a function, at least in part, of inclusion
of the patients on the list, the second clinical trial different
than the first clinical trial.
7. The system of claim 6 wherein the machine is operable to
determine whether the patients meet criteria for the second
clinical trial.
8. The system of claim 6 wherein the machine is operable to
retrieve patient information from multiple, different types of data
sources and is operable to determine the eligibility as a function
of the patient information.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application Ser. No. 60/335,542, filed on Nov. 2, 2001, which is
incorporated by reference herein in its entirety.
FIELD OF THE INVENTION
[0002] The present invention relates to medical information
processing systems, and, more particularly to a computerized system
and method for selecting persons for clinical trials.
BACKGROUND OF THE INVENTION
[0003] Selection of persons for clinical trials is an expensive
process. It is estimated that it costs drug companies several
thousand dollars for each participant selected. Furthermore,
sometimes even after being selected, persons must be dropped from a
trial because of inaccurate or incorrect information. This may
delay the trial, causing an even greater expense.
[0004] Although drug companies try to get the word out by placing
advertisements or through direct contact with physicians, the
selection process is generally quite inefficient. Physicians tend
to be busy and do not always have time to respond to requests for
patients, and patients may not see the advertisements for clinical
trials or subscribe to the periodicals where they are placed.
[0005] Moreover, physicians at a specialized medical center tend to
refer patients to trials sponsored at that center. Many physicians
are unaware of all the available clinical trials because of the
time it takes to keep current on all available trials for every
patient that the physician sees.
[0006] In addition, clinical trials often call for very specific
selection criteria and it may be difficult to ascertain if a
particular person qualifies for a trial. Furthermore, because
hospitals typically store information in an unstructured manner, it
may be impossible using hospital records to select patients
qualifying for particular clinical trials.
[0007] An equally important problem is that of matching clinical
trials to specific patients. For example, for cancer alone, at any
point in time there are over 600 trials in progress. Statistics
show that clinical trial web sites total 75,000 hits every week,
mostly from patients seeking information about trials, who are
trying to fet added to a trial. Estimates from National Cancer
Institute indicate that only two percent of those patients eligible
for a trial are in a trial. Thus, it is critically important for an
individual to know if he or she may be eligible for a trial.
[0008] Given the importance and expense of selecting qualified
persons for clinical trials, it would be desirable and highly
advantageous to provide improved techniques for automatically
selecting prospective participants for clinical trials.
SUMMARY OF THE INVENTION
[0009] The present invention provides a technique for selecting
prospective participants in a clinical trial.
[0010] In various embodiments of the present invention, a method is
provided that includes receiving a request for a list of
prospective participants meeting specified criteria for a clinical
trial. A set of patient records is then retrieved to determine
persons meeting the specified criteria.
[0011] The specified criteria may include probability information,
thus allowing the selection of patients likely to meet the
specified criteria for the clinical study (e.g., 90% likelihood of
diabetes, 70% likelihood of hypertension). In this case, the
relevant patient records would include probabilistic information to
allow for such selection. Additional information for each
prospective participant may also be retrieved. This additional
information may include information about other clinical trials
that the person participated in, including whether a placebo was
administered.
[0012] Furthermore, persons may still be selected even though not
all information needed to determine whether a person qualifies in
all respects for a clinical trial is present.
[0013] Consent to participate in a clinical trial should be
obtained. A list of persons for whom consent was obtained can be
outputted and forwarded to an entity interested in performing the
clinical trial. Typically, this is a drug company. Physicians may
be notified of their Institutional Review Board (IRB) statuses
(e.g., `approved`, `pending`, or `not approved`. Expiration dates
of their status may be forwarded to approved physicians.
[0014] Because patient confidentiality is important, the anonymity
of a person meeting the specified criteria must be preserved. The
process of obtaining consent may include selecting physicians
associated with the persons meeting the specified criteria,
requesting approval to participate from each of the selected
physicians, and providing consent information to persons meeting
the specified criteria whose physician provided approval to
participate in the clinical trial.
[0015] To further facilitate the process, questionnaires may be
provided. These questionnaires may be used to ascertain
qualifications for the clinical trial.
[0016] Additionally, compensation and fees can be determined for
the parties involved. For example, participating physicians may be
compensated. The entity requesting the list may be charged a fee.
The patients participating in the clinical trial may also be
compensated.
[0017] The data source used to determine the persons eligible for
the clinical trial may include a data warehouse. Further, it may be
populated with structured information obtained from mining
unstructured patient records. The patient records may include
patient information obtained from a plurality of participating
health care providers, such as hospitals.
[0018] In various alternative embodiments of the present invention,
a system for selecting prospective clinical trials for an
individual patient is provided. The system includes a clinical
trials database, a data source containing patient information, and
a clinical trials brokerage for generating a list of clinical
trials for patients meeting specified criteria associated with the
clinical trials. At least some of the information in the data
source containing patient information may be obtained from mining
unstructured patient records.
[0019] These and other aspects, features and advantages of the
present invention will become apparent from the following detailed
description of preferred embodiments, which is to be read in
connection with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0020] FIG. 1 is a block diagram of a computer processing system to
which the present invention may be applied according to an
embodiment of the present invention;
[0021] FIG. 2 shows an exemplary clinical trials brokerage system
according to an embodiment of the present invention;
[0022] FIG. 3 shows an exemplary clinical trials brokerage system
according to another embodiment of the present invention; and
[0023] FIG. 4 shows a flow diagram outlining an exemplary technique
for selecting a person for a clinical trial according to an
embodiment of the present invention.
DESCRIPTION OF PREFERRED EMBODIMENTS
[0024] To facilitate a clear understanding of the present
invention, illustrative examples are provided herein which describe
certain aspects of the invention. However, it is to be appreciated
that these illustrations are not meant to limit the scope of the
invention, and are provided herein to illustrate certain concepts
associated with the invention.
[0025] It is also to be understood that the present invention may
be implemented in various forms of hardware, software, firmware,
special purpose processors, or a combination thereof. Preferably,
the present invention is implemented in software as a program
tangibly embodied on a program storage device. The program may be
uploaded to, and executed by, a machine comprising any suitable
architecture. Preferably, the machine is implemented on a computer
platform having hardware such as one or more central processing
units (CPU), a random access memory (RAM), and input/output (I/O)
interface(s). The computer platform also includes an operating
system and microinstruction code. The various processes and
functions described herein may either be part of the
microinstruction code or part of the program (or combination
thereof) which is executed via the operating system. In addition,
various other peripheral devices may be connected to the computer
platform such as an additional data storage device and a printing
device.
[0026] It is to be understood that, because some of the constituent
system components and method steps depicted in the accompanying
figures are preferably implemented in software, the actual
connections between the system components (or the process steps)
may differ depending upon the manner in which the present invention
is programmed.
[0027] FIG. 1 is a block diagram of a computer processing system
100 to which the present invention may be applied according to an
embodiment of the present invention. The system 100 includes at
least one processor (hereinafter processor) 102 operatively coupled
to other components via a system bus 104. A read-only memory (ROM)
106, a random access memory (RAM) 108, an I/O interface 110, a
network interface 112, and external storage 114 are operatively
coupled to the system bus 104. Various peripheral devices such as,
for example, a display device, a disk storage device(e.g., a
magnetic or optical disk storage device), a keyboard, and a mouse,
may be operatively coupled to the system bus 104 by the I/O
interface 110 or the network interface 112.
[0028] The computer system 100 may be a standalone system or be
linked to a network via the network interface 112. The network
interface 112 may be a hard-wired interface. However, in various
exemplary embodiments, the network interface 112 can include any
device suitable to transmit information to and from another device,
such as a universal asynchronous receiver/transmitter (UART), a
parallel digital interface, a software interface or any combination
of known or later developed software and hardware. The network
interface may be linked to various types of networks, including a
local area network (LAN), a wide area network (WAN), an intranet, a
virtual private network (VPN), and the Internet.
[0029] The external storage 114 may be implemented using a database
management system (DBMS) managed by the processor 102 and residing
on a memory such as a hard disk. However, it should be appreciated
that the external storage 114 may be implemented on one or more
additional computer systems. For example, the external storage 114
may include a data warehouse system residing on a separate computer
system.
[0030] Those skilled in the art will appreciate that other
alternative computing environments may be used without departing
from the spirit and scope of the present invention.
[0031] Referring to FIG. 2, a clinical trials brokerage 250 is
illustrated. The clinical trials brokerage 250 is shown operatively
connected to a data repository which contains patient information
typically collected from one or more health care organization, such
as hospitals. This data repository is called a structured clinical
patient record (CPR) 280. In various embodiments of the present
invention, a plurality of drug companies, such as drug company 210,
request lists of persons meeting specified criteria for clinical
trials. The structured CPR 280 is then consulted to obtain the
lists of persons meeting the specified criteria.
[0032] The specified criteria may include probability information,
thus allowing the selection of patients likely to meet the
specified criteria for the clinical study (e.g., 90% likelihood of
diabetes, 70% likelihood of hypertension). In this case, the
relevant patient records would include probabilistic
information.
[0033] Furthermore, persons may still be selected even though not
all information needed to determine whether a patient qualifies in
all respects for a clinical trial is present. In this case, the
list would include "persons of interest" some of whom might later
be excluded from participating in the clinical trial for various
reasons. Information about each person meeting the selection may
additionally be provided, including information about other
clinical trials that the person participated in and whether a
placebo was administered.
[0034] The system may keep track of a plurality of clinical trials,
and maintain a list of person who were administered a placebo
instead of the drug being tested. In many cases, a person is
disqualified from a trial if he or she participated in a trial for
a similar drug; however, if it is determined that a placebo was
administered, the system may be configured to not exclude the
person. In other cases, the system would provide information about
the trial(s) that the person participated in.
[0035] A physician, such as physician 230, may be contacted if one
of their patients meets the specified criteria for a clinical
trial. Prior to releasing information to a drug company, it is
generally necessary to obtain agreement of the patient's physician
and an informed consent of the patient to participate in the trial.
For example, the physician 230 may recommend to a patient that a
clinical trial being conducted by the drug company 210 would be
beneficial. The details of the trial may have been forwarded to the
physician 230. Furthermore, physicians may be notified of their
Institutional Review Board (IRB) statuses (e.g., `approved`,
`pending`, or `not approved`. Expiration dates of their status may
be forwarded to approved physicians.
[0036] The clinical trials brokerage 250 can be notified that the
patient provided an intent to participate. When the necessary
informed consent information is obtained, the clinical trials
brokerage 250 can provide the identity of the patient (and other
patient information) to the drug company 210.
[0037] Preferably, the structured CPR 280 is populated with patient
information using data mining techniques described in "Patient Data
Mining," by Rao et al., Attorney Docket No. 2001P20906US01,
copending U.S. patent application Ser. No. 10/287,055, filed
herewith, which is incorporated by reference herein in its
entirety.
[0038] That disclosure teaches a data mining framework for mining
high-quality structured clinical information. The data mining
framework includes a data miner that mines medical information from
a computerized patient record based on domain-specific knowledge
contained in a knowledge base. The data miner includes components
for extracting information from the computerized patient record,
combining all available evidence in a principled fashion over time,
and drawing inferences from this combination process. The mined
medical information is stored in a structured computerized patient
record.
[0039] To determine the specified criteria for the clinical study,
multiple data sources typically need to be consulted. For example,
to determine whether the patient is diabetic, the system might have
to examine the following information:
[0040] (a) ICD-9 billing codes for secondary diagnoses associated
with diabetes;
[0041] (b) drugs administered to the patient that are associated
with the treatment of diabetes (e.g., insulin);
[0042] (c) patient's lab values that are diagnostic of diabetes
(e.g., two successive blood sugar readings over 250 mg/d);
[0043] (d) doctor mentions that the patient is a diabetic in the
H&P (history & physical) or discharge note (free text);
and
[0044] (e) patient procedures (e.g., foot exam) associated with
being a diabetic.
[0045] As can be seen, there are multiple independent sources of
information, observations from which can support (with varying
degrees of certainty) that the patient is diabetic (or more
generally has some disease/condition). Not all of them may be
present, and in fact, in some cases, they may contradict each
other. Probabilistic observations can be derived, with varying
degrees of confidence. Then these observations (e.g., about the
billing codes, the drugs, the lab tests, etc.) may be
probabilistically combined to come up with a final probability of
diabetes. Note that there may be information in the patient record
that contradicts diabetes. For instance, the patient is has some
stressful episode (e.g., an operation) and his blood sugar does not
go up.
[0046] It should be appreciated that the selection of patients for
clinical trials may be based on probabilistic information. Thus, a
list of patients that meet the specified criteria may comprise a
list of patients likely (e.g., according to a particular degree of
confidence) to have met the criteria for the clinical trial.
[0047] Since it may be necessary to obtain additional information
or to verify information about a participant, the clinical trials
brokerage 250 may output, or otherwise provide, questionnaires.
These questionnaires may be used to ascertain qualifications for
the clinical trial. For example, the patient may be asked to
provide a detailed family history of particular diseases.
[0048] In addition to providing a list of persons meeting the
specified criteria, the clinical trials brokerage 250 may also
calculate various charges and fees. For example, participating
physicians may need to be compensated. The drug company may be
charged a fee for the list. Additionally, participants in the
clinical trial may also be compensated.
[0049] In various embodiments of the present invention, lists of
persons who are pre-qualified for certain types of clinical trials
may be generated. These lists of pre-qualified individuals may be
made available to drug companies or other entities interested in
conducting a clinical trial.
[0050] Referring to FIG. 3, an alternate embodiment of the present
invention is illustrated. In this embodiment, a clinical trials
brokerage 350 is able to access a structured CPR 380 containing
mined structured patient information, and also a clinical trials
database 390 containing information about various clinical trials.
The information in the clinical trials database 390 may include
information regarding the qualifications for clinical trials along
with other information regarding the trials. A patient, such as
patient 335, may request information about a particular clinical
trial. The patient may either directly access the clinical trials
brokerage 350 or go through a physician, such as physician 330. The
clinical trials brokerage 330 may access the structured CPR 380
(populated with information in the same manner as the CPR 280) to
retrieve information about the patient, and attempt to match
clinical trials of interest to the patient based on the medical
history of the patient and available trials.
[0051] Referring to FIG. 4, a flow diagram outlining an exemplary
technique for selecting a person for a clinical trial is
illustrated. Beginning at step 401, a person is selected from among
a set of persons meeting specified criteria. This step may include
receiving a request for a list of persons meeting specified
criteria for a clinical trial, and retrieving a set of patient
records from a data source to determine persons meeting the
specified criteria.
[0052] For example, a drug company might be interested in selecting
black males who are diabetic and have had a heart attack within the
last three years. This might be used to test a new drug.
[0053] Using conventional approaches, satisfying the
above-mentioned selection criteria could be difficult because
computerized hospital databases generally do not store such
information. However, by employing the data mining techniques
described in "Patient Data Mining," by Rao et al., Attorney Docket
No. 2001P20906US01, copending U.S. patent application Ser. No.
10/287,055, filed herewith, a structured CPR can be populated with
such patient information, thus allowing this selection criteria to
be satisfied.
[0054] In step 402, the person's physician can be notified that the
person has been selected for the clinical trial. At this point, a
hospital's Institutional Review Board (IRB) can also be notified.
The physician can also be notified if IRB approval has already been
granted for this trial at this site, or if he needs to wait for the
IRB approval for this trial. Next, in step 403, a determination is
made as to whether the physician will participate in the study. If
it is determined that the physician will participate, control
continues to step 404; otherwise control terminates at step
408.
[0055] In step 404, the person is notified that he or she may
qualify for the clinical trial. The patient can be directly
contacted, or, indirectly contacted through a physician. At this
point, the patient may be given detailed information about the
clinical trial. The patient may be asked for additional
information, such as through a questionnaire. The questionnaire may
be used to determine qualification for the study and/or as a way to
obtain additional useful information.
[0056] Next, in step 405, a determination is made as to whether the
person indicated a desire to participate in the clinical trial. If
the person notified his or her physician of an intent to
participate, control continues to step 406; otherwise control
terminates at step 408.
[0057] In step 406, release information is obtained. At this point
the person may be provided with a consent form or be directed to
complete one provided to him by his or her physician. Any
information regarding participant compensation, including
reimbursements, may also be provided. Control continues to step
407.
[0058] In step 407, fees and charges may be determined. For
instance, the entity requesting the list of patients may be charged
an appropriate fee for the list of patients. Furthermore, the
physician and trial participants may also be compensated for their
participation in the study. Control continues to step 408 where the
operation stops.
[0059] As shown in FIGS. 1-4, this invention is preferably
implemented using a general purpose computer system. However the
systems and methods of this invention can be implemented using any
combination of one or more programmed general purpose computers,
programmed microprocessors or microcontrollers and peripheral
integrated circuit elements, ASIC or other integrated circuits,
digital signal processors, hardwired electronic or logic circuits
such as discrete element circuits, programmable logic devices such
as a PLD, PLA, FPGA or PAL, or the like. In general, any device
capable of implementing a finite state machine that is in turn
capable of implementing the flowchart shown in FIG. 4 can be used
to implement this system.
[0060] Although illustrative embodiments of the present invention
have been described herein with reference to the accompanying
drawings, it is to be understood that the invention is not limited
to those precise embodiments, and that various other changes and
modifications may be affected therein by one skilled in the art
without departing from the scope or spirit of the invention.
* * * * *