U.S. patent application number 13/925212 was filed with the patent office on 2013-12-26 for systems and methods for analytics on viable patient populations.
This patent application is currently assigned to Quintiles Transnational Corporation. The applicant listed for this patent is Wade Kenneth Brant, Joseph William Charles Goodgame, Gavin David Thomas Nichols. Invention is credited to Wade Kenneth Brant, Joseph William Charles Goodgame, Gavin David Thomas Nichols.
Application Number | 20130346093 13/925212 |
Document ID | / |
Family ID | 49774051 |
Filed Date | 2013-12-26 |
United States Patent
Application |
20130346093 |
Kind Code |
A1 |
Goodgame; Joseph William Charles ;
et al. |
December 26, 2013 |
Systems and Methods for Analytics on Viable Patient Populations
Abstract
Systems and methods for analytics on viable patient populations
are disclosed. One disclosed method includes displaying a user
interface control associated with a patient criteria, receiving a
selection of a patient criteria through the user interface control,
the patient criteria associated with a characteristic of a patient
population, retrieving a subset of patient population source data
from a patient population data source, the subset of patient
population source data based at least in part on the selected
patent criteria, and displaying a graphical representation of a
patient population based on the retrieved subset of the patient
population source data.
Inventors: |
Goodgame; Joseph William
Charles; (Zionsville, IN) ; Nichols; Gavin David
Thomas; (Raleigh, NC) ; Brant; Wade Kenneth;
(Greenwood, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Goodgame; Joseph William Charles
Nichols; Gavin David Thomas
Brant; Wade Kenneth |
Zionsville
Raleigh
Greenwood |
IN
NC
IN |
US
US
US |
|
|
Assignee: |
Quintiles Transnational
Corporation
Durham
NC
|
Family ID: |
49774051 |
Appl. No.: |
13/925212 |
Filed: |
June 24, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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61663219 |
Jun 22, 2012 |
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61663292 |
Jun 22, 2012 |
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61663057 |
Jun 22, 2012 |
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61663299 |
Jun 22, 2012 |
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61663398 |
Jun 22, 2012 |
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61663357 |
Jun 22, 2012 |
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61663216 |
Jun 22, 2012 |
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Current U.S.
Class: |
705/2 |
Current CPC
Class: |
G06T 11/206 20130101;
G06F 40/166 20200101; G06F 16/211 20190101; G06F 16/248 20190101;
G16H 10/20 20180101; G06F 16/345 20190101; G06F 17/10 20130101;
G06F 3/0484 20130101; G16H 40/63 20180101; G16H 10/60 20180101 |
Class at
Publication: |
705/2 |
International
Class: |
G06F 19/00 20060101
G06F019/00 |
Claims
1. A method comprising: displaying a user interface control
associated with a patient criteria; receiving a selection of a
patient criteria through the user interface control, the patient
criteria associated with a characteristic of a patient population;
retrieving a subset of patient population source data from a
patient population data source, the subset of patient population
source data based at least in part on the selected patent criteria;
and displaying a graphical representation of a patient population
based on the retrieved subset of the patient population source
data.
2. The method of claim 1, further comprises receiving a selection
of patient population source data, and wherein displaying the user
interface control is based on the selected patient population
source data.
3. The method of claim 2, further comprising receiving a
modification of the selected patient population source data.
4. The method of claim 1, further comprising displaying a window,
wherein the user interface control is user positionable in the
window.
5. The method of claim 1, wherein retrieving the subset of patient
population source data based at least in part on the selected
patient criteria further comprises: generating a query based at
least in part on the selected patient criteria; and executing the
query on a database comprising the patient population source
data.
6. The method of claim 1, wherein displaying a graphical
representation of a patient population based on the retrieved
subset of the patient population source data comprises displaying a
Venn bar diagram.
7. The method of claim 1, further comprising receiving a
modification of the selected patient criteria.
8. A computer readable medium comprising software program code
executable by a processor to: display a user interface control
associated with a patient criteria; receive a selection of a
patient criteria through the user interface control, the patient
criteria associated with a characteristic of a patient population;
retrieve a subset of patient population source data from a patient
population data source, the subset of patient population source
data based at least in part on the selected patent criteria; and
display a graphical representation of a patient population based on
the retrieved subset of the patient population source data.
9. The computer readable medium of claim 8, further comprising
software program code executable by a processor to receive a
selection of patient population source data, and wherein displaying
the user interface control is based on the selected patient
population source data.
10. The computer readable medium of claim 9, further comprising
software program code executable by a processor to receive a
modification of the selected patient population source data.
11. The computer readable medium of claim 8, further comprising
software program code executable by a processor to display a
window, wherein the user interface control is user positionable in
the window.
12. The computer readable medium of claim 8, wherein retrieving the
subset of patient population source data based at least in part on
the selected patient criteria comprises: generating a query based
at least in part on the selected patient criteria; and executing
the query on a database comprising the patient population source
data.
13. The computer readable medium of claim 8, wherein displaying a
graphical representation of a patient population based on the
retrieved subset of the patient population source data comprises
displaying a Venn bar diagram.
14. The computer readable medium of claim 8, further comprising
software program code executable by a processor to receive a
modification of the selected patient criteria.
15. A system comprising: a processor; and a memory in communication
with the processor, the memory comprising computer program code
executable by the processor to: display a user interface control
associated with a patient criteria; receive a selection of a
patient criteria through the user interface control, the patient
criteria associated with a characteristic of a patient population;
retrieve a subset of patient population source data from a patient
population data source, the subset of patient population source
data based at least in part on the selected patent criteria; and
display a graphical representation of a patient population based on
the retrieved subset of the patient population source data.
16. The system of claim 15, the memory further comprising software
program code executable by the processor to receive a selection of
patient population source data, and wherein displaying the user
interface control is based on the selected patient population
source data.
17. The system of claim 16, the memory further comprising software
program code executable by the processor to receive a modification
of the selected patient population source data.
18. The system of claim 15, the memory further comprising software
program code executable by the processor to display a window,
wherein the user interface control is user positionable in the
window.
19. The system of claim 15, wherein retrieving the subset of
patient population source data based at least in part on the
selected patient criteria comprises: generating a query based at
least in part on the selected patient criteria; and executing the
query on a database comprising the patient population source
data.
20. The system of claim 15, displaying a graphical representation
of a patient population based on the retrieved subset of the
patient population source data comprises displaying a Venn bar
diagram
21. The system of claim 15, the memory further comprising software
program code executable by the processor to receive a modification
of the selected patient criteria.
Description
REFERENCE TO RELATED APPLICATION
[0001] This application claims priority to U.S. Provisional
Application No. 61/663,219, filed Jun. 22, 2012, entitled "Systems
and Methods for Analytics on Viable Patient Populations;" U.S.
Provisional Application No. 61/663,292, filed on Jun. 22, 2012,
entitled "Method and System to Manipulate Multiple Selections
against a Population of Elements;" U.S. Provisional Application No.
61/663,057, filed on Jun. 22, 2012, entitled "Systems and Methods
For Predictive Analytics For Site Initiation and Patient
Enrollment;" U.S. Provisional Application No. 61/663,299, filed on
Jun. 22, 2012, entitled "Methods and Systems for Predictive
Clinical Planning and Design and Integrated Execution Services;"
U.S. Provisional Application No. 61/663,398, filed on Jun. 22,
2012, entitled "Systems and Methods for Subject Identification (ID)
Modeling;" U.S. Provisional Application No. 61/663,357, filed Jun.
22, 2012; entitled "Methods and Systems for a Clinical Trial
Development Platform;" U.S. Provisional Application No. 61/663,216,
filed Jun. 22, 2012; entitled "Systems and Methods for Data
Visualization." The entirety of all of which is hereby incorporated
by reference herein.
FIELD OF THE INVENTION
[0002] The present invention relates generally to systems and
methods for the creation and analysis of clinical trials. The
present invention relates more specifically to systems and methods
for analytics on viable patient populations.
BACKGROUND
[0003] Clinical trials for molecules that may become pharmaceutical
products are complex endeavors that often last for years. Because
of this, clinical trials are quite expensive and require careful
planning to maximize return on investment. One critical aspect of
planning is determining optimal inclusion and exclusion criteria
for forming a patient population for the clinical trial.
[0004] Existing tools and methods for analyzing and determining
optimal patient population criteria suffer from a number of
deficiencies. First, current methods of patient analysis are driven
by a single question/single answer paradigm. In addition, once a
particular query is formed and submitted, results can take anywhere
from thirty minutes to hours or days to arrive. Furthermore,
current methods provide text-based analysis of data, but do not
provide a simple visual way of representing patient populations.
Because of these limitations, clinical trial planners are unable to
create "what if" scenarios and quickly receive the results of a
"what if" scenario in an easily readable visual form. Therefore,
existing methods and systems for analyzing patient populations
require a substantial amount of time for trial designers to fine
tune the criteria for a population such that they are not overly
inclusive or exclusive.
SUMMARY
[0005] Embodiments of the present invention provide systems and
methods for Analytics Viable Patient Populations. In one
embodiment, a three-tier system provides a client application to
view and modify criteria related to patient populations, a query
building engine for dynamically forming queries based on the
criteria supplied by the user, and one or more databases for
storing medical records, prescription records, clinical trial data,
medical claim information, and other patient information analyzed
based on exclusion/inclusion criteria provided by a user. The
application in such an embodiment receives the user's criteria
selections, dynamically builds complex queries, submits the queries
to the one or more databases, and displays the results from the
queries in a simple graphical form. The application is able to
provide the user with the impact of the user's selections on the
patient population in an easy-to-read graphical format. Based on
the results, the user may determine whether the criteria are too
inclusive/exclusive and adjust the criteria. This process may be
performed iteratively until the criteria producing an optimal
patient population are determined.
[0006] In one embodiment, the user is also provided with a query
builder interface--an alternative interface through which a user
may visually build and submit complex queries applying
inclusion/exclusion criteria to form a prospective patient
population. Once again, the application is able to provide the user
with the impact of the user's queries on the patient population in
an easy-to-read graphical format. Based on the results, the user
may determine whether the criteria are too inclusive/exclusive and
adjust the criteria. This process may be performed iteratively
until the criteria producing an optimal patient population are
determined.
[0007] This embodiment is mentioned not to limit or define the
invention, but to provide an example of an embodiment of the
invention to aid understanding thereof. Embodiments are discussed
in the Detailed Description, and further description of the
invention is provided there. Advantages offered by the various
embodiments of the present invention may be further understood by
examining this specification.
BRIEF DESCRIPTION OF THE FIGURES
[0008] These and other features, aspects, and advantages of the
present invention are better understood when the following Detailed
Description is read with reference to the accompanying drawings,
wherein:
[0009] FIG. 1 is a block diagram illustrating an exemplary
environment for implementation of one embodiment of the present
invention;
[0010] FIG. 2 is a screen shot of a patient population editor view
according to one embodiment of the present invention;
[0011] FIG. 3 is a flowchart illustrating a method for performing
patient population analysis and manipulation according to one
embodiment of the present invention;
[0012] FIG. 4 is screen shot of a patient population query editor
view according to one embodiment of the present invention;
[0013] FIG. 5 is a is a screenshot of an interface for manipulating
a patient population criteria element according to one embodiment
of the present invention;
[0014] FIG. 6 is a screen shot of a patient population query editor
view according to one embodiment of the present invention;
[0015] FIG. 7 is a flowchart illustrating one method for performing
patient population analysis and manipulation according to one
embodiment of the present invention;
[0016] FIG. 8 screen shot of a patient population query editor view
according to one embodiment of the present invention; and
[0017] FIG. 9 is a screen shot of a patient population query editor
view according to one embodiment of the present invention.
DETAILED DESCRIPTION
[0018] Embodiments of the present invention provide systems and
methods for analytics on viable patient populations.
Illustrative Embodiment of the Present Invention
[0019] One illustrative embodiment of the present invention
comprises an application for selecting patient population source
data and utilizing adjustable criteria to include or exclude
patient segments to create a patient population for a clinical
trial. The embodiment allows a user to access an application that
presents a variety of patient-related adjustable criteria for
manipulating the patient population source data to create a
prospective patient population. These parameters may include, for
example, the gender, age, ethnicity, height, weight, body mass
index, lab results, and more.
[0020] Once the user has set the parameters, the user is presented
with a graphical representation of the patient population that
allows the user to determine whether the selected criteria were
overly exclusive or inclusive. For example, the graphical display
may include a line chart showing a breakdown of age and gender
across the resulting patient population, a pie chart demonstrating
a breakdown of ethnicity for the prospective patient population, a
thermometer showing the overall amount of patients remaining after
the criteria are applied, and/or a Venn Bar diagram showing
overlaps between populations to help the user understand the
individual impact of each selected criteria on the prospective
patient population.
[0021] The process is iterative; the user is able to change the
selected criteria to determine the most appropriate criteria for
forming an optimal patient population for a given clinical
trial.
[0022] This illustrative embodiment neither limits nor defines the
invention. Rather, the illustrative embodiment is meant to provide
an example of how the present invention may be implemented.
Illustrative Environment
[0023] Referring now to the drawings, in which like numerals
indicate like elements throughout the several figures, FIG. 1 is a
block diagram illustrating an exemplary environment for
implementation of one embodiment of the present invention. The
embodiment shown in FIG. 1 includes a client 100 that allows a user
to interface with an application server 200, web server 300, and/or
database 400 via a network 500.
[0024] The client 100 may be, for example, a personal computer
(PC), such as a laptop or desktop computer, which includes a
processor and a computer-readable media. The client 100 also
includes user input devices, such as a keyboard and mouse or touch
screen, and one or more output devices, such as a display. In some
embodiments of the invention, the user of client 100 accesses an
application or applications specific to one embodiment of the
invention. In other embodiments, the user accesses a standard
application, such as a web browser on client 100, to access
applications running on a server such as application server 200,
web server 300, or database 400. For example, in one embodiment, in
the memory of client 100 are stored applications including a design
studio application for planning and designing clinical trials. The
client 100 may also be referred to as a terminal in some
embodiments of the present invention.
[0025] Such applications may be resident in any suitable
computer-readable medium and executable on any suitable processor.
Such processors may comprise, for example, a microprocessor, an
ASIC, a state machine, or other processor, and can be any of a
number of computer processors, such as processors from Intel
Corporation, Advanced Micro Devices Incorporated, and Motorola
Corporation. The computer-readable media stores instructions that,
when executed by the processor, cause the processor to perform the
steps described herein.
[0026] The client 100 provides a software layer, which is the
interface through which the user interacts with the system by
receiving and displaying data to and from the user. In one
embodiment, the software layer is implemented in the programming
language C# (also referred to as C Sharp). In other embodiments,
the software layer can be implemented in other languages such as
Java or C++. The software layer may be graphical in nature, using
visual representations of data to communicate said data to one or
more users. The visual representations of data may also be used to
receive additional data from one or more users.
[0027] Embodiments of computer-readable media comprise, but are not
limited to, an electronic, optical, magnetic, or other storage
device, transmission device, or other device that comprises some
type of storage and that is capable of providing a processor with
computer-readable instructions. Other examples of suitable media
comprise, but are not limited to, a floppy disk, CD-ROM, DVD,
magnetic disk, memory chip, ROM, RAM, PROM, EPROM, EEPROM, an ASIC,
a configured processor, all optical media, all magnetic tape or
other magnetic media, or any other medium from which a computer
processor can read instructions. Also, various other forms of
computer-readable media may be embedded in devices that may
transmit or carry instructions to a computer, including a router,
private or public network, or other transmission device or channel,
both wired and wireless. The instructions may comprise code from
any suitable computer-programming language, including, for example,
C, C++, C#, Visual Basic, Java, Python, Perl, and JavaScript.
Furthermore the instructions may be comprise code capable of
interfacing with Microsoft Windows Presentation Foundation
subsystem for rendering a graphical user interface.
[0028] The application server 200 also comprises a processor and a
memory. The application server may execute business logic or other
shared processes. The application server may be, for example, a
Microsoft Windows Server operating in a .NET framework, an IBM
Weblogic server, or a Java Enterprise Edition (J2E) server. While
the application server 200 is shown as a single server, the
application server 200, and the other servers 300, 400 shown may be
combined or may include multiple servers operating together to
perform various processes. In such embodiments, techniques such as
clustering or high availability clustering may be used. Benefits to
architectures such as these include redundancy and performance,
among others.
[0029] In the embodiment shown in FIG. 1, the application server
200 is in communication with a web server 300 via a network
connection 250. The web server 300 also comprises a processor and a
memory. In the memory are stored applications including web server
software. Examples of web server software include Microsoft
Internet Information Services (IIS), Apache Web Server, and Sun
Java System Web Server from Oracle, among others.
[0030] In the embodiment shown in FIG. 1, the web server 300 is in
communication with a database 400 via a network connection 350 and
a network connection 450. The web server 300 provides a web service
layer that, together or separate from application server 200, acts
as middleware between a database 400 and the software layer,
represented by the client 100. The web server 300 communicates with
the database 400 to send and retrieve data to and from the database
400.
[0031] The network 500 may be any of a number of public or private
networks, including, for example, the Internet, a local area
network ("LAN"), or a wide area network ("WAN"). The network
connections 150, 250, 350, and 450 may be wired or wireless
networks and may use any known protocol or standard, including
TCP/IP, UDP, multicast, 802.11b, 802.11g, 802.11n, or any other
known protocol or standard. Further, the network 100 may represent
a single network or different networks. As would be clear to one of
skill in the art, the client 100, servers 200, 300, and database
400 may be in communication with each other over the network or
directly with one another.
[0032] The database 400 may be one or a plurality of databases that
store electronically encoded information comprising the data
required to plan, design, and execute a clinical trial. In one
embodiment, the data comprises one or more design elements
corresponding to the various elements related to one or more
clinical trials. The database 400 may be implemented as any known
database, including an SQL database or an object database. Further,
the database software may be any known database software, such as
Microsoft SQL Server, Oracle Database, MySQL, Sybase, or
others.
[0033] In addition either the database 400 or the web server 300
may execute search server software, such as Apache SOLR. Using a
relational database management system ("RDBMS") software, such as
SQLServer 2008, in conjunction with a search server product, such
as Apache SOLR, that provides indexing functionality, provides fast
responses to queries across exceptionally large sets of data.
Patient Population Editor
[0034] One embodiment of the present invention comprises a patient
population editor for selecting criteria for shaping patient
populations for clinical trials. The patient population editor
allows the user to select patient population source data and to
select and manipulate adjustable patient criteria to include or
exclude segments of the overall patient population for a specific
clinical trial and to visually see the effects of the selections.
In one embodiment the adjustable criteria available for
manipulation are dynamically loaded based on the selected patient
population source data. The patient population editor in one such
embodiment presents choices to the user in the form of slider input
tools ("sliders") and checkboxes. The user then adjusts the sliders
to set limits for patient criteria associated with each slider and
checks desired checkboxes associated with patient criteria. For
example, limits may comprise upper and lower boundaries. In one
embodiment, the patient criteria categories include:
[0035] Co-morbidities
[0036] Concomitant medications
[0037] Age
[0038] Gender
[0039] Ethnicity
[0040] The application executing on the application server 200
executes an algorithm to dynamically generate a query, based on the
selected/manipulated adjustable patient criteria, directed to the
database 400. The application then generates graphical views of the
data returned by the database 400 for presentation on the client
100. The embodiments described herein may operate in a similar way
within this architecture or may be implemented in other ways. For
example, in some embodiments, the client 100 may perform much of
the processing in addition to providing the display and receiving
the user's input.
[0041] FIG. 2 is a screen shot of a patient population editor view,
comprising a patient criteria selection interface A, an age range
line chart B, an ethnicity pie chart C, a patient thermometer bar
chart D, and a Venn Bar diagram E.
[0042] In the embodiment shown in FIG. 2, patient criteria
selection interface A comprises data entry mechanisms such as
sliders for selecting upper and lower bounds for the age range of
the patient population and checkboxes for selecting gender and
ethnicity criteria. In other embodiments, drop down menus, radio
buttons, editable data entry fields, or any other user interface
mechanism known in the art may be used. Furthermore, while the
embodiment of the patient criteria selection interface A shown in
FIG. 2 allows for selection of co-morbidities, concomitant
medications, body mass index, age, gender, and ethnicity, any other
relevant criteria for shaping a patient population may be used. For
example, criteria selection interfaces related to lab results,
height, weight, lifestyle criteria, payment method, or any other
relevant criteria may be provided in various embodiments.
[0043] Age range line chart B, ethnicity pie chart C, patient
thermometer bar chart D, and Venn Bar diagram E are examples of
graphical display mechanisms that may be used to aid the user's
understanding of the adjustable criteria selections/manipulations
on the patient population. The age range line chart B shows the age
range of the patient population by gender and percentage of the
patients. Ethnicity pie chart C shows the breakdown of the
ethnicity of the patient population based on the size of the pieces
of pie representing each ethnicity. Patient thermometer bar chart D
shows how many patients would be available in the patient
population after applying the selected patient criteria. Finally
Venn Bar E is operative to show overlaps between populations to
allow the user to understand the individual impact of the user's
choices on various segments of the patient population. The
functionality of the Venn Bar is described in more detail in
provisional application entitled "Method and System to Manipulate
Multiple Selections against a Population of Elements," Application
No. 61/663,292, attorney docket #31006-842890, filed Jun. 22, 2012,
which is fully incorporated herein by reference.
[0044] FIG. 3 is a flowchart illustrating one method for performing
patient population analysis and manipulation using the patient
population editor according to one embodiment of the present
invention. In the embodiment shown, the user would first select
patient population source at step 302. At step 304, the user would
then manipulate selected patient criteria using a patient
population criteria selection interface such as the interface
described above. Manipulating one or more patient criteria causes
the patient population editor to receive the query parameters,
generate a corresponding query, execute the query on one or more
databases based on the criteria, receive the results of the query,
and to use those results to update one or more graphical display
mechanisms. At step 306, the user then reviews the resulting
prospective patient population and, at step 308, determines if it
is satisfactory. If so, the process ends at step 310. If not, the
user decides to modify selected patient population source data
and/or manipulate one or more patient selection criteria at
decision point 312. This process continues iteratively until a
satisfactory patient population is created.
Patient Population Query Editor
[0045] One embodiment of the present invention comprises a patient
population query editor for authoring complex queries for shaping a
prospective patient population. The patient population query editor
allows the user visually construct complex queries to shape a
prospective patient population for a specific clinical trial by
including or excluding segments of an overall patient population.
The patient population query editor in one such embodiment allows a
user to select patient population source data and provides a list
of patient criteria elements that may be dragged and dropped into a
query builder window and manipulated to visually construct a query.
The patient criteria elements have associated values that define
the scope related to the element. In one embodiment, patient
criteria elements within a query builder window operate to show the
information related to the number of patients from the patient
population source data that meet the scope defined for the
element.
[0046] In one embodiment, the available criteria elements are
dynamically loaded based on the selected patient population source
data. In one such embodiment, the patient criteria elements may
largely correspond to the patient criteria described above in
relation to the patient population editor, and therefore may
include:
[0047] Co-morbidities
[0048] Concomitant medications
[0049] Age
[0050] Gender
[0051] Ethnicity
[0052] Lab Results
[0053] Height
[0054] Weight
[0055] Lifestyle Criteria
[0056] Payment method
[0057] The application executing on the application server 200
executes an algorithm to dynamically generate a query, based on a
graphical representation of a query in a query builder window,
directed to the database 400. The application then updates the
patient criteria elements within a query builder window to show the
number of patients corresponding to the defined scope of each
element, and updates an overall number of patients selected from
the patient population source data displayed in the patient
population query editor based on the data returned by the database
400 for presentation on the client 100. The embodiments described
herein may operate in a similar way within this architecture or may
be implemented in other ways. For example, in some embodiments, the
client 100 may perform much of the processing in addition to
providing the display and receiving the user's input.
[0058] FIG. 4 is a screen shot of a patient population query editor
view according to one embodiment of the present invention. The
screen shot of FIG. 4 comprises an interface for selecting patient
population source data, a list of patient criteria elements, and
two query builder windows. In the embodiment shown, a single set of
patient population source data, along with the total population of
that source data, is listed in the Data Source field in the upper
left area of the screen shot. Below the Data Source field is the
list of patient criteria elements that may be dragged into query
builder windows, such as query builder windows labeled "A" and "B"
in FIG. 4 (respectively "query builder window A" and "query builder
window B". FIG. 4 illustrates the Body Mass Index patient
population criteria element ("BMI element") being dragged and
placed into the query builder window A. As the BMI element is
dragged into the area of an existing element, arrows are shown
indicating allowed placement positions. In the embodiment shown,
placing the element above or below an existing element creates a
logical "OR" relationship, whereas placing an element to the left
or right creates a logical "AND" relationship. Various other types
of logical relationships and constructs may be created visually in
embodiments of the present invention.
[0059] FIG. 5 is a screenshot of a patient criteria element
manipulation interface for defining the scope of a patient criteria
element according to one embodiment of the present invention. This
interface may be displayed automatically when the element is
dragged and dropped into a query builder window. Alternatively, the
interface may be opened by clicking on a button displayed on the
element within a query builder window.
[0060] In the embodiment shown in FIG. 5, the patient criteria
element manipulation interface comprises sliders for selecting
upper and lower bounds for the body mass index of the patient
population. In other embodiments, checkboxes, drop down menus,
radio buttons, editable data entry fields, or any other user
interface mechanism known in the art may be used may be used for
manipulating the body mass index criteria element or any other
criteria element. Furthermore, while the embodiments shown in FIGS.
4 and 5 list patient population criteria elements for
co-morbidities, concomitant medications, body mass index, age,
gender, and ethnicity, any other relevant criteria for shaping a
patient population may be used. For example, criteria selection
interfaces related to lab results, height, weight, lifestyle
criteria, payment method, or any other relevant criteria element
may be provided.
[0061] FIG. 6 is a screen shot of a patient population query editor
view according to one embodiment of the present invention. In
particular, FIG. 6 illustrates the patient population query editor
view of FIG. 4 after the BMI element has been added to the query
represented in query builder window A. As can be seen in FIGS. 4
and 6, the values selected/entered to define the scope of the
patient criteria elements, and the corresponding patient
population, are displayed within the criteria elements within the
query builder windows. With the addition of the BMI element in
query builder window A, the query represented in query builder
window A requires that the prospective patient population must be
age 18-82 or have a BMI between 25 and 40.9, and must be
female.
[0062] FIG. 7 is a flowchart illustrating one method for performing
patient population analysis and manipulation using the patient
population query editor according to one embodiment of the present
invention. In the embodiment shown, the user would first select
patient population source data at step 702. The user would then
drag a patient population criteria element into a desired location
in a query builder window at step 704. The user would then define
or adjust the scope of the patient population criteria element at
step 706. Adding and/or manipulating one or more patient population
criteria elements causes the application 200 to query one or more
databases based on the patient criteria elements and to update the
patient population information shown within each criteria element
and the overall population tally displayed within the patient
population query editor view. At step 708, the user then reviews
the resulting prospective patient population and, at step 710,
determines if it is satisfactory. If so, the process ends at step
712. If not, the user decides to modify the selected patient
population source data, drag an additional patient criteria element
into a query builder window, reposition an existing patient
criteria element within a query builder window, and/or adjust the
scope of a patient criteria element at decision point 714. This
process continues iteratively until a satisfactory patient
population is created.
[0063] FIG. 8 is a screen shot of a patient population query editor
view according to one embodiment of the present invention. In
particular, FIG. 8 illustrates the patient population query editor
view of FIG. 6 after a user clicked the green flag displayed within
the BMI element. Clicking the green flags in patient criteria
elements causes the flag to turn red, and vice-versa. Toggling the
flag between green and red changes whether the element is including
or excluding patient segments falling within the scope of the
element's settings.
[0064] FIG. 9 is a screen shot of a patient population query editor
view according to one embodiment of the present invention. In
particular, FIG. 9 illustrates the use of a Venn Bar for comparing
the query represented by the element configuration displayed in
query builder window A and the query represented by the element
configuration displayed in query builder window B. The green
segments in bars A and B and located in the column "A, B,"
represent a portion of the population that result from both
queries. The blue segment in bar A located in the column "A" that
is not in bar B represents a portion of the population that only
results from query A. The grey segment in the row and column
labeled "0" indicates the portion of the population that is not a
result of either query.
Advantages
[0065] Embodiments of the present invention provide many advantages
over conventional methods of analyzing the effects of inclusion and
exclusion criteria on a patient population. For example, employing
a blended approach using RDBMS technologies and SOLR allows the
present invention provides fast access to large data sources with
all queries taking less than approximately 30 seconds.
Consequently, the present invention provides substantially
real-time analysis capabilities of the effects of inclusion and
exclusion criteria on a prospective patient population, whereas
earlier systems typically required 30 minutes or more to provide
results to similar queries.
[0066] The patient population editor provides the ability for a
user to easily adjust inclusion and exclusion criteria and view
easily-readable and intuitive graphical representations of the
results within seconds. For example, the patient population editor
may use a Venn Bar diagram that shows overlaps between populations
to allow the user to more easily understand the individual impact
of choices on various segments of the patient population.
[0067] The patient population query editor provides a graphical
interface that allows a user to visually construct complex queries
using patient criteria elements. The patient population query
editor provides one or more query builder windows to allow a user
to simultaneously view and edit multiple queries. Further, the
patient population query editor provides a graphical
representation, such as a Venn Bar, that allows a user to easily
view patient population segments common to multiple queries,
population segments that result from a single query, and population
segments that do not result from any of the queries.
General
[0068] The foregoing description of the embodiments of the
invention has been presented only for the purpose of illustration
and description and is not intended to be exhaustive or to limit
the invention to the precise forms disclosed. Numerous
modifications and adaptations are apparent to those skilled in the
art without departing from the spirit and scope of the
invention.
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