U.S. patent application number 13/153673 was filed with the patent office on 2012-12-06 for wellness decision support services.
This patent application is currently assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION. Invention is credited to Mark J.H. Hsiao, Pei-yun S. Hsueh, Sreeram Ramakrishnan, Liangzhao Zeng.
Application Number | 20120308975 13/153673 |
Document ID | / |
Family ID | 47261944 |
Filed Date | 2012-12-06 |
United States Patent
Application |
20120308975 |
Kind Code |
A1 |
Hsiao; Mark J.H. ; et
al. |
December 6, 2012 |
Wellness Decision Support Services
Abstract
Techniques for providing one or more user-centric wellness
decision support services are provided. The techniques include
providing an interface that facilitates selection of a risk
assessment model of interest for a user and an action plan to
trigger one or more follow-up action items, applying the selected
model to assess the user's wellness risk level based on one or more
user wellness records, and applying the selected action plan to
trigger one or more relevant disease management and lifestyle
interventions.
Inventors: |
Hsiao; Mark J.H.; (Sindian
City, TW) ; Hsueh; Pei-yun S.; (Hawthorne, NY)
; Ramakrishnan; Sreeram; (Yorktown Heights, NY) ;
Zeng; Liangzhao; (Mohegan Lake, NY) |
Assignee: |
INTERNATIONAL BUSINESS MACHINES
CORPORATION
Armonk
NY
|
Family ID: |
47261944 |
Appl. No.: |
13/153673 |
Filed: |
June 6, 2011 |
Current U.S.
Class: |
434/247 |
Current CPC
Class: |
G16H 50/20 20180101;
G16H 70/60 20180101; G16H 50/30 20180101 |
Class at
Publication: |
434/247 |
International
Class: |
A63B 69/00 20060101
A63B069/00 |
Claims
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17. A computer program product comprising a tangible computer
readable recordable storage medium including computer useable
program code for providing one or more user-centric wellness
decision support services, the computer program product including:
computer useable program code for providing an interface that
facilitates selection of a risk assessment model of interest for a
user and an action plan to trigger one or more follow-up action
items; computer useable program code for applying the selected
model to assess the user's wellness risk level based on one or more
user wellness records; and computer useable program code for
applying the selected action plan to trigger one or more relevant
disease management and lifestyle interventions.
18. The computer program product of claim 17, further comprising
computer useable program code for using a personal wellness
knowledge manager to maintain a wellness knowledge repository.
19. The computer program product of claim 17, further comprising
computer useable program code for using a wellness decision service
deployment module to analyze input from a knowledge repository and
one or more restrictions and constraints in a user risk profile,
and output an adjusted plan.
20. The computer program product of claim 17, further comprising
computer useable program code for providing a configuration-free
module for use if there is no selection of a risk assessment model
of interest and an action plan.
21. The computer program product of claim 20, wherein the computer
useable program code for providing a configuration-free module for
use if there is no selection of a risk assessment model of interest
and an action plan comprises: computer useable program code for
constructing a user's wellness profile by scanning through one or
more user wellness records and identifying one or more risk
factors; computer useable program code for facilitating interaction
with the user for input of one or more wellness management goals
and risk factor importance; and computer useable program code for
identifying one or more pertinent risk models and associated risk
factors and ranks one or more relevant action plans.
22. A system for providing one or more user-centric wellness
decision support services, comprising: a memory; and at least one
processor coupled to the memory and operative to: provide an
interface that facilitates selection of a risk assessment model of
interest for a user and an action plan to trigger one or more
follow-up action items; apply the selected model to assess the
user's wellness risk level based on one or more user wellness
records; and apply the selected action plan to trigger one or more
relevant disease management and lifestyle interventions.
23. The system of claim 22, wherein the at least one processor
coupled to the memory is further operative to use a wellness
decision service deployment module to analyze input from a
knowledge repository and one or more restrictions and constraints
in a user risk profile, and output an adjusted plan.
24. The system of claim 22, wherein the at least one processor
coupled to the memory is further operative to provide a
configuration-free module for use if there is no selection of a
risk assessment model of interest and an action plan.
25. The system of claim 24, wherein the at least one processor
coupled to the memory operative to provide a configuration-free
module for use if there is no selection of a risk assessment model
of interest and an action plan is further operative to: construct a
user's wellness profile by scanning through one or more user
wellness records and identifying one or more risk factors;
facilitate interaction with the user for input of one or more
wellness management goals and risk factor importance; and identify
one or more pertinent risk models and associated risk factors and
ranks one or more relevant action plans.
Description
FIELD OF THE INVENTION
[0001] Embodiments of the invention generally relate to information
technology, and, more particularly, to health management.
BACKGROUND OF THE INVENTION
[0002] The prevalence of lifestyle-related health problems poses a
grand challenge to national health systems. For example, structured
lifestyle intervention on controlling health risks can be
effective, but the implementation of such user-centric plans can
quickly drain out resources.
[0003] Dynamically forming wellness service ecosystems to offer
personalized lifestyle intervention plans also exist. However,
while existing providers keep expanding service choices to cover
various user needs, there is still a long tail of demand
unsatisfied, such as, for example, the ability to infer wellness
needs and adjust interventions accordingly.
[0004] Additionally, existing approaches often provide a rigid
system design that limits the reusability, composibility, and
accessibility of the components. As a result, the existing systems
do not facilitate individuals with self-assessment capabilities or
control over an individual wellness management process. Also,
existing approaches do not fully utilize risk models.
SUMMARY OF THE INVENTION
[0005] Principles and embodiments of the invention provide
techniques for wellness decision support services. An exemplary
method (which may be computer-implemented) for providing one or
more user-centric wellness decision support services, according to
one aspect of the invention, can include steps of providing an
interface that facilitates selection of a risk assessment model of
interest for a user and an action plan to trigger one or more
follow-up action items, applying the selected model to assess the
user's wellness risk level based on one or more user wellness
records, and applying the selected action plan to trigger one or
more relevant disease management and lifestyle interventions.
[0006] One or more embodiments of the invention or elements thereof
can be implemented in the form of a computer product including a
tangible computer readable storage medium with computer useable
program code for performing the method steps indicated.
Furthermore, one or more embodiments of the invention or elements
thereof can be implemented in the form of an apparatus including a
memory and at least one processor that is coupled to the memory and
operative to perform exemplary method to steps. Yet further, in
another aspect, one or more embodiments of the invention or
elements thereof can be implemented in the form of means for
carrying out one or more of the method steps described herein; the
means can include (i) hardware module(s), (ii) software module(s),
or (iii) a combination of hardware and software modules; any of
(i)-(iii) implement the specific techniques set forth herein, and
the software modules are stored in a tangible computer-readable
storage medium (or multiple such media).
[0007] These and other objects, features and advantages of the
present invention will become apparent from the following detailed
description of illustrative embodiments thereof, which is to be
read in connection with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1 is a diagram illustrating risk-driven wellness
decision support architecture, according to an embodiment of the
present invention;
[0009] FIG. 2 is a diagram illustrating example steps for
risk-driven wellness decision support, according to an embodiment
of the present invention;
[0010] FIG. 3 is a diagram illustrating a user model acquisition
module and personalization framework, according to an embodiment of
the present invention;
[0011] FIG. 4 is a diagram illustrating an example system design
for risk-driven wellness decision, according to an embodiment of
the present invention;
[0012] FIG. 5 is a chart illustrating system-level components,
according to an embodiment of the present invention;
[0013] FIG. 6 is a flow diagram illustrating techniques for
providing one or more user-centric wellness decision support
services, according to an embodiment of the invention; and
[0014] FIG. 7 is a system diagram of an exemplary computer system
on which at least one embodiment of the invention can be
implemented.
DETAILED DESCRIPTION OF EMBODIMENTS
[0015] Principles of the invention include risk-driven wellness
decision support services. As detailed herein, one way to help
overcome "treatment inertia" (that is, the inclination of human
beings to resist change) is to allow the users to perform
self-assessment on wellness risks and find suitable life
intervention plans accordingly. In one or more embodiments of the
invention, the development of a wellness decision support tool
involves at least the tasks of applying risk models to infer a
person's wellness status, and, given the wellness risk assessment,
following the wellness guidelines to select suitable lifestyle
intervention plans.
[0016] Also, one or more embodiments of the invention include
designing a wellness cloud that is a dynamic infrastructure pattern
that follows service-oriented approaches to facilitate the
collaboration among wellness service providers and independent
software vendors (ISVs). On top of the wellness services can be
provided to develop a configurable wellness decision service
engine, where service providers, with permission from the user, can
plug-in various wellness evidences to provide personalized
services.
[0017] Additionally, one or more embodiments of the invention
include components such as storage of a patient's health profile
(for example, previous lab exam results), expert-provided guideline
for health promotion (for example, exercise routines or dietary
plans), connection to a specific brand of monitoring devices for
direct download, and connection to clinical experience (for
example, clinical visit calendar).
[0018] As described herein, a wellness decision support system uses
a statistical engine to perform remote wellness knowledge
application, and can also complement a patient similarity engine to
perform collaborative filtering as the foundation of any
personalization service.
[0019] As further detailed herein, one or more embodiments of the
invention can include the following aspects. To address the
challenge of wellness knowledge reusability, a knowledge manager is
used that handles the publish/subscribe (pub/sub) mechanism of
wellness knowledge (which can be stored in the international
predictive model markup language (PMML) standard) and allows joint
analysis, such that models can be applied on the fly to datasets of
different parties. To address the challenge of wellness decision
service accessibility and composibility, a user-configurable
wellness decision services is used in which a user can specify the
model and guideline of interest in the wellness knowledge
repository and apply them on his or her own wellness records for
assessment and action. Also, for the users/developers who are not
domain experts, one or more embodiments can also include a
configure-free module, which can interactively solicit user models
(that is, wellness management goal and perceived importance of risk
factors) from user input and select the most relevant action plans
according to the learned user model.
[0020] Additionally, one or more embodiments of the invention can
also include a platform that is equipped with connections to
personal wellness record databases and analytics capabilities of
bootstrapping the processing of personal wellness risk profiling
from examples, saving users from the high entry barrier of manual
input. Also, a context-awareness component can be include that
integrates contextual information, which is collected from smart
sensors (for example, activity type, location, social network
status) and users in the loop to infer personal wellness status
(that is, how the patient is). Further, a personalized continuous
feedback loop mechanism can also be included that can update a
current status and recommended services with respect to changes
revealed in the monitoring context.
[0021] In one or more embodiments of the invention, parameters can
be configured to include the types of health risk and the factors a
user wants to control. The configured service can then analyze the
risk factors underlying the selected types of risk models and
compare their risk levels with the selected population group with
which to compare. If no population group is selected, a subset of
users who are the most similar to a particular user's wellness
history can be selected for comparison.
[0022] FIG. 1 is a diagram illustrating risk-driven wellness
decision support architecture, according to an embodiment of the
present invention. By way of illustration, FIG. 1 depicts a user
device 102, a data collection network 104, a personal wellness
record (PWR) 106, a data request component 108, a knowledge manager
component 110, a personal wellness decision support component 112,
application components 114 and output components (for example,
clinical decision support, risk stratification, personalization,
etc.) 116.
[0023] As illustrated in FIG. 1, one or more embodiments of the
invention include the feature of reusable domain knowledge. Domain
experts or vendors can upload risk assessment models and follow-up
action plans for others to use. Additionally, one or more
embodiments of the invention include configuring a wellness
decision service. As depicted in FIG. 1, users can select any given
model from the repository to apply on their own wellness records
for assessment.
[0024] One or more embodiments of the invention, as noted herein,
can also include the feature of a configure-free module. For those
who do not know which model or action plan to choose, service
providers can invoke the configure-free module to solicit input
from healthcare professionals and users so as to select suitable
actions accordingly at the point of wellness care.
[0025] FIG. 2 is a diagram illustrating example steps for
risk-driven wellness decision support, according to an embodiment
of the present invention. By way of illustration, FIG. 2 depicts
preprocessing steps 202, personal wellness risk profiling for
healthcare professionals steps 204, visualization for joint
decision making steps 206 and user model solicitation steps 208.
Preprocessing steps 202 include establishing connection to PWR and
pre-fetching relevant PWR data fields for analysis. Personal
wellness risk profiling for healthcare professionals steps 204
include scanning PWR for relevant risk factors of each important
risk to be watched (based, for example, on a physician's
prescription), triggering relevant risk models (or guidelines) to
estimate risk levels and the importance of each risk factor,
performing a risk-benefit analysis and scoring the weights of
factors to be monitored.
[0026] As also detailed in FIG. 2, visualization for joint decision
making steps 206 include converting the wellness risk profile to
visual objects, creating and exposing widgets that illustrate the
profile from the last step, soliciting user-specified benefits of
interventions, and composing a dashboard based on a combination of
widgets. Additionally, user model solicitation steps 208 include
user interaction with the risk profile and user specification of a
target risk level and a perceived importance of interventions on
each factor. Further, step 210 includes re-ranking action plans
based on the user-specified importance level.
[0027] Accordingly, a user identifies important risks and factors
for wellness decisions and the system of one or more embodiments of
the invention configures the decision service to invoke suitable
action plans. The system selects the action plans that have
interventions on matching risk factors to those in the solicited
user model (that is, the perceived importance levels of the factors
and interventions), and the system ranks these selected action
plans based on, for example, simplified additive multi-attribute
value functions, using either one of the following two
strategies.
[0028] One strategy includes an information-based rating, which
includes ranking action plans with respect to the user model. For
example, the importance level of an action plan is the weighted
average of factor importance:
imp ( u a , ap t ) = f i .di-elect cons. ap t w f i ' imp ( u a , f
i ) w f i ' = w f i / i = 1 n w f i ##EQU00001##
[0029] Another strategy includes collaborative rating, which
includes ranking action plans with respect to the models of users
in the same risk group. For example, the importance level of a
factor is determined by the average of importance ratings
reweighted by the similarity to the user:
imp ( u a , f i ) = n .di-elect cons. N sim ( u a , u n ) imp ( u n
, f i ) n .di-elect cons. N sim ( u a , u n ) ##EQU00002##
[0030] FIG. 3 is a diagram illustrating a user model acquisition
module and personalization framework, according to an embodiment of
the present invention. By way of illustration, FIG. 3 depicts a
device 302, a personal wellness record 304, a personalization
module 306 which includes a risk stratification component 308, a
personal wellness status assessment component 310, a wellness
management model 312 and a user model 314. FIG. 3 also depicts a
user model acquisition component 316, an intervention component 318
and additional information components 320 (for example, physical
activity, nutrition, medication taking, etc.).
[0031] As illustrated in FIG. 3, a user can identify the perceived
importance to wellness decisions, (for example, with respect to
fat, carbohydrate, protein, cholesterol, fiber, etc. intake) as
detailed in one of the examples described herein. Accordingly, as
depicted in FIG. 3, the personalization engine can select the
relevant attributes from a user model to make a prediction of the
user's wellness status as well as make follow-up recommendations.
If there are some attributes missing from the user model that are
essential for prediction and recommendation, the engine will
solicit those attributes from the user.
[0032] FIG. 4 is a diagram illustrating an example system design
for risk-driven wellness decision, according to an embodiment of
the present invention. By way of illustration, FIG. 4 depicts a
personal wellness decision support (PWDS) application kit 402, a
data preparation component 404, a model application component 406,
and component 408 which includes a personal wellness decision
manager component 410, PWDS manager user interface (UI) 412 and a
knowledge manager component 414. FIG. 4 also depicts a scalable
platform 416, which includes a PWDS component 418, a user-specified
configuration component 420, a configure-free module 422, an
expert-provided guideline component 424, a connection 426 to
monitoring devices, a connection 428 to clinical experience, a user
model 430 and a personal wellness record 432.
[0033] In connection with the personal wellness decision support
(PWDS) manager 412, when the user knows what to choose, the flow of
data can continue to user configuration. When the user does not
know what to choose, the configure-free module can be triggered as
follows. A dashboard of risk profiles and widgets is provided to
display impacts of interventions. Also, feedback is solicited from
user to construct user models (that is, target risk and the
perceived benefits of interventions on different risk factors). As
such, risk action plans are selected based on an
information-based/collaborative filtering strategy. Additionally,
one or more embodiments of the invention can include an auto
scale-in/scale-out mechanism implemented to determine how many
instances are needed for current personalization task.
[0034] FIG. 5 is a chart illustrating system-level components,
according to an embodiment of the present invention. By way of
illustration, FIG. 5 depicts a model creation portion 502 and a
decision management and sharing portion 504. FIG. 5 describes who
the likely users of each component are. For example, a user can use
the manager to learn his or her health risk and select follow-up
action plans accordingly, using the dynamically generated widget
and feedbacks on different interventions. The expert can use PWDS
to create or upload new risk models. Also, the vendor can subscribe
to different models the experts have created and stored in the
knowledge repository. Additionally, the vendor can consequently
generate new wellness-related services for target users based on
these learned models.
[0035] An example of applying risk-driven personalization on the
selection of proper nutrition intake plans for diabetic users can
include the following (for illustration purposes). Jane, a diabetic
patient, has been using a wellness management portal to manage her
disease. Her physical examination center has just notified her that
her annual check-up report is now ready online. She logged-in to
see the report and discovered some problem areas and likely
complications (such as, for instance, hypoglycemia episodes) in the
physician's note. As she wants to understand a bit more, she enters
the risk profiling section.
[0036] Accordingly, one or more embodiments of the invention can go
through her personal wellness history (including the new physical
exam results) to extract features that are related to the problem
areas diagnosed by the physician. Also, the system analyzes the
risk level of the problem areas using the extracted features and
shows a chart to the user that illustrates the problem areas, links
each of the problem areas to its likely sources of problem and
calculates the importance level of each factor.
[0037] Additionally, the user's risk profile can be used to trigger
suggestions of follow-up disease management and lifestyle
interventions (for example, daily nutrition intake composition)
based on national guidelines (or the guidelines prescribed by the
physician). In this example case, the user has a high risk of
dyslipidemia (specifically, hyper-lipidemia), therefore a special
diet intervention is recommended to lower total cholesterol (TC)
and LDL cholesterol (LDL-C) concentrations. The national guideline
suggests the daily nutrition composition under such risk as
follows: fat .ltoreq.30%; carbohydrate 50-60%; protein 10-20%;
total cholesterol .ltoreq.300 mg; fiber 25-35 mg. Going through
Jane's blood glucose (BG) monitoring records, one or more
embodiments of the invention can also find that the low-fat,
high-carb meals are not helping Jane prevent hypoglycemia
episodes.
[0038] Following up on the requirement of the guidelines, there are
several options of diet planning available that can meet the
requirement. The configuration-free module of one or more
embodiments of the invention can then be invoked to learn the
dietitian's opinions on Jane's conditions and Jane's own
preferences. First, the acquisition module is invoked to learn the
dietitian's opinions on Jane's conditions and Jane's own
preferences. She chooses the coronary heart disease (CHD) risk as
the target outcome to be improved and uses the dashboard and
widgets to visualize what interventions can help reduce the risk.
After interacting with the system, she answers questions of the
benefits of the different interventions.
TABLE-US-00001 0 worst ideal 1.0 Fat excessive (0) Med (0.3) Low
(0.9) none (1.0) Carb excessive (0) High (0.5) Med (0.7) none (1.0)
Low (0.8) Protein Low (0) excessive (0.7) High (0.9) Med (1.0)
Cholesterol excessive (0) High (0.2) Med (0.8) Low (1.0) Fiber
excessive (0) High (0.3) Low (0.4) Med (1.0)
[0039] One or more embodiments of the invention can then score the
action plans with respect to the solicited user model (that is, the
perceived importance levels of the factors and interventions).
TABLE-US-00002 Meal Plan 1 Meal Plan 2 Meal Plan 3 Fat Low 0.9 None
1.0 High 0.3 Carb Low 0.8 Med 0.7 High 0.5 Protein excessive 0.7
High 0.9 Med 1.0 Cholesterol High 0.2 Med 0.8 Low 1.0 Fiber High
0.3 Med 1.0 Low 0.4
[0040] For each adaptation (modification and insertion) the
adjustment module applies, the system will check if the adapted
plan is feasible. Once all of the available diet plans are
adjusted, the ranker module can be invoked to score the multiple
adjusted plans so that these plans can be displayed in the order of
preference. One or more embodiments of the invention can rank these
selected action plans based on a simplified additive
multi-attribute value function, such as the information-based
rating described herein.
TABLE-US-00003 FAT CARB PRO CHOL FIBER TOTALS Weights 0.38 0.26
0.16 0.12 0.08 Importance scores: Meal Plan 1 0.9 0.8 0.7 0.2 0.3
0.710 Meal Plan 2 1.0 0.7 0.9 0.8 1.0 0.826 Meal Plan 3 0.3 0.5 0.1
0.1 0.4 0.304
[0041] recommends Meal Plan 2
[0042] Based on the personal nutrition need and preferences, when
dining out, the smart nutrition system will personalize the
recommendation scoring of each dish on the menu. For example, foods
that come with higher proportion of non-starchy vegetables and
low-carb fruits (such as berries) will be scored higher for Jane.
In addition, one or more embodiments of the invention also receive
feedbacks from Jane and use the feedback to update recommendations.
The information-based strategy is combined with the collaborative
filtering that can learn from a control group.
[0043] When system developers know what disease risk models and
comorbidity index to incorporate into a user's wellness decision
support, they can, for example, use a knowledge manager component
to check in the wellness knowledge repository of pertinent risk
models, and use the configuration interface of wellness decision
services to apply the pertinent risk models on incoming user
data.
[0044] When system developers do not know what to incorporate, they
can invoke the configure-free module, as detailed herein, to learn
user models. Developers can then configure the decision services
with the learned pertinent risk models and importance risk
factors.
[0045] Accordingly, the configured wellness decision service can be
deployed to users in situations, such as, for example, each time a
new user comes in, his/her wellness profile will be created, and
when s/he returns the next time, his/her profile will be updated
with the changes of risk factors identified through monitoring
data.
[0046] One or more embodiments of the invention also include a
simplified additive multi-attribute value function with
collaborative filtering. This provides a workable means to
implement the principles of risk-based personalized decision
support. Also, it can be more accurate than guideline-based
decision support (more realistic scores, tradeoffs, etc.), and can
identify interventions, specify perceived benefits over
interventions, identify alternative action plans available and
measure scores, as well as provide a simple calculation by additive
functions and collaborative filtering algorithms.
[0047] Accordingly, as detailed herein, one or more embodiments of
the invention can provide a personal wellness status assessment
(using the past to infer current status). Given the selected risk
models from the repository, the system can profile the current
wellness status of a user given his/her wellness record.
Additionally, one or more embodiments can provide personalized
lifestyle intervention recommendations (understanding current
status and context). Given the selected risk models and lifestyle
intervention plan, the system can trigger the suitable follow-up
actions based on wellness records.
[0048] Dynamic service delivery (understanding changes) can also be
provided, in that given the changes in the wellness record, the
wellness decision support can update the user wellness profile
accordingly. Further, one or more embodiments of the invention
additionally include micropayment provisioning (understanding
contribution). As the knowledge manager logs how the risk models
and plans are used by other services, the system can help develop a
micro-payment provisioning mechanism.
[0049] FIG. 6 is a flow diagram illustrating techniques for
providing one or more user-centric wellness decision support
services, according to an embodiment of the present invention. Step
602 includes providing an interface that facilitates selection of a
risk assessment model of interest for a user and an action plan to
trigger one or more follow-up action items. This step can be
carried out, for example, using a personal wellness decision
configuration interface. Providing an interface further facilitates
selection of a target population group with which to compare a
personal risk level.
[0050] In one or more embodiments of the invention, selection of
the risk assessment model can be carried out by the healthcare
professional (or, for example, a case managers or the user) who
work with the service vendors to select the risk assessment model.
The user can play with the widget (provided by one or more
embodiments of the invention) to understand the consequence of
different interventions on the various types of risks being
analyzed. Accordingly, one or more embodiments of the invention
provide flexibility of model selection on the vendor side, as well
as the benefit for the users to select intervention plans based on
both health-professional prescribed assessment model and their own
preferences.
[0051] Step 604 includes applying the selected model to assess the
user's wellness risk level based on one or more user wellness
records. This step can be carried out, for example, using a risk
stratification engine.
[0052] Step 606 includes applying the selected action plan to
trigger one or more relevant disease management and lifestyle
interventions. This step can be carried out, for example, using a
personalized recommendation engine. Applying the selected model to
assess the user's wellness risk level based on one or more user
wellness records further includes assessing the user's wellness
risk level based on records from the selected target population
group.
[0053] The techniques depicted in FIG. 6 also include using a
personal wellness knowledge manager to maintain a wellness
knowledge repository. The knowledge repository can be used in
connection with the models that describe what user attributes are
to be used in analyzing a particular type of risk and in what
fashion (for example, weighting). One or more embodiments of the
invention can also include using a personal wellness decision
support client to facilitate sharing of disease management and
lifestyle intervention action plans (for example, rules for
exercise therapy or nutrition intakes) in an online knowledge
repository. Also, a wellness decision service deployment module can
be used to analyze input from a knowledge repository (for example,
an input disease management plan or related guidelines) and one or
more restrictions and constraints in a user risk profile, and
output an adjusted plan.
[0054] The techniques depicted in FIG. 6 also include providing a
configuration-free module for use if there is no user selection of
a risk assessment model of interest and an action plan. The
configuration-free module solicits input from one or more
healthcare professionals and one or more users. Also, the
configuration-free module includes an automatic profiling module
that constructs a user's wellness profile by scanning through one
or more user wellness records and identifying one or more risk
factors. Additionally, the configuration-free module includes a
user model solicitation interface that facilitates interaction with
the user for input of one or more wellness management goals and
risk factor importance. Further, the configuration-free module
includes a configuration facilitation module that identifies one or
more pertinent risk models and associated risk factors and ranks
one or more relevant action plans.
[0055] Ranking relevant action plans can include information-based
filtering by matchmaking a description of each action plan to one
or more user records and aggregating an importance level rating of
one or more involved risk factors (for example, via:
imp ( u a , ap t ) = f i .di-elect cons. ap t w f i ' imp ( u a , f
i ) w f i ' = w f i / i = 1 n w f i ) . ##EQU00003##
Also, ranking relevant action plans can include collaborative
filtering by aggregating an importance level rating of each risk
factor from one or more users who have a similar wellness history
to the user in question (for example, via:
imp ( u a , f i ) = n .di-elect cons. N sim ( u a , u n ) imp ( u n
, f i ) n .di-elect cons. N sim ( u a , u n ) ) . ##EQU00004##
[0056] Additionally, one or more embodiments of the invention
include using a wellness decision service deployment module to
analyze input from a knowledge repository (for example, an input
disease management plan or related guidelines) and one or more
restrictions and constraints in a user risk profile, and output an
adjusted plan. Further, the techniques depicted in FIG. 6 can
include facilitating a vendor to subscribe to one or more models
(created by experts) stored in a knowledge repository and new
wellness-related services for target users based on the learned
models.
[0057] The techniques depicted in FIG. 6 can also, as described
herein, include providing a system, wherein the system includes
distinct software modules, each of the distinct software modules
being embodied on a tangible computer-readable recordable storage
medium. All the modules (or any subset thereof) can be on the same
medium, or each can be on a different medium, for example. The
modules can include any or all of the components shown in the
figures. In one or more embodiments, the modules include a personal
wellness decision configuration interface module, a risk
stratification engine module and a personalized recommendation
engine module that can run, for example on one or more hardware
processors. The method steps can then be carried out using the
distinct software modules of the system, as described above,
executing on the one or more hardware processors. Further, a
computer program product can include a tangible computer-readable
recordable storage medium with code adapted to be executed to carry
out one or more method steps described herein, including the
provision of the system with the distinct software modules.
[0058] Additionally, the techniques depicted in FIG. 6 can be
implemented via a computer program product that can include
computer useable program code that is stored in a computer readable
storage medium in a data processing system, and wherein the
computer useable program code was downloaded over a network from a
remote data processing system. Also, in one or more embodiments of
the invention, the computer program product can include computer
useable program code that is stored in a computer readable storage
medium in a server data processing system, and wherein the computer
useable program code are downloaded over a network to a remote data
processing system for use in a computer readable storage medium
with the remote system.
[0059] Further, in one or more embodiments of the invention, the
techniques depicted in FIG. 6 can be implemented via instantiation
of program code in a system engine, where the description can be
translated into a computable program to make inference from the
input data.
[0060] As will be appreciated by one skilled in the art, aspects of
the present invention may be embodied as a system, method or
computer program product. Accordingly, aspects of the present
invention may take the form of an entirely hardware embodiment, an
entirely software embodiment (including firmware, resident
software, micro-code, etc.) or an embodiment combining software and
hardware aspects that may all generally be referred to herein as a
"circuit," "module" or "system." Furthermore, aspects of the
present invention may take the form of a computer program product
embodied in one or more computer readable medium(s) having computer
readable program code embodied thereon.
[0061] One or more embodiments of the invention, or elements
thereof, can be implemented in the form of an apparatus including a
memory and at least one processor that is coupled to the memory and
operative to perform exemplary method steps.
[0062] One or more embodiments can make use of software running on
a general purpose computer or workstation. With reference to FIG.
7, such an implementation might employ, for example, a processor
702, a memory 704, and an input/output interface formed, for
example, by a display 706 and a keyboard 708. The term "processor"
as used herein is intended to include any processing device, such
as, for example, one that includes a CPU (central processing unit)
and/or other forms of processing circuitry. Further, the term
"processor" may refer to more than one individual processor. The
term "memory" is intended to include memory associated with a
processor or CPU, such as, for example, RAM (random access memory),
ROM (read only memory), a fixed memory device (for example, hard
drive), a removable memory device (for example, diskette), a flash
memory and the like. In addition, the phrase "input/output
interface" as used herein, is intended to include, for example, one
or more mechanisms for inputting data to the processing unit (for
example, mouse), and one or more mechanisms for providing results
associated with the processing unit (for example, printer). The
processor 702, memory 704, and input/output interface such as
display 706 and keyboard 708 can be interconnected, for example,
via bus 710 as part of a data processing unit 712. Suitable
interconnections, for example via bus 710, can also be provided to
a network interface 714, such as a network card, which can be
provided to interface with a computer network, and to a media
interface 716, such as a diskette or CD-ROM drive, which can be
provided to interface with media 718.
[0063] Accordingly, computer software including instructions or
code for performing the methodologies of the invention, as
described herein, may be stored in one or more of the associated
memory devices (for example, ROM, fixed or removable memory) and,
when ready to be utilized, loaded in part or in whole (for example,
into RAM) and implemented by a CPU. Such software could include,
but is not limited to, firmware, resident software, microcode, and
the like.
[0064] A data processing system suitable for storing and/or
executing program code will include at least one processor 702
coupled directly or indirectly to memory elements 704 through a
system bus 710. The memory elements can include local memory
employed during actual implementation of the program code, bulk
storage, and cache memories which provide temporary storage of at
least some program code in order to reduce the number of times code
must be retrieved from bulk storage during implementation.
[0065] Input/output or I/O devices (including but not limited to
keyboards 708, displays 706, pointing devices, and the like) can be
coupled to the system either directly (such as via bus 710) or
through intervening I/O controllers (omitted for clarity).
[0066] Network adapters such as network interface 714 may also be
coupled to the system to enable the data processing system to
become coupled to other data processing systems or remote printers
or storage devices through intervening private or public networks.
Modems, cable modem and Ethernet cards are just a few of the
currently available types of network adapters.
[0067] As used herein, including the claims, a "server" includes a
physical data processing system (for example, system 712 as shown
in FIG. 7) running a server program. It will be understood that
such a physical server may or may not include a display and
keyboard.
[0068] As noted, aspects of the present invention may take the form
of a computer program product embodied in one or more computer
readable medium(s) having computer readable program code embodied
thereon. Any combination of one or more computer readable medium(s)
may be utilized. The computer readable medium may be a computer
readable signal medium or a computer readable storage medium. A
computer readable storage medium may be, for example, but not
limited to, an electronic, magnetic, optical, electromagnetic,
infrared, or semiconductor system, apparatus, or device, or any
suitable combination of the foregoing. Media block 718 is a
non-limiting example. More specific examples (a non-exhaustive
list) of the computer readable storage medium would include the
following: an electrical connection having one or more wires, a
portable computer diskette, a hard disk, a random access memory
(RAM), a read-only memory (ROM), an erasable programmable read-only
memory (EPROM or Flash memory), an optical fiber, a portable
compact disc read-only memory (CD-ROM), an optical storage device,
a magnetic storage device, or any suitable combination of the
foregoing. In the context of this document, a computer readable
storage medium may be any tangible medium that can contain, or
store a program for use by or in connection with an instruction
execution system, apparatus, or device.
[0069] A computer readable signal medium may include a propagated
data signal with computer readable program code embodied therein,
for example, in baseband or as part of a carrier wave. Such a
propagated signal may take any of a variety of forms, including,
but not limited to, electro-magnetic, optical, or any suitable
combination thereof. A computer readable signal medium may be any
computer readable medium that is not a computer readable storage
medium and that can communicate, propagate, or transport a program
for use by or in connection with an instruction execution system,
apparatus, or device.
[0070] Program code embodied on a computer readable medium may be
transmitted using any appropriate medium, including but not limited
to wireless, wireline, optical fiber cable, radio frequency (RF),
etc., or any suitable combination of the foregoing.
[0071] Computer program code for carrying out operations for
aspects of the present invention may be written in any combination
of one or more programming languages, including an object oriented
programming language such as Java, Smalltalk, C++ or the like and
conventional procedural programming languages, such as the "C"
programming language or similar programming languages. The program
code may execute entirely on the user's computer, partly on the
user's computer, as a stand-alone software package, partly on the
user's computer and partly on a remote computer or entirely on the
remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider).
[0072] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems) and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer program
instructions. These computer program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing apparatus to
produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or
blocks.
[0073] These computer program instructions may also be stored in a
computer readable medium that can direct a computer, other
programmable data processing apparatus, or other devices to
function in a particular manner, such that the instructions stored
in the computer readable medium produce an article of manufacture
including instructions which implement the function/act specified
in the flowchart and/or block diagram block or blocks.
[0074] The computer program instructions may also be loaded onto a
computer, other programmable data processing apparatus, or other
devices to cause a series of operational steps to be performed on
the computer, other programmable apparatus or other devices to
produce a computer implemented process such that the instructions
which execute on the computer or other programmable apparatus
provide processes for implementing the functions/acts specified in
the flowchart and/or block diagram block or blocks.
[0075] The flowchart and block diagrams in the figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, component, segment, or portion of code, which comprises
one or more executable instructions for implementing the specified
logical function(s). It should also be noted that, in some
alternative implementations, the functions noted in the block may
occur out of the order noted in the figures. For example, two
blocks shown in succession may, in fact, be executed substantially
concurrently, or the blocks may sometimes be executed in the
reverse order, depending upon the functionality involved. It will
also be noted that each block of the block diagrams and/or
flowchart illustration, and combinations of blocks in the block
diagrams and/or flowchart illustration, can be implemented by
special purpose hardware-based systems that perform the specified
functions or acts, or combinations of special purpose hardware and
computer instructions.
[0076] It should be noted that any of the methods described herein
can include an additional step of providing a system comprising
distinct software modules embodied on a computer readable storage
medium; the modules can include, for example, any or all of the
components shown in the figures and corresponding descriptions
detailed herein. The method steps can then be carried out using the
distinct software modules and/or sub-modules of the system, as
described above, executing on one or more hardware processors 702.
Further, a computer program product can include a computer-readable
storage medium with code adapted to be implemented to carry out one
or more method steps described herein, including the provision of
the system with the distinct software modules.
[0077] In any case, it should be understood that the components
illustrated herein may be implemented in various forms of hardware,
software, or combinations thereof; for example, application
specific integrated circuit(s) (ASICS), functional circuitry, one
or more appropriately programmed general purpose digital computers
with associated memory, and the like. Given the teachings of the
invention provided herein, one of ordinary skill in the related art
will be able to contemplate other implementations of the components
of the invention.
[0078] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the invention. As used herein, the singular forms "a," "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
[0079] The corresponding structures, materials, acts, and
equivalents of all means or step plus function elements in the
claims below are intended to include any structure, material, or
act for performing the function in combination with other claimed
elements as specifically claimed. The description of the present
invention has been presented for purposes of illustration and
description, but is not intended to be exhaustive or limited to the
invention in the form disclosed. Many modifications and variations
will be apparent to those of ordinary skill in the art without
departing from the scope and spirit of the invention. The
embodiment was chosen and described in order to best explain the
principles of the invention and the practical application, and to
enable others of ordinary skill in the art to understand the
invention for various embodiments with various modifications as are
suited to the particular use contemplated.
[0080] At least one embodiment of the invention may provide one or
more beneficial effects, such as, for example, providing a
configure-free module that can interactively solicit user models
from user input and select the most relevant action plans according
to a learned user model.
[0081] It will be appreciated and should be understood that the
exemplary embodiments of the invention described above can be
implemented in a number of different fashions. Given the teachings
of the invention provided herein, one of ordinary skill in the
related art will be able to contemplate other implementations of
the invention. Indeed, 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 made by one skilled in the
art.
* * * * *