INTERACTIVE HEALTHCARE MODELING

• US 20140257829A1
• Filed: 03/08/2013
• Published: 09/11/2014
• Est. Priority Date: 03/08/2013
• Status: Abandoned Application

• Current Assignee: Evidera Archimedes, Inc.
• Original Assignee: Archimedes, Inc. (Thermo Fisher Scientific Incorporated)
• Inventors: Schuetz, Charles Andrew, Cohen, Marc-david
• Application Number:
  US13/791,810
• Publication Number:
  US 20140257829A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method comprises receiving a prediction request that comprises a population definition and one or more healthcare treatment criteria specifying a treatment scenario; in response to receiving the prediction request, performing in a real-time: parsing the prediction request to identify the population definition and the one or more healthcare treatment criteria; mapping the one or more healthcare treatment criteria to a function of one or more input variables to determine a particular dataset, from a plurality of datasets; based, at least in part, on the population definition and the particular dataset, determining a response surface; determining prediction data by estimating, using the response surface which approximates the healthcare simulation model, simulation results that using the healthcare simulation model would yield; returning the prediction data.

Claims

1. A method comprising:

receiving a prediction request that comprises a population definition and one or more healthcare treatment criteria specifying a treatment scenario;

in response to receiving the prediction request, performing in a real-time;

parsing the prediction request to identify the population definition and the one or more healthcare treatment criteria;

mapping the one or more healthcare treatment criteria to a function of one or more input variables to determine a particular dataset, from a plurality of datasets;

based, at least in part, on the population definition and the particular dataset, determining a response surface;

determining prediction data by estimating, using the response surface which approximates the healthcare simulation model, simulation results that using the healthcare simulation model would yield;

returning the prediction data;

wherein the method is performed by one or more computing devices.

2. The method of claim 1, wherein the response surface is generated according to an experimental design.

3. The method of claim 1, wherein the prediction request comprises a request to predict effects of the treatment scenario on individuals specified by the population definition.

4. The method of claim 2, wherein the experimental design is a matrix describing a set of experiments and simulations performed using any one of a plurality of healthcare models.

5. The method of claim 2, wherein the response surface allows:

comparing effects of the treatment scenario, specified by the one or more healthcare treatment criteria, on individuals specified by the population definition;

determining one or more optimum patient populations for the treatment scenario;

determining one or more optimum treatment scenarios for the individuals specified by the population definition.

6. A method comprising:

receiving a plurality of combinations of input variables, each of the plurality of combinations of input variables comprising health data;

retrieving, from a plurality of healthcare models, a particular healthcare model that accepts the plurality of combinations of input variables;

for each of the plurality of combination of input variables;

generating a response dataset by performing one or more healthcare model simulations using the particular healthcare model and the input variables by varying values of the input variables using an experimental design, and determining values of response variables;

storing the response dataset in a database;

wherein the one or more healthcare model simulations comprise performing a statistical analysis;

wherein the plurality of combinations of input variables comprises any one of;

population-related data and treatment-scenario data;

wherein the method is performed by one or more computing devices.

7. The method of claim 6, wherein the plurality of combinations of input variables comprises any one data of:

treatment data, biomarkers data, disease risk data and population data;

wherein the response variables comprise any one data of;

disease event rates and other statistical information.

8. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform:

receiving a prediction request that comprises a population definition and one or more healthcare treatment criteria specifying a treatment scenario;

in response to receiving the prediction request, performing in a real-time;

parsing the prediction request to identify the population definition and the one or more healthcare treatment criteria;

mapping the one or more healthcare treatment criteria to a function of one or more input variables to determine a particular dataset, from a plurality of datasets;

based, at least in part, on the population definition and the particular dataset, determining a response surface;

determining prediction data by estimating, using the response surface which approximates the healthcare simulation model, simulation results that using the healthcare simulation model would yield;

returning the prediction data.

9. The non-transitory computer-readable storage medium of claim 8, wherein the response surface is generated according to an experimental design.

10. The non-transitory computer-readable storage medium of claim 9, wherein the prediction request comprises a request to predict effects of the treatment scenario on individuals specified by the population definition.

11. The non-transitory computer-readable storage medium of claim 8, wherein the experimental design is a matrix describing a set of experiments and simulations performed using any one of a plurality of healthcare models.

12. The non-transitory computer-readable storage medium of claim 8, wherein the response surface allows:

comparing effects of the treatment scenario, specified by the one or more healthcare treatment criteria, on individuals specified by the population definition;

determining one or more optimum patient populations for the treatment scenario;

determining one or more optimum treatment scenarios for the individuals specified by the population definition.

13. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform:

receiving a plurality of combinations of input variables, each of the plurality of combinations of input variables comprising health data;

retrieving, from a plurality of healthcare models, a particular healthcare model that accepts the plurality of combinations of input variables;

for each of the plurality of combination of input variables;

generating a response dataset by performing one or more healthcare model simulations using the particular healthcare model and the input variables by varying values of the input variables using an experimental design, and determining values of response variables;

storing the response dataset in a database;

wherein the one or more healthcare model simulations comprise performing a statistical analysis;

wherein the plurality of combinations of input variables comprises any one of;

population-related data and treatment-scenario data.

14. The non-transitory computer-readable storage medium of claim 13, wherein the plurality of combinations of input variables comprises any one data of:

treatment data, biomarkers data, disease risk data and population data;

wherein the response variables comprise any one data of;

disease event rates and other statistical information.

15. An apparatus, comprising:

one or more processors;

a request processor coupled to the one or more processors, and configured to perform;

receiving a prediction request that comprises a population definition and one or more healthcare treatment criteria specifying a treatment scenario;

in response to receiving the prediction request, performing in a real-time;

parsing the prediction request to identify the population definition and the one or more healthcare treatment criteria;

mapping the one or more healthcare treatment criteria to a function of one or more input variables to determine a particular dataset, from a plurality of datasets;

based, at least in part, on the population definition and the particular dataset, determining a response surface;

determining prediction data by estimating, using the response surface which approximates the healthcare simulation model, simulation results that using the healthcare simulation model would yield;

returning the prediction data.

16. The apparatus of claim 15, wherein the response surface is generated according to an experimental design.

17. The apparatus of claim 16, wherein the prediction request comprises a request to predict effects of the treatment scenario on individuals specified by the population definition.

18. The apparatus of claim 15, wherein the experimental design is a matrix describing a set of experiments and simulations performed using any one of a plurality of healthcare models.

19. The apparatus of claim 15, wherein the response surface allows:

comparing effects of the treatment scenario, specified by the one or more healthcare treatment criteria, on individuals specified by the population definition;

determining one or more optimum patient populations for the treatment scenario;

determining one or more optimum treatment scenarios for the individuals specified by the population definition.

20. An apparatus, comprising:

one or more processors;

a model executing unit coupled to the one or more processors, and configured to perform;

receiving a plurality of combinations of input variables, each of the plurality of combinations of input variables comprising health data;

retrieving, from a plurality of healthcare models, a particular healthcare model that accepts the plurality of combinations of input variables;

for each of the plurality of combination of input variables;

generating a response dataset by performing one or more healthcare model simulations using the particular healthcare model and the input variables by varying values of the input variables using an experimental design, and determining values of response variables;

storing the response dataset in a database;

wherein the one or more healthcare model simulations comprise performing a statistical analysis;

wherein the plurality of combinations of input variables comprises any one of;

population-related data and treatment-scenario data.

21. The apparatus of claim 20, wherein the plurality of combinations of input variables comprises any one data of:

treatment data, biomarkers data, disease risk data and population data;

wherein the response variables comprise any one data of;

disease event rates and other statistical information.