Automated profiler system for providing medical information to patients

• US 20020165737A1
• Filed: 03/20/2002
• Published: 11/07/2002
• Est. Priority Date: 03/15/1999
• Status: Abandoned Application

• Current Assignee: Physicians' Desk Reference, Inc.
• Original Assignee: NexCura, Inc. (McKesson Corp.)
• Inventors: Mahran, Howard E.
• Application Number:
  US10/104,575
• Publication Number:
  US 20020165737A1
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 70/20 relating to practices or guidelines
• CPC Class Codes: Y10S 128/923 by comparison of patient data to other data
• CPC Class Codes: Y10S 706/902 Application using ai with detail of the ai system
• CPC Class Codes: Y10S 706/924 Medical
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

Apparatus and methods are disclosed for generating individualized medical profiles based on information provided by a patient, and on data extracted from medical literature. In a first stage, medical literature is selected for inclusion in a database by using specified inclusion criteria. Information on input parameters to studies contained in the literature, output parameters of the studies, and algorithms contained in the studies is extracted from the literature, and stored in a database. In a second stage, patients provide information, which is matched against the input parameters of the studies in the database, and algorithms from the matched studies are applied to the information provided by the patient to produce values for the output parameters. Combination analysis is used to combine the values of output parameters into “super-category” values, that are used to generate an individualized medical profile.

Claims

1. A method of generating individualized medical profiles for patients, the method comprising:

selecting medical literature for inclusion in a medical database, based on a set of predetermined inclusion criteria;

extracting data from studies in the selected medical literature for addition to the medical database, the data extracted for each study including one or more input parameters, one or more output parameters, and one or more algorithms;

compiling a set of input parameters comprising one or more input parameters extracted from each study, a set of output parameters comprising one or more output parameters extracted from each study, and a set of algorithms comprising one or more algorithms extracted from each study;

collecting information from a patient to provide values for a subset of the set of input parameters;

matching the subset of input parameters to the one or more input parameters for each study in the medical database to produce a set of applicable studies;

using a first subset of the set of algorithms corresponding to the applicable studies on the values of the subset of input parameters to produce values for a subset of the set of output parameters corresponding to the applicable studies; and

generating an individualized medical profile based on the values of the subset of output parameters.

2. The method of claim 1, further comprising:

adding data on treatments and treatment indications to the medical database;

using the values of the subset of output parameters to determine which treatment indications are met; and

generating a treatment indications report wherein the treatment indications for each treatment are listed, along with a mark showing whether each treatment indication was met,

wherein generating the individualized medical profile further comprises including the treatment indications report in the individualized medical profile.

3. The method of claim 2, further comprising:

applying combination analysis to the values of the subset of output parameters to produce a set of combined super-category values,

wherein using the values of the subset of output parameters to determine which treatment indications are met comprises using the set of combined super-category values to determine which treatment indications are met.

4. The method of claim 3, wherein using the values of the subset of output parameters to determine which treatment indications are met further comprises using the values of the subset of input parameters to determine which treatment indications are met.

5. The method of claim 2, wherein adding data on treatments and treatment indications to the medical database comprises adding a rule to the medical database for each indication, the rule determining whether the treatment indication is met.

6. The method of claim 5, wherein using the values of the subset of output parameters to determine which treatment indications are met further comprises using the rule for each treatment indication to determine whether the treatment indication is met.

7. The method of claim 2, further comprising generating outcome information for each treatment, and including the outcome information in the individualized medical profile.

8. The method of claim 7, wherein generating outcome information for each treatment comprises generating an outcome score for each treatment.

9. The method of claim 7, wherein generating outcome information for each treatment comprises:

determining which studies in the medical database are applicable to the outcome of a treatment; and

using a second subset of the set of algorithms corresponding to the studies that are applicable to the outcome of the treatment to produce output values indicative of the outcome of the treatment.

10. The method of claim 7, wherein the outcome information is stored in an individualized patient output dataset in the medical database.

11. The method of claim 2, wherein information on which treatment indications were met is stored in an individualized patient output dataset in the medical database.

12. The method of claim 1, wherein values of the subset of output parameters are stored in an individualized patient output dataset in the medical database.

13. The method of claim 1, wherein the first subset of algorithms comprise calculations or tables that map values of the subset of input parameters to values of the subset of output parameters.

14. The method of claim 13, wherein the tables optionally represent neural networks.

15. The method of claim 1, wherein matching the subset of input parameters to the one or more input parameters for each study further comprises:

compiling a list of unmatched studies, including each study for which the subset of input parameters does not match the one or more input parameters of the respective study; and

using the list of unmatched studies to generate a missing data report.

16. The method of claim 1, wherein the method further comprises applying combination analysis to the values of the subset of output parameters to produce a set of combined super-category values.

17. The method of claim 16, wherein the combination analysis comprises a technique chosen from a set consisting of meta-analysis, averaging, fuzzy logic, fuzzy sets, and interactive combination techniques.

18. The method of claim 17, wherein the data extracted for each study includes statistical information, and the statistical information is used to determine which combination analysis technique is applied.

19. The method of claim 1, wherein collecting information from the patient comprises:

generating an input form having input fields for a plurality of input parameters from the set of input parameters; and

extracting values for the plurality of input parameters from values entered by the patient into the input fields.

20. The method of claim 19, wherein each one of the set of input parameters in the medical database includes display code for displaying that input parameter, and generating the input form comprises executing the display code for each one of the plurality of input parameters in the form.

21. The method of claim 19, wherein each one of the set of input parameters in the medical database includes validation code for validating that input parameter, and extracting values for the subset of input parameters from data entered by the patient comprises executing the validation code for each value entered by the patient.

22. The method of claim 19, wherein each one of the set of input parameters includes an identifier for a form on which that input parameter should appear.

23. The method of claim 1, wherein selecting medical literature for inclusion in the medical database further comprises:

providing the medical literature to a review board including a plurality of reviewers;

having each reviewer assign each study in the medical literature a score, based on the predetermined inclusion criteria; and

determining which studies should be included in the medical database based on the scores assigned by the reviewers.

24. The method of claim 23, wherein determining which studies should be included comprises computing an average score for each of the studies, and including studies for which the average score exceeds a predetermined threshold.

25. The method of claim 1, wherein the predetermined inclusion criteria comprise one or more of:

criteria based on the objectives of the study, on the study population, on the description of the methods used in the study, on the results of the study, on the statistical significance of the study, and on the ability to summarize the results of the study in the form of a calculation or table.

26. The method of claim 1, wherein the data extracted for each study further includes citation information, a patient readable abstract, statistical information, and information on the study population.

28. The digital storage medium of claim 27, wherein the fields of each study record comprise:

an input parameters field that contains identifiers of records in the input parameter table for input parameters associated with a study;

an output parameters field that contains identifiers of records in the output parameter table for output parameters associated with the study; and

an algorithms field that contains algorithms from the study that map values of the input parameters associated with the study to values of output parameters associated with the study.

29. The digital storage medium of claim 28, wherein the algorithms field comprises a calculations field, containing calculations or tables that map values of input parameters to values of output parameters.

30. The digital storage medium of claim 29, wherein the tables in the calculations field represent neural networks.

31. The digital storage medium of claim 36, wherein the fields of each study record further comprise:

a citation information field, which stores citation information, such as the author, title, publication date, and journal in which the study appeared; and

an abstract field, which contains an abstract for the study.

32. The digital storage medium of claim 28, wherein the fields of each study record further comprise one or more of:

a statistical information field, that contains statistical information on the study;

a study population field that stores information on the size of the study population;

an output category field that identifies the function of the output of the study; and

a treatment category field that identifies the treatment that was applied to a study population.

33. The digital storage medium of claim 27, wherein the fields of each input parameter record comprise a name field, containing the name of the input parameter, and a description field, containing a description of the input parameter.

34. The digital storage medium of claim 27, wherein the fields of each input parameter record comprise:

a display code field, containing display code that displays the input parameter when the display code is executed; and

a validation code field, containing validation code that validates checks to see if a value for the input parameter is valid when the validation code is executed.

35. The digital storage medium of claim 27, wherein the fields of each input parameter record comprise a form ID field, which identifies input forms on which the input parameter should appear.

36. The digital storage medium of claim 27, wherein the fields of each output parameter record comprise a name field, containing the name of the output parameter, and a description field, containing a description of the output parameter.

37. The digital storage medium of claim 27, wherein the fields of each output parameter record comprise a super-category field, containing an identifier of the super-category into which values of the output parameter are combined.

38. The digital storage medium of claim 27, wherein the medical database further comprises a treatment indications table, containing information on the indications for treatments, and wherein the treatment indications table stores a plurality of indication records, each indication record comprising a plurality of fields containing information on an indication for a treatment.

39. The digital storage medium of claim 38, wherein the fields of each indication record comprise one or more of:

a treatment ID field that identifies the treatment to which the indication pertains;

a rule field that contains a rule that must be satisfied for the indication to be met; and

a description field that contains a description of the indication.

40. The digital storage medium of claim 27, wherein the medical database further comprises a patient input dataset that stores values of input parameters entered by a patient.

41. The digital storage medium of claim 27, wherein the medical database further comprises a patient output dataset that stores values of output parameters and super-category values computed based on information provided by a patient.

27. A digital storage medium storing a medical database, the database comprising a literature dataset, containing information on selected medical literature, the literature dataset including:

a study table that contains information on studies extracted from the selected medical literature, the study table storing a plurality of study records, each study record comprising a plurality of fields containing information on a study;

an input parameter table that stores a plurality of input parameter records, each input parameter record comprising a plurality of fields containing information on an input parameter; and

an output parameter table that stores a plurality of output parameter records, each output parameter record comprising a plurality of fields containing information on an output parameter.

42. A computer system for generating individualized medical profiles for patients, the computer system comprising a server storing a series of programmed routines, the computer system further comprising:

a medical database containing information on studies extracted from medical literature, the information comprising a set of input parameters, a set of output parameters and a set of algorithms, each study having one or more input parameters, one or more output parameters, and one or more algorithms;

a data collection routine that collects information from a patient to provide values for a subset of the set of input parameters;

a matching routine that matches the subset of input parameters for which values are collected from the patient with the set input parameters to produce a set of applicable studies;

a computation routine that uses algorithms from the applicable studies on the values of the subset of input parameters to produce values for a subset of the set of output parameters; and

an output routine that generates an individualized medical profile based on the values of the subset of output parameters.

43. The computer system of claim 42, wherein the medical database further comprises data on treatments and treatment indications from the medical database, the computer system further comprising:

a treatment routine that uses the values of the output parameters to determine which treatment indications are met and generates a treatment indications report wherein the treatment indications for each treatment are listed, along with a mark showing whether each treatment indication was met.

44. The computer system of claim 43, wherein the treatment routine applies combination analysis to the values of the subset of output parameters to produce a set of combined super-category values and uses the set of combined super-category values to determine which treatment indications are met.

45. The computer system of claim 43, wherein the treatment routine uses the values of the subset of input parameters to determine which treatment indications are met.

46. The computer system of claim 43, wherein the medical database stores a rule for each treatment indication and the treatment routine uses the rule to determine whether the treatment indication is met.

47. The computer system of claim 43, wherein the computer system further comprises an outcome routine that generates outcome information for each treatment, and the output routine includes the outcome information in the individualized medical profile.

48. The computer system of claim 47, wherein the outcome routine determines which studies in the medical database are applicable to the outcome of a treatment and uses the algorithms from the studies that are applicable to the outcome of the treatment to produce output values indicative of the outcome of the treatment.

49. The computer system of claim 48, wherein the algorithms comprise calculations or tables that map values of input parameters to values of output parameters.

50. The computer system of claim 49, wherein the tables optionally represent neural networks.

51. The computer system of claim 42, wherein the computer system further comprises:

a routine that compiles a list of unmatched studies, including all studies for which the information collected from the patient does not match the one or more input parameters of each one of the studies and uses the list of unmatched studies to generate a missing data report.

52. The computer system of claim 42, wherein the computation routine further comprises a combination routine that applies combination analysis to the values of the subset of output parameters to produce a set of combined super-category values.

53. The computer system of claim 52, wherein the combination routine performs combination analysis using a technique chosen from a set consisting of meta-analysis, averaging, fuzzy logic, fuzzy sets, and interactive combination techniques.

54. The computer system of claim 52, wherein the combination routine accesses statistical information on the studies from the medical database and uses the statistical information to determine which combination analysis technique to apply.

55. The computer system of claim 42, wherein the data collection routine generates an input form having input fields for a plurality of input parameters and extracts values for the plurality of input parameters from values entered by the patient into the input fields.

56. The computer system of claim 55, wherein each one of the set of input parameters in the medical database includes display code for displaying that input parameter, and the data collection routine generates the input form by executing the display code for each one of the plurality of input parameters in the form.

57. The computer system of claim 55, wherein each one of the set of input parameters in the medical database includes validation code for validating that input parameter, and the data collection routine extracts values for the plurality of input parameters from data entered by the patient by executing the validation code for each value entered by the patient.

58. The computer system of claim 55, wherein each one of the set of input parameters includes an identifier for a form on which that input parameter should appear.