Automated collection and analysis patient care system and method for ordering and prioritizing multiple health disorders to identify an index disorder

• US 6,440,066 B1
• Filed: 11/16/1999
• Issued: 08/27/2002
• Est. Priority Date: 11/16/1999
• Status: Expired due to Term

• Current Assignee: Cardiac Intelligence Corp (Boston Scientific Corporation)
• Original Assignee: Cardiac Intelligence Corp (Boston Scientific Corporation)
• Inventors: Bardy, Gust H.
• Primary Examiner(s): EVANISKO, GEORGE ROBERT
• Application Number:
  US09/441,405
• Time in Patent Office: 1,015 Days
• Field of Search: 600/300, 600/301, 600/513, 600/483, 128/720, 128/923-925
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61N 1/3627 for treating a mechanical deficiency of the heart, e.g. congestive heart failure or cardiomyopathy
• CPC Class Codes: A61N 1/37282 characterised by communication with experts in remote locations using a network
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• 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: Y10S 128/923 by comparison of patient data to other data

Abstract

An automated collection and analysis patient care system and method for ordering and prioritizing multiple health disorders to identify an index disorder is described. A plurality of monitoring sets are retrieved from a database. Each of the monitoring sets include stored measures relating to patient information recorded and derived on a substantially continuous basis. A patient status change is determined by comparing at least one stored measure from each of the monitoring sets to at least one other stored measure with both stored measures relating to the same type of patient information. Each patient status change is ordered in temporal sequence from least recent to most recent. A plurality of health disorder candidates categorized by quantifiable physiological measures of pathophysiologies indicative of each respective health disorder are evaluated and the health disorder candidate with the pathophysiology most closely matching those patient status changes which occurred least recently is identified.

Claims

1. An automated system for ordering and prioritizing multiple health disorders to identify an index disorder, comprising:

a database for storing a plurality of monitoring sets, each monitoring set comprising measures relating to patient information previously recorded and derived on a substantially continuous basis;

a comparison module determining patient status changes by comparing at least one stored measure from each of the monitoring sets to at least one other stored measure from another of the monitoring sets with both stored measures relating to the same type of patient information; and

an analysis module ordering each patient status change in temporal sequence from least recent to most recent and for categorizing a plurality of health disorder candidates by quantifiable physiological measures of pathophysiologies indicative of each respective health disorder and evaluating the health disorder candidates, and identifying the health disorder candidate having the pathophysiology substantially corresponding to the patient status changes which occurred substantially least recently as the index disorder.

2. An automated system according to claim 1, further comprising:

an adjustable time window defined for the patient information; and

the comparison module comparing the at least one stored measure to at least one other stored measure which was previously recorded within the adjustable time window.

3. An automated system according to claim 2, wherein the adjustable time window further comprises an upper bound relating to at least one of the health disorder candidates.

4. An automated system according to claim 1, further comprising:

the analysis module identifying the health disorder candidates having pathophysiologies substantially corresponding to the patient status changes which occurred recently.

5. An automated system according to claim 1, further comprising:

a symptomatic event ordering set comprising a plurality of previously related quantifiable physiological measures for one of the health disorder candidates; and

the analysis module evaluating each quantifiable physiological measure in the symptomatic event ordering set responsive to a change in at least one of the quantifiable physiological measures.

6. An automated system according to claim 1, further comprising:

a database module periodically receiving one of the monitoring set for an individual patient, at least one of the measures in the monitoring set having been previously recorded by at least one of an implantable medical device and an external medical device and storing the received monitoring set in the database as part of a patient care record for the individual patient.

7. An automated system according to claim 1, further comprising:

a sequencing module prioritizing the patient status changes in accordance with a pre-determined ordering; and

the analysis module comparing the patient status changes having a higher priority which occurred least recently before the patient status changes having a lower priority.

8. An automated system according to claim 1, further comprising:

the database for storing a plurality of quality of life measures;

the comparison module determining a patient subjective changes by comparing at least one quality of life measure to at least one other quality of life measure; and

the analysis module ordering each patient subjective change in temporal sequence from least recent to most recent.

9. An automated system according to claim 8, further comprising:

the sequencing module prioritizing the patient status changes in accordance with a pre-determined ordering based on a substantially least recent patient subjective change.

10. An automated system according to claim 8, further comprising:

the analysis module correlating the identified health disorder candidate with each patient subjective change.

11. An automated system according to claim 1, further comprising:

a set of stickiness indicators for corresponding types of patient information, each stickiness indicator corresponding to a temporal limit related to patient diagnosis or treatment;

the comparison module comparing a time span occurring between the patient status changes for each stored measure to the stickiness indicator relating to the same type of patient information as the stored measure being compared; and

the analysis module determining a revised program of patient diagnosis or treatment responsive to the patient status changes occurring subsequent to a time span exceeding the stickiness indicator.

12. An automated system according to claim 1, further comprising:

a database module retrieving the plurality of monitoring sets from the database as one of a patient care record for an individual patient, a peer group, and a overall patient population.

13. An automated system according to claim 1, further comprising:

a reference baseline comprising measures stored in the database, each measure relating to patient information stored during an initial time period and comprise either medical device measures or derived measures calculable therefrom; and

a database module obtaining at least one of the measures and one other of the stored measures from the reference baseline.

14. An automated system according to claim 1, wherein the plurality of health disorders comprise congestive heart failure, myocardial ischemia, respiratory insufficiency, and atrial fibrillation, the system further comprising:

an indicator threshold corresponding to a quantifiable physiological measure of a pathophysiology indicative of one of congestive heart failure, myocardial ischemia, respiratory insufficiency, and atrial fibrillation; and

the analysis module testing each patient status change against an indicator threshold corresponding to the same type of patient information as the stored measures which were compared.

15. A method for ordering and prioritizing multiple health disorders to identify an index disorder for use in an automated collection and analysis patient care system, comprising:

storing a plurality of monitoring sets into a database, each monitoring set comprising measures relating to patient information previously recorded and derived on a substantially continuous basis;

determining patient status changes by comparing at least one stored measure from each of the monitoring sets to at least one other stored measure from another of the monitoring sets with both stored measures relating to the same type of patient information;

ordering each patient status change in temporal sequence from least recent to most recent;

categorizing a plurality of health disorder candidates by quantifiable physiological measures of pathophysiologies indicative of each respective health disorder; and

evaluating the health disorder candidates and identifying the health disorder candidate having the pathophysiology substantially corresponding to the patient status changes which occurred substantially least recently as the index disorder.

16. A method according to claim 15, the operation of determining a patient status change further comprising:

defining an adjustable time window for the patient information; and

comparing the at least one stored measure to at least one other stored measure which was previously recorded within the adjustable time window.

17. A method according to claim 16, wherein the adjustable time window further comprises an upper bound relating to at least one of the health disorder candidates.

18. A method according to claim 15, further comprising:

identifying the health disorder candidates having pathophysiologies substantially corresponding to the patient status changes which occurred recently.

19. A method according to claim 15, further comprising:

categorizing a plurality of previously related quantifiable physiological measures for one of the health disorder candidates into a symptomatic event ordering set; and

evaluating each quantifiable physiological measure in the symptomatic event ordering set responsive to a change in at least one of the quantifiable physiological measures.

20. A method according to claim 15, further comprising:

periodically receiving one of the monitoring sets for an individual patient, at least one of the stored measures in the monitoring set having been previously recorded by at least one of an implantable medical device and an external medical device; and

storing the received monitoring set in the database as part of a patient care record for the individual patient.

21. A method according to claim 15, further comprising:

prioritizing the patient status changes in accordance with a pre-determined ordering; and

comparing the patient status changes having a higher priority which occurred least recently before the patient status changes having a lower priority.

22. A method according to claim 15, further comprising:

storing a plurality of quality of life measures;

determining patient subjective changes by comparing at least one quality of life measure to at least one other quality of life measure; and

ordering each patient subjective change in temporal sequence from least recent to most recent.

23. A method according to claim 22, further comprising:

prioritizing the patient status changes in accordance with a predetermined ordering based on a substantially least recent patient subjective change.

24. A method according to claim 22, further comprising:

correlating the identified health disorder candidate with each patient subjective change.

25. A method according to claim 15, further comprising:

defining a set of stickiness indicators for corresponding types of patient information, each stickiness indicator corresponding to a temporal limit related to patient diagnosis or treatment;

comparing a time span occurring between the patient status changes for each stored measure to the stickiness indicator relating to the same type of patient information as the stored measure being compared; and

determining a revised program of patient diagnosis or treatment responsive to the patient status changes occurring subsequent to a time span exceeding the stickiness indicator.

26. A method according to claim 15, further comprising:

retrieving the plurality of monitoring sets from the database as one of a patient care record for an individual patient, a peer group, and a overall patient population.

27. A method according to claim 15, further comprising:

storing a reference baseline comprising measures into the database, which each measure relating to patient information stored during an initial time period and comprise either medical device measures or derived measures calculable therefrom; and

obtaining at least one of the measures and one other of the measures from the reference baseline.

28. A method according to claim 15, wherein the plurality of health disorders comprise congestive heart failure, myocardial ischemia, respiratory insufficiency, and atrial fibrillation, the method further comprising:

defining an indicator threshold corresponding to a quantifiable physiological measure of a pathophysiology indicative of one of congestive heart failure, myocardial ischemia, respiratory insufficiency, and atrial fibrillation; and

testing each patient status change against an indicator threshold corresponding to the same type of patient information as the stored measures which were compared.

29. A computer-readable device having a storage medium holding code for ordering and prioritizing multiple health disorders to identify an index disorder for use in an automated collection and analysis patient care system, comprising:

code for operatively storing a plurality of monitoring sets into a database, each monitoring set comprising measures relating to patient information previously recorded and derived on a substantially continuous basis;

code for operatively determining patient status changes by comparing at least one stored measure from each of the monitoring sets to at least one other stored measure from another of the monitoring sets with both stored measures relating to the same type of patient information;

code for operatively ordering each patient status change in temporal sequence from least recent to most recent;

code for operatively categorizing a plurality of health disorder candidates by quantifiable physiological measures of pathophysiologies indicative of each respective health disorder; and

code for operatively evaluating the health disorder candidates and identifying the health disorder candidates having the pathophysiology substantially corresponding to the patient status changes which occurred substantially least recently as the index disorder.

30. A storage medium according to claim 29, the operation of determining a patient status change further comprising:

code for operatively defining an adjustable time window for the patient information; and

code for operatively comparing the at least one stored measure to at least one other stored measure which was previously recorded within the adjustable time window.

31. A storage medium according to claim 29, further comprising:

code for operatively identifying the health disorder candidates having pathophysiologies substantially corresponding to the patient status changes which occurred recently.

32. A storage medium according to claim 29, further comprising:

code for operatively categorizing a plurality of related quantifiable physiological measures for one such health disorder into a symptomatic event ordering set; and

code for operatively evaluating each such quantifiable physiological measure in the symptomatic event ordering set responsive to a change in at least one such quantifiable physiological measure.

33. A storage medium according to claim 29, further comprising:

code for operatively periodically receiving a monitoring set for an individual patient, at least one stored measure in the monitoring set having been recorded by at least one of a medical device adapted to be implanted in an individual patient and an external medical device proximal to the individual patient when the device measures are recorded; and

code for operatively storing the received monitoring set in the database as part of a patient care record for the individual patient.

34. A storage medium according to claim 29, further comprising:

code for operatively prioritizing the patient status changes in accordance with a pre-determined ordering; and

code for operatively comparing the patient status changes having a higher priority which occurred least recently before the patient status changes having a lower priority.

35. A storage medium according to claim 29, further comprising:

code for operatively storing a plurality of quality of life measures;

code for operatively determining patient subjective changes by comparing at least one quality of life measure to at least one other quality of life measure; and

code for operatively ordering each patient subjective change in temporal sequence from least recent to most recent.

36. A storage medium according to claim 35, further comprising:

code for operatively-prioritizing the patient status changes in accordance with a pre-determined ordering based on a substantially least recent patient subjective change.

37. A storage medium according to claim 35, further comprising:

code for operatively correlating the identified health disorder candidate with each patient subjective change.

38. A storage medium according to claim 29, further comprising:

code for operatively defining a set of stickiness indicators for corresponding types of patient information, each stickiness indicator corresponding to a temporal limit related to patient diagnosis or treatment;

code for operatively comparing a time span occurring between the patient status changes for each stored measure to the stickiness indicator relating to the same type of patient information as the stored measure being compared; and

code for operatively determining a revised program of patient diagnosis or treatment responsive to the patient status changes occurring subsequent to a time span exceeding the stickiness indicator.

39. A storage medium according to claim 29, further comprising:

code for operatively retrieving the plurality of monitoring sets from the database as one of a patient care record for an individual patient, a peer group, and a overall patient population.

40. A storage medium according to claim 29, further comprising:

code for operatively storing a reference baseline comprising measures into the database, each measure relating to patient information stored during an initial time period and comprise either medical device measures or derived measures calculable therefrom; and

code for operatively obtaining at least one of the measures and one other of the measures from the reference baseline.