System and method for prioritizing medical conditions

• US 8,369,937 B2
• Filed: 12/06/2011
• Issued: 02/05/2013
• Est. Priority Date: 11/16/1999
• Status: Expired due to Fees

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Bardy, Gust H.
• Primary Examiner(s): EVANISKO, GEORGE ROBERT
• Application Number:
  US13/312,174
• Publication Number:
  US 20120078064A1
• Time in Patent Office: 427 Days
• Field of Search: 600/301, 600/300, 600/513, 600515-518, 600/483, 128923-925
• US Class Current: 600/513
• 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: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02 Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• 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 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A system for ordering and prioritizing multiple health disorders for automated remote patient care is presented. A database maintains information for an individual patient by organizing monitoring sets in a database, and measures relating to patient information previously recorded and derived on a substantially continuous basis into a monitoring set in the database. A server retrieving and processing the monitoring includes a comparison module comparing stored measures from each of the monitoring sets to other stored measures 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 and categorizing health disorder candidates by quantifiable physiological measures, 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.

Claims

1. A process for forming an index disorder for use in automated patient care, comprising:

storing sets of device measures regularly recorded by a medical device for a patient under automated patient care, a set of reference baseline measures recorded during an initial observation period, and indicator thresholds corresponding to quantifiable physiological measures of pathophysiologies; and

retrieving the device measures and the reference baseline measures from the database;

iteratively processing the device measures and the reference baseline measures with the indicator thresholds and identifying multiple near-simultaneous disorders from said iterative processing, wherein each iterative loop of the iterative process comprises analyzing the device measures and the reference baseline measures for changes occurring over time; and

analyzing and ordering the changes and the multiple-near simultaneous disorders occurring over time; and

identifying the index disorder based on said analyzing and ordering.

2. A process according to claim 1, further comprising:

storing processed raw and physiological measures; and

comparing a plurality of the processed raw and physiological measures to quantify one or more changes in pathophysiology, and to order the pathophysiology changes in temporal sequence.

3. A process according to claim 1, further comprising:

categorizing health disorder candidates by pathophysiology; and

identifying the health disorder candidate having a pathophysiology substantially comparable to a change in pathophysiology that occurred either substantially least or most recently.

4. A process according to claim 1, further comprising:

storing processed raw and physiological measures; and

comparing at least one of the processed raw and physiological measures to at least one other of the processed raw and physiological measures that were previously recorded.

5. A process according to claim 1, further comprising:

storing a plurality of previously-related pathophysiologies for at least one health disorder candidate;

sorting the plurality of previously-related pathophysiologies for at least one health disorder candidate into a symptomatic event ordering set; and

evaluating each pathophysiology in the symptomatic event ordering set in response to a change in the pathophysiology being evaluated.

6. A process according to claim 1, further comprising:

prioritizing pathophysiology changes using a predefined ordering, wherein the physiological changes have different priorities; and

comparing the pathophysiology changes having higher priorities that occurred least recently before the pathophysiology changes having lower priorities.

7. A process according to claim 1, further comprising tracking temporal changes in pathophysiology.

8. A process according to claim 1, wherein the indicator thresholds correspond to a pathophysiology indicative of at least one of congestive heart failure, myocardial ischemia, respiratory insufficiency, and atrial fibrillation health disorders, further comprising:

testing pathophysiology changes against the indicator thresholds to determine whether a change in pathophysiology has occurred.