Method and System For Active Patient Management

• US 20090125328A1
• Filed: 11/12/2007
• Published: 05/14/2009
• Est. Priority Date: 11/12/2007
• Status: Abandoned Application

• Current Assignee: Air Products and Chemicals Incorporated (Linde Plc)
• Original Assignee: Air Products and Chemicals Incorporated (Linde Plc)
• Inventors: Nevins, Sean Michael
• Application Number:
  US11/938,409
• Publication Number:
  US 20090125328A1
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Methods and systems for active patient management are provided. A central system can receive data about one or more patients from sources such as implantable medical devices within the patient, healthcare providers, pharmacies, and insurance entities. The system may automatically identify anomalous data or trends in the data, and automatically alert a healthcare provider associated with the patient. The alert may provide additional contextual information related to the alert data. Thus, the healthcare provider need not manually analyze patient data on a regular basis. The system also may perform predictive modeling to identify when a patient may need additional healthcare.

Claims

1. A method comprising:

receiving data describing a patient'"'"'s health condition from multiple patient data sources;

performing an analysis of the received data, the analysis using data from multiple patient data sources; and

providing a contextual alert to a healthcare provider in response to a result of the analysis, the contextual alert comprising an indication of a causal factor contributing to the alert.

2. The method of claim 1, wherein the performing an analysis of the received data includes identifying a potentially adverse event.

3. The method of claim 1, wherein the contextual alert includes a risk index.

4. The method of claim 3, wherein the causal factor is a primary contributor to the value of the risk index.

5. The method of claim 3, wherein the risk index indicates the likelihood that the patient will require hospitalization.

6. The method of claim 1, further comprising:

responsive to instruction received from the healthcare provider, sending new configuration data to a medical device associated with the patient.

7. A computer-readable storage medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform a method comprising:

receiving data describing a patient'"'"'s health condition from multiple patient data sources;

performing an analysis of the received data, the analysis using data from multiple patient data sources; and

providing a contextual alert to a healthcare provider in response to a result of the analysis, the contextual alert comprising an indication of a causal factor contributing to the alert.

8. The computer-readable storage medium of claim 7, wherein the performing an analysis of the received data includes identifying a potentially adverse event.

9. The computer-readable storage medium of claim 7, wherein the contextual alert includes a risk index.

10. The computer-readable storage medium of claim 9, wherein the causal factor is a primary contributor to the value of the risk index.

11. The computer-readable storage medium of claim 9, wherein the risk index indicates the likelihood that the patient will require hospitalization.

12. The computer-readable storage medium of claim 7, further comprising:

responsive to instruction received from the healthcare provider, sending new configuration data to a medical device associated with the patient.

13. A method comprising:

receiving data describing a patient'"'"'s health condition;

creating a predictive model of the patient'"'"'s condition based on the received data; and

providing a contextual alert to a healthcare provider in response to a prediction of the predictive model, the contextual alert comprising an indication of a causal factor contributing to the alert.

14. The method of claim 13, wherein the alert includes a risk index.

15. The method of claim 14, wherein the risk index indicates the likelihood that the patient will require hospitalization.

16. The method of claim 14, wherein the causal factor is a primary contributor to the value of the risk index.

17. A computer-readable storage medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform a method comprising:

receiving data describing a patient'"'"'s health condition;

creating a predictive model of the patient'"'"'s condition based on the received data; and

providing a contextual alert to a healthcare provider in response to a prediction of the predictive model, the contextual alert comprising an indication of a causal factor contributing to the alert.

18. The computer-readable storage medium of claim 17, wherein the alert includes a risk index.

19. The computer-readable storage medium of claim 18, wherein the risk index indicates the likelihood that the patient will require hospitalization.

20. The computer-readable storage medium of claim 18, wherein the causal factor is a primary contributor to the value of the risk index.

21. A system comprising:

a receiving unit to receive data describing a health condition of a patient from multiple patient data sources;

an analyzer to analyze the data received by the receiving unit and to compare results of the analysis to a set of conditions defining when a contextual alert should be sent, the contextual alert comprising an indication of a causal factor contributing to the alert; and

a communication output to send the contextual alert to a healthcare provider.

22. The system of claim 21, wherein the alert includes a risk index, and the causal factor is a primary contributor to the value of the risk index.

23. The system of claim 21, further comprising a communication link adapted to send new configuration data to a medical device associated with the patient.

24. The system of claim 21, the analyzer further to construct a predictive model based on the received data, the predictive model specifying the conditions defining when the contextual alert should be sent.

25. The system of claim 24, wherein the alert includes a risk index, and the causal factor is a primary contributor to the value of the risk index.