System for using patient data combined with database data to predict and report outcomes

• US 10,573,415 B2
• Filed: 04/21/2014
• Issued: 02/25/2020
• Est. Priority Date: 04/21/2014
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Patel, Amisha S., Riff, Kenneth M., Mongeon, Luc R.
• Primary Examiner(s): Ng, Jonathan
• Assistant Examiner(s): Reichert, Rachelle L
• Application Number:
  US14/257,232
• Publication Number:
  US 20150302178A1
• Time in Patent Office: 2,136 Days
• Field of Search: None
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• 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

A system and associated method receives, by a database coupled to a communication network, patient medical data from multiple data sources including data retrieved from implantable medical devices implanted in patients. A processor accesses the database to generate a dataset from the medical data having at least one data characteristic matching a corresponding data characteristic of a patient group of at least one patient. At least one subset of the dataset is identified that had a therapy intervention subsequent to a time point that the subset had the matching data characteristic(s). An outcome of the subset is determined and a predictive outcome for the patient group is produced based on the outcome of at least one subset.

Claims

1. A system, comprising:

a database coupled to a communication network and configured to store medical data for a plurality of patients received via the network from a plurality of data sources comprising data retrieved from implantable medical devices implanted in the plurality of patients;

a processor coupled to the database for accessing the stored medical data and configured to;

receive, from a remote computer, a request for a report of a predictive outcome of a therapy intervention for a patient group of at least one patient, the therapy intervention comprising a change in an operating parameter of an automated medical device, and, in response to the request;

generate a dataset from the stored medical data having at least one data characteristic matching a corresponding data characteristic of the patient group;

determine from the dataset at least one subset that had the therapy intervention take place subsequent to a time point that the at least one subset had the at least one matching data characteristic;

determine an outcome of the at least one subset;

produce the predictive outcome for the patient group based on the outcome of the at least one subset; and

transmit the report of the predictive outcome to the remote computer; and

automatically, in response to new data received by the database, produce an updated predictive outcome of the therapy intervention for the patient group and transmit an updated report of the updated predictive outcome to the remote computer.

2. The system of claim 1, wherein the outcome comprises a change in the performance of an implantable medical device.

3. The system of claim 1, wherein the outcome comprises a cost of medical treatment.

4. The system of claim 1, wherein the processor is further configured to:

generate a plurality of mathematical models of the data stored in the database; and

compare data of the patient group to the models to identify a dataset having the matching characteristic to the patient group.

5. The system of claim 1, wherein the processor is configured to:

determine a change in the at least one data characteristic of the patient group in response to the new data;

generate an updated dataset in response to determining the change; and

produce the updated predictive outcome in response to the updated dataset.

6. The system of claim 1, wherein the processor is configured to:

determine a change in an actual outcome of the dataset in response to the new data; and

produce the updated predictive outcome in response to the change in the actual outcome.

7. The system of claim 1, wherein the processor is further configured to:

determine from the dataset a subset having an optimal outcome;

determine a therapy intervention difference between the patient group data and the subset;

report an action to reduce the therapy intervention difference; and

report a predictive outcome expected if the reported action is taken.

8. The system of claim 7, wherein the processor is further configured to:

compute a predicted difference in a monetary cost of medical care if the reported action is taken; and

report the predicted change in the monetary cost of medical care.

9. The system of claim 1, wherein the outcome of the therapy intervention comprises at least one of a side-effect frequency, a hospitalization frequency, or a status of an atrial fibrillation (AF) burden of the patient group.

10. The system of claim 1, wherein the outcome of the therapy intervention comprises a change in a frequency of shocks delivered by the automated medical device.

11. The system of claim 1, wherein the change in the operating parameter of the automated medical device comprises a programming change made to the automated medical device.

12. A method, comprising:

receiving, by a database coupled to a communication network, medical data for a plurality of patients from a plurality of data sources comprising data retrieved from implantable medical devices implanted in the plurality of patients;

receiving, from a remote computer, a request for a report of a predictive outcome of a therapy intervention for a patient group of at least one patient, the therapy intervention comprising a change in an operating parameter of an automated medical device, and, in response to the request;

generating by a processor coupled to the database a dataset from the medical data having at least one data characteristic matching a corresponding data characteristic of the patient group of at least one patient;

determining from the dataset at least one subset that had the therapy intervention subsequent to a time point that the at least one subset had the at least one matching data characteristic;

determining an outcome of the at least one subset;

producing the predictive outcome for the patient group based on the outcome of the at least one subset; and

transmitting the report of the predictive outcome to the remote computer; and

automatically, in response to new data received by the database, producing an updated outcome of the therapy intervention for the patient group, and transmitting an updated report of the updated predictive outcome to the remote computer.

13. The method of claim 12, wherein the outcome comprises a change in the performance of an implantable medical device.

14. The method of claim 12, wherein the outcome comprises a cost of medical treatment.

15. The method of claim 12, further comprising:

generating a plurality of mathematical models of the data stored in the database; and

comparing data of the patient group to the plurality of models to identify the dataset having the matching characteristic to the patient group.

16. The method of claim 12, further comprising:

determining a change in the at least one data characteristic of the patient group in response to the new data;

generating an updated dataset in response to determining the change; and

producing the updated predictive outcome in response to the updated dataset.

17. The method of claim 12, further comprising:

determining a change in an actual outcome of the dataset in response to the new data; and

producing the updated predictive outcome in response to the change in the actual outcome.

18. The method of claim 12, further comprising:

determining from the dataset a subset having an optimal outcome;

determining a therapy difference between the patient group data and the subset;

reporting an action to reduce the therapy difference; and

reporting a predictive outcome expected if the reported action is taken.

19. The method of claim 18, further comprising:

computing a predicted difference in a monetary cost of medical care if the reported action is taken; and

reporting the predicted change in the monetary cost of medical care.

20. The method of claim 12, wherein the outcome of the therapy intervention comprises at least one of a side-effect frequency, a hospitalization frequency, or a status of an atrial fibrillation (AF) burden of the patient group.

21. The method of claim 12, wherein the outcome of the therapy intervention comprises a change in a frequency of shocks delivered by the automated medical device.

22. The method of claim 12, wherein the change in the operating parameter of the automated medical device comprises a programming change made to the automated medical device.

23. A system, comprising:

means for receiving medical data for a plurality of patients from a plurality of data sources comprising data retrieved from implantable medical devices implanted in the plurality of patients;

means for storing the received data;

means for receiving, from a remote computer, a request for a report of a predictive outcome of a therapy intervention for a patient group of at least one patient, the therapy intervention comprising a change in an operating parameter of an automated medical device, and, in response to the request;

generating a dataset from the medical data having at least one data characteristic matching a corresponding data characteristic of the patient group of at least one patient;

determining from the dataset at least one subset that had the therapy intervention subsequent to a time point that the at least one subset had the at least one matching data characteristic;

determining an outcome of the at least one subset;

producing the predictive outcome for the patient group based on the outcome of the at least one subset; and

transmitting the report of the predictive outcome to the remote computer; and

means for automatically, in response to new data received by the database, producing an updated outcome of the therapy intervention for the patient group, and transmitting an updated report of the updated predictive outcome to the remote computer.

24. A non-transitory computer readable storage medium storing a set of instructions to cause a system to:

receive by a database coupled to a communication network medical data for a plurality of patients from a plurality of data sources comprising data retrieved from implantable medical devices implanted in the plurality of patients;

receive, from a remote computer, a request for a report of a predictive outcome of a therapy intervention for a patient group of at least one patient, the therapy intervention comprising a change in an operating parameter of an automated medical device, and, in response to the request;

generate a dataset from the medical data having at least one data characteristic matching a corresponding data characteristic of the patient group of at least one patient;

determine from the dataset at least one subset that had the therapy intervention subsequent to a time point that the at least one subset had the at least one matching data characteristic;

determine an outcome of the at least one subset;

produce the predictive outcome for the patient group based on the outcome of the at least one subset; and

transmit the report of the predictive outcome to a remote computer; and

automatically, in response to new data received by the database, produce an updated predictive outcome of the therapy intervention for the patient group and transmit an updated report of the updated predictive outcome to the remote computer.