Remote health application for the optimization of remote site visit frequency

• US 7,711,582 B2
• Filed: 04/17/2006
• Issued: 05/04/2010
• Est. Priority Date: 04/17/2006
• Status: Expired due to Fees

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Duckert, David W., Friedman, Bruce A.
• Primary Examiner(s): Koppikar; Vivek D
• Application Number:
  US11/279,935
• Publication Number:
  US 20070255596A1
• Time in Patent Office: 1,478 Days
• Field of Search: 705 2- 4, 600300-301
• US Class Current: 705/3
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• 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 50/30 for calculating health indices; for individual health risk assessment

Abstract

A system and method for the optimization of scheduling visits by a clinician to a plurality of remotely located patients. A plurality of predefined or clinician specified risk factors are combined with patient data with a home visit interval algorithm to specify a visit interval for each patient. This interval is used with a calendar with other information regarding past and future scheduled visits to determine the optimal date for the next visit to the patient by the clinician. The patient risk factors may be weighted to place more emphasis on specific factors, thus allowing for the tailoring of the system to meet the needs of an individual patient.

Claims

1. A system for scheduling clinical visits to a remotely located patient, the system comprising:

a plurality of patient risk factors stored on a risk factor database, the plurality of patient risk factors each comprising a default value wherein the default value is a weight that enables the emphasis of some patient risk factors over others in determining the visit interval;

patient data stored on a patient database;

a visit interval algorithm operating on a computer processor connected to the risk factor database and the patient database, the visit interval algorithm upon execution by the computer processor derives a visit interval from the plurality of patient risk factors and the patient data; and

a calendar operating on the computer processor, the calendar comprising a previous patient visit and the calendar schedules a patient visit for a date that is the visit interval from the previous patient visit;

wherein the default values are modified over time using fuzzy logic or a neural network, in response to collected patient data.

2. The system of claim 1 wherein the visit date information further comprises any scheduled contact with a healthcare provider involved with the patient'"'"'s treatment.

3. The system of claim 1 wherein the visit interval algorithm comprises institutionally defined controls.

4. The system of claim 3 wherein the institutionally defined controls are maximum visit intervals.

9. The system of claim 1 wherein the patient visit scheduled by the calendar replaces a previously scheduled future patient visit.

10. The system of claim 9 further comprising a communication device associated with the patient, the communication device transmits measured patient data to the processor.

11. The system of claim 10 wherein the processor produces an indication of the scheduled patient visit and the communication device further receives the indication of the scheduled patient visit.

12. The system of claim 10 wherein upon the communication device transmitting the measured patient data to the processor, the visit interval algorithm calculates a new visit interval and the calendar replaces the future patient visit with a new patient visit based on the new visit interval.

16. The system of claim 1 wherein the default values are modified over time using fuzzy logic.

17. The system of claim 1 wherein the default values are modified over time using a neural network.

5. A system for real-time scheduling of clinician visits to a patient receiving care at a remote location, the system comprising:

a communications device associated with the patient, the communications device transmitting patient physiological data from the patient to a processor in real time;

a plurality of risk factors stored in a risk factor database connected to the processor, each of the plurality of risk factors comprising a default value wherein the default value is a weight that enables the emphasis of some patient risk factors over others;

a patient database storing patient medical history information connected to the processor;

a visit interval algorithm stored on a computer readable medium and executed by the processor, the visit interval algorithm applying the patient physiological data and the patient medical history information to the plurality of risk factors to determine a visit interval; and

a calendar comprising a past patient visit date, the calendar receives the visit interval from the processor and schedules a patient visit for a date that is the visit interval from the past patient visit date;

wherein the default values are modified over time based upon the patient physiological data using fuzzy logic or a neural network.

13. The system of claim 5 wherein upon the communications device transmitting patient data to the processor, the visit interval algorithm calculates a new visit interval and the calendar replaces a future patient visit with a new patient visit based on the new visit interval.

18. The system of claim 5 wherein the default values are modified over time using fuzzy logic.

19. The system of claim 5 wherein the default values are modified over time using a neural network.

6. A method of optimizing the care provided by a clinician to a plurality of remotely located patients with treatment and care needs, the method comprising the steps of:

providing each patient with an associated communications device;

transmitting patient data via the communications device to a computer workstation comprising a processor;

operating the processor to execute a remote health application stored on a computer readable medium, which upon execution performs the steps of;

comparing at least one patient risk factor, the at least one patient risk factor having a default value, to the patient data to determine a patient visit interval;

deriving a patient visit date by adding the patient visit interval to a past patient visit date;

scheduling the patient visit date;

notifying the patient of the scheduled patient visit date via the communications device; and

modifying the default value of the at least one patient risk factor in response to the patient data using fuzzy logic or a neural network;

wherein the default value is a weight that enables the emphasis of some patient risk factors over others in determining the patient visit interval.

7. The method of claim 6 wherein the patient data transmitted via the communications device comprises linguistic communication and physiological patient data.

8. The method of claim 7 wherein the linguistic communication provides the clinician with qualitative information regarding the patient'"'"'s condition, the patient data comprising the qualitative information.

14. The method of claim 6 further comprising operating the processor to update the patient visit interval and updating the scheduled patient visit date each time that patient data is transmitted to the processor from the communications device.

15. The method of claim 6 further adjusting a scheduled visit date of a first patient to a scheduled visit date of a second patient based upon the geographical proximity of the first patient to the second patient.

20. The method of claim 6 wherein the step of modifying uses fuzzy logic.

21. The method of claim 6 wherein the step of modifying uses a neural network.