SYSTEM AND METHOD FOR SUPPORTING HEALTH MANAGEMENT SERVICES

• US 20140357961A1
• Filed: 06/14/2013
• Published: 12/04/2014
• Est. Priority Date: 06/04/2013
• Status: Active Grant

• Current Assignee: Purdue Pharma L.P.
• Original Assignee: Purdue Pharma L.P.
• Inventors: Meltzer, Brian, Natarajan, Sayee
• Granted Patent: US 9,955,869 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• 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 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4833 Assessment of subject's compliance to treatment
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/747 in case of emergency, i.e. alerting emergency services
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A method in support of health management services acts upon active and passive data, in which the active data is communicated by a patient or healthcare professional and in which the passive data is detected by at least one sensor detectably coupled to the patient. These data are correlated with each other and if a predefined correlation is not met, further data can be solicited, patient-specific queries can be generated, alerts can be communicated, or a combination of these can be done in embodiments of the invention. Any Irregularity or trend in the data can be identified and processed in embodiments of the invention. Also in some embodiments, these data can be used in connection with intelligent, machine-based decisions to send communications concerning the provision of further healthcare resources to patients, such as in view of their relative acuity rank. Systems can be constructed to implement the methods described herein.

Claims

1. A method in support of health management services for a patient, comprising:

receiving, at a server having a processor and memory, passive data detected by at least one patient sensor that is detectably coupled to the patient;

generating, by code executing in the processor, a first patient-specific query for delivery to the patient;

receiving, at the server, active data provided by the patient responsive to the first patient-specific query;

correlating, using code executing in the processor, the received active data with the received passive data; and

in response to a failure of the correlation to meet a predefined correlation threshold, soliciting at least one of further active data and further passive data using code executing in the processor.

2. The method of claim 1, wherein the soliciting step comprises:

at least one of regenerating the first patient-specific query and generating a second patient-specific query, for delivery to the patient.

3. The method of claim 1, further comprising:

in response to at least one of soliciting the further active data and soliciting the further passive data, receiving at least one of the further active data and the further passive data; and

repeating the step of correlating, using code executing in the processor, the received active data with the received passive data.

4. The method of claim 1, further comprising:

upon the correlation failing to meet the predefined correlation threshold, generating a notification reflecting the failure; and

providing the notification to at least one of the patient, a healthcare professional, and a third-party.

5. The method of claim 1, further comprising:

upon the processor successfully completing the correlation to meet the predefined correlation threshold, generating a notification reflecting a successful correlation of the received active data with the received passive data; and

providing the notification to at least one of the patient, a healthcare professional, and a third-party.

6. The method of claim 1, further comprising:

identifying, by code executing in the processor, any predefined irregularities in the received active data and the received passive data; and

in response to the identification of at least one predefined irregularity in the received active data or in the received passive data, generating a second patient-specific query for delivery to the patient.

7. The method of claim 6, further comprising:

upon at least one of the processor detecting the at least one irregularity and the correlation failing to meet the predefined correlation threshold, generating a notification reflecting the irregularity or failure; and

providing the notification to at least one of the patient, a healthcare professional, and a third-party.

8. The method of claim 6, further comprising:

upon the processor identifying an absence of irregularities in the received active data and the received passive data and successfully completing the correlation to meet the predefined correlation threshold, generating a notification reflecting an absence of irregularities and a successful correlation of the received active data with the received passive data; and

providing the notification to at least one of the patient, a healthcare professional, and a third-party.

9. The method of claim 1, further comprising:

storing in the memory at least one of the received active data, the received passive data, and first correlation data reflective of data generated by the correlation of the received active data with the received passive data;

anonymizing the at least one of the received active data, the received passive data, and the first correlation data;

correlating the anonymized at least one of the received active data, the received passive data, and the first correlation data of the patient with other anonymized data of at least one other patient;

generating second correlation data reflective of data generated by the correlation of the anonymized data of the patient with the anonymized data of the at least one other patient; and

presenting the second correlation data to at least one of the patient, a healthcare professional, and a third-party.

10. The method of claim 5, further comprising:

receiving healthcare professional-generated data responsive to providing the notification to the healthcare professional;

wherein the healthcare professional-generated data represents at least one of a diagnosis, a treatment plan, a healthcare professional-query, and an observation relating to the patient;

storing in the memory the healthcare professional-generated data and at least one of the received active data, the received passive data, and first correlation data reflective of data generated by the correlation of the received active data with the received passive data;

anonymizing the healthcare professional-generated data and the at least one of the received active data, the received passive data, and the first correlation data;

associating the anonymized healthcare professional-generated data and the anonymized at least one of the received active data, the received passive data, and the first correlation data;

correlating the anonymized healthcare professional-generated data with other anonymized healthcare professional-generated data of at least one other healthcare professional;

generating anonymized healthcare professional-correlation data reflective of data generated by the correlation of the anonymized healthcare professional-generated data of the healthcare professional with the other anonymized healthcare professional-generated data of the at least one other healthcare professional; and

presenting the anonymized healthcare professional-correlation data to at least one of the patient, the healthcare professional, the at least one other healthcare professional, an accountable care organization to which the healthcare professional belongs, and a third-party payor.

11. The method of claim 5, further comprising:

determining based on predefined scheduling criteria whether to schedule a patient appointment with the healthcare professional;

upon a determination not to schedule a patient appointment with the healthcare professional, generating a healthcare professional-query for delivery to the patient; and

upon a determination to schedule a patient appointment with the healthcare professional;

generating a critical-level indicator associated with the patient;

receiving patient-calendar information associated with the patient;

coordinating the patient-calendar information with received healthcare-professional scheduling information responsive to the critical-level indicator;

wherein a later-in-time patient with a higher associated critical-level indicator is prioritized over an earlier-in-time patient with a lower associated critical-level indicator; and

determining an agreed-upon appointment.

12. The method of claim 1, wherein the step of generating the first patient-specific query comprises:

selecting and providing the first patient-specific query for delivery to the patient; and

communicating the first patient-specific query over a network connection to a device of the patient.

13. A method in support of health management services, comprising:

receiving, at a server having a processor and memory, passive data detected by at least one sensor that is detectably coupled to a patient;

generating, by code executing in the processor, a first patient-specific query;

receiving, at the server, active data provided by the patient responsive to the first patient-specific query;

correlating, using code executing in the processor, the received active data with the received passive data;

in response to a failure of the correlation to meet a predefined correlation threshold, generating an alert using the server configured by code executing in the processor; and

communicating at least one of the first patient-specific query and the alert over a network connection to a device of the patient.

14. The method of claim 13, further comprising:

identifying, by code executing in the processor, any predefined irregularities in the received active data and the received passive data;

in response to the identification of at least one predefined irregularity in the received active data or in the received passive data, generating, using the server configured by code executing in the processor, a second patient-specific query for delivery to the patient.

16. The system as in claim 14 further configured to:

identify any predefined irregularities in the received active data and the received passive data; and

in response to the identification of at least one predefined irregularity in the received active data or in the received passive data, generate a second patient-specific query.

17. The system as in claim 14, wherein the network connection to the device comprises a connection which is in communication with the at least one passive sensor.

15. A system in support of health management services for a patient having at least one passive sensor detectably coupled to the patient to gather data therefrom, comprising:

a server having a processor and memory;

a plurality of code sets that are executable in the processor and which, when executed, configure the processor to;

receive passive data detected by at least one sensor that is detectably coupled to the patient;

generate a first patient-specific query;

receive active data provided by the patient responsive to the first patient-specific query;

correlate the received active data with the received passive data;

in response to a failure of the correlation to meet a predefined correlation threshold, solicit at least one of further active data and further passive data; and

a network connection configured to communicate the first patient-specific query over a network to a device of the patient.

18. A method in support of analyzing health management services provided by a plurality of healthcare professionals who are affiliated with one or more healthcare networks, comprising:

correlating, using code executing in a processor, separate sets of data received from each of a plurality of patients, the data comprising active data which is provided responsive to data queries and passive data provided by an electronic device associated with respective patients;

mapping the correlations to one or more symptoms using code executing in the processor;

storing the correlations in a database in association with each patient and in association with at least one healthcare professional;

identifying, using code executing in the processor, a set of patients among the plurality of patients having a trend of changes in the correlations for a particular symptom or any failure of the correlation to meet a predefined correlation threshold for the particular symptom;

ranking the set of patients in order of most acute to least acute using code executing in the processor; and

communicating over a distributed computer network to either the healthcare professional or the healthcare network affiliated with the healthcare professional that further resources are to be provided to at least a portion of the ranked patients based on the ranking.

19. The method of claim 18, further comprising scheduling at least one intervention by the healthcare professional with the patient after the communicating step.