System and method for providing an on-demand real-time patient-specific data analysis computing platform

• US 10,381,114 B2
• Filed: 09/28/2017
• Issued: 08/13/2019
• Est. Priority Date: 04/26/2015
• Status: Active Grant

• Current Assignee: Inovalon, Inc. (Inovalon Holdings, Inc.)
• Original Assignee: Inovalon, Inc. (Inovalon Holdings, Inc.)
• Inventors: Dunleavy, Keith R.
• Primary Examiner(s): Najarian, Lena
• Application Number:
  US15/718,520
• Publication Number:
  US 20180018432A1
• Time in Patent Office: 684 Days
• Field of Search: None
• 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 computing platform configured to receive and process an on-demand real-time patient-specific data analysis order is provided. The computing platform can receive an order, determine the viability of the order, and then perform the desired analysis based on parameters provided within the order. As part of the analysis, the computing platform can mine one or more data sources to collect data relevant to the ordered diagnostic. Once the data is collected, the computing platform can analyze the data according to one or more pre-programmed algorithms. The selection of which algorithms to apply to the data set can be determined by the type of on-demand real-time patient-specific data analysis ordered. The on-demand real-time patient-specific data analysis in some examples can be ordered using an external ordering user interface.

Claims

1. A computer-implemented method comprising:

receiving, from a computing platform that does not already store a sufficient amount of patient-specific medical history data to perform a particular analysis of real-time, patient-specific medical history data for a particular patient and by a message hub of a data analysis system that includes (i) one or more servers that implement the message hub, (ii) a processing server, (iii) one or more servers that store profiles associated with different patients, (iv) a data lake that is in electronic communication with the processing server through one or more external network interfaces and that stores identified data and de-identified data on behalf of one or more third-party healthcare providers, (v) one or more servers that implement an analytics engine, (vi) one or more servers that implement a result generator, (vii) the computing platform that does not already store the sufficient amount of patient-specific medical history data to perform the particular analysis and that comprises an interface that is dedicated to interfacing with the data analysis system, and (viii) one or more servers that implement a data integration service for re-identifying the de-identified data, and for standardizing the identified data and the re-identified data, a request for the particular analysis of real-time, patient-specific medical history data for the particular patient;

determining, by the processing server of the data analysis system, that a particular profile that is associated with the particular patient indicates that a sufficient amount of the real-time, patient-specific medical history data is stored in the identified data or the de-identified data in the data lake for the analytics engine to perform the particular analysis;

in response to determining that the particular profile that is associated with the particular patient indicates that a sufficient amount of the real-time, patient-specific medical history data is stored in the identified data or the de-identified data in the data lake for the analytics engine to perform the particular analysis, obtaining, by the processing server of the data analysis system, the real-time, patient-specific medical history data that is stored in the identified data or the de-identified data in the data lake using a real-time, transactional data mining technique that obtains data items individually through the one or more external network interfaces in real-time and that is other than batch processing, rather than waiting for the data items to be provided through the one or more external network interfaces in one or more batches;

re-identifying, by the one or more servers that implement the data integration service, the de-identified data of the obtained real-time, patient-specific medical history data, and standardizing the identified data and the re-identified data of the obtained real-time, patient-specific medical history data;

performing, by the analytics engine of the data analysis system, the particular analysis based on the obtained, standardized, real-time, patient-specific medical history data for the particular patient;

generating, by the result generator of the data analysis system, a result of performing the requested analysis based on the obtained, standardized, real-time, patient-specific medical history data for the particular patient, then deleting the obtained, standardized, real-time, patient-specific medical history data for the particular patient; and

providing, by the message hub of the data analysis system, the result of performing the requested analysis, through the interface that is dedicated to interfacing with the data analysis system, for output on the computing platform.

2. The method of claim 1, wherein the particular analysis comprises a quality of care analysis that assesses a quality of care that the particular patient has received by a provider, and wherein the result of performing the analysis comprises an assessment of a quality of care of the particular patient and an indication of remedial steps that may be undertaken to bring the particular patient within a defined standard of care.

3. The method of claim 1, wherein the requested analysis comprises an analysis that assesses a potential current or future existence of, or a predicted, implication imposed by, a condition, and wherein the result of performing the analysis comprises a risk score for the condition.

4. The method of claim 1, wherein the requested analysis comprises a waste-avoidance analysis that assesses potentially unnecessary utilization of tests, and wherein the result of performing the analysis comprises an indication of one or more potentially unnecessary tests or treatments.

5. The method of claim 1, wherein the requested analysis comprises an eligibility analysis that assesses a user'"'"'s eligibility for various programs, and wherein the result of performing the analysis comprises a respective indication of eligibility or applicability for each of the various programs.

6. The method of claim 1, wherein the requested analysis comprises a risk analysis that assesses categories of care, or cost burdens, for a care model or a payment model.

7. The method of claim 1, wherein the request includes inclusion criteria that specifies specific sets of data stored on the data lake that are to be included in the analysis.

8. The method of claim 1, wherein the request includes exclusion criteria that specifies specific sets of data stored on the data lake that are to be excluded from the analysis.

9. The method of claim 1, wherein obtaining the patient-specific data that is stored in the data lake comprises:

obtaining one or more data items that are already at a first database of the data analysis system when the request is received.

10. The method of claim 1, wherein obtaining the patient-specific data that is stored in the data lake comprises:

obtaining one or more data items that are externally stored at an external data source when the request is received.

11. The method of claim 1, wherein the data analysis system is exposed as a web service.

12. The method of claim 1, comprising, after receiving the request, transmitting a secure socket layer (SSL) certificate from the message hub to an order processing architecture.

13. The method of claim 1, comprising, before determining that the particular profile that is associated with the particular patient indicates that the real-time, patient-specific medical history data that is stored in the data lake is sufficient to perform the requested analysis, determining, using an organization map, that a user is associated with an organization that authorizes the requested analysis.

14. The method of claim 1, wherein determining that the particular profile that is associated with the particular patient indicates that the real-time, patient-specific medical history data that is stored in the data lake is sufficient to perform the requested analysis comprises receiving a data including a Boolean flag that indicates that sufficient data exists.

21. The method of claim 1, wherein the computing platform implements a legacy order entry interface.

15. A data analysis system comprising (i) one or more servers that implement a message hub, (ii) a processing server, (iii) one or more servers that store profiles associated with different patients, (iv), a data lake that is in electronic communication with the processing server through one or more external network interfaces and that stores identified data and de-identified data on behalf of one or more third-party healthcare providers, (v) one or more servers that implement an analytics engine, (vi) one or more servers that implement a result generator, (vii) a computing platform that comprises an interface that is dedicated to interfacing with the data analysis system, and that does not already store a sufficient amount of patient-specific medical history data to perform a particular analysis of real-time, patient-specific medical history data for a particular patient, and (viii) one or more servers that implement a data integration service for re-identifying the de-identified data, and for standardizing the identified data and the re-identified data, the data analysis system further comprising:

one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising;

receiving, by the message hub of the data analysis system, a request for the particular analysis of real-time, patient-specific medical history data for the particular patient;

determining, by the processing server of the data analysis system, that a particular profile that is associated with the particular patient indicates that a sufficient amount of the real-time, patient-specific medical history data is stored in the identified data or the de-identified data in the data lake for the analytics engine to perform the particular analysis;

in response to determining that the particular profile that is associated with the particular patient indicates that a sufficient amount of the real-time, patient-specific medical history data is stored in the identified data or the de-identified data in the data lake for the analytics engine to perform the particular analysis, obtaining, by the processing server of the data analysis system, the real-time, patient-specific medical history data that is stored as de-identified data in the data lake using a real-time, transactional data mining technique that obtains data items individually through the one or more external network interfaces in real-time and that is other than batch processing, rather than waiting for the data items to be provided through the one or more external network interfaces in one or more batches;

re-identifying, by the one or more servers that implement the data integration service, the de-identified data of the obtained real-time, patient-specific medical history data, and standardizing the identified data and the re-identified data of the obtained real-time, patient-specific medical history data;

performing, by the analytics engine of the data analysis system, the particular analysis based on the obtained, standardized, real-time, patient-specific medical history data for the particular patient;

generating, by the result generator of the data analysis system, a result of performing the requested analysis based on the obtained, standardized, real-time, patient-specific medical history data for the particular patient, then deleting the obtained, standardized, real-time, patient-specific medical history data for the particular patient; and

providing, by the message hub of the data analysis system, the result of performing the requested analysis, through the interface that is dedicated to interfacing with the data analysis system, for output on the computing platform.

16. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

receiving, from a computing platform that does not already store a sufficient amount of patient-specific medical history data to perform a particular analysis of real-time, patient-specific medical history data for a particular patient and by a message hub of a data analysis system that includes (i) one or more servers that implement the message hub, (ii) a processing server, (iii) one or more servers that store profiles associated with different patients, (iv) a data lake that is in electronic communication with the processing server through one or more external network interfaces and that stores identified data and de-identified data on behalf of one or more third-party healthcare providers, (v) one or more servers that implement an analytics engine, (vi) one or more servers that implement a result generator, (vii) the computing platform that does not already store the sufficient amount of patient-specific medical history data to perform the particular analysis and that comprises an interface that is dedicated to interfacing with the data analysis system, and (viii) one or more servers that implement a data integration service for re-identifying the de-identified data, and for standardizing the identified data and the re-identified data, a request for the particular analysis of real-time, patient-specific medical history data for the particular patient;

determining, by the processing server of the data analysis system, that a particular profile that is associated with the particular patient indicates that a sufficient amount of the real-time, patient-specific medical history data is stored in the identified data or the de-identified data in the data lake for the analytics engine to perform the particular analysis;

in response to determining that the particular profile that is associated with the particular patient indicates that a sufficient amount of the real-time, patient-specific medical history data is stored in the identified data or the de-identified data in the data lake for the analytics engine to perform the particular analysis, obtaining, by the processing server of the data analysis system, the real-time, patient-specific medical history data that is stored in the identified data or the de-identified data in the data lake using a real-time, transactional data mining technique that obtains data items individually through the one or more external network interfaces in real-time and that is other than batch processing, rather than waiting for the data items to be provided through the one or more external network interfaces in one or more batches;

re-identifying, by the one or more servers that implement the data integration service, the de-identified data of the obtained real-time, patient-specific medical history data, and standardizing the identified data and the re-identified data of the obtained real-time, patient-specific medical history data;

performing, by the analytics engine of the data analysis system, the particular analysis based on the obtained, standardized, real-time, patient-specific medical history data for the particular patient;

generating, by the result generator of the data analysis system, a result of performing the requested analysis based on the obtained, standardized, real-time, patient-specific medical history data for the particular patient, then deleting the obtained, standardized, real-time, patient-specific medical history data for the particular patient; and

providing, by the message hub of the data analysis system, the result of performing the requested analysis, through the interface that is dedicated to interfacing with the data analysis system, for output on the computing platform.

17. The medium of claim 16, wherein the particular analysis comprises a quality of care analysis that assesses a quality of care that the particular patient has received by a provider, and wherein the result of performing the analysis comprises an assessment of a quality of care of the particular patient and an indication of remedial steps that may be undertaken to bring the particular patient within a defined standard of care.

18. The medium of claim 16, wherein the requested analysis comprises an analysis that assesses a potential current or future existence of, or a predicted, implication imposed by, a condition, and wherein the result of performing the analysis comprises a risk score for the condition.

19. The medium of claim 16, wherein the requested analysis comprises a waste-avoidance analysis that assesses potentially unnecessary utilization of tests, and wherein the result of performing the analysis comprises an indication of one or more potentially unnecessary tests or treatments.

20. The medium of claim 16, wherein the requested analysis comprises an eligibility analysis that assesses a user'"'"'s eligibility for various programs, and wherein the result of performing the analysis comprises a respective indication of eligibility or applicability for each of the various programs.