BACKGROUND

The present invention relates to techniques for filling important gaps in data, particularly in health-related data, including electronic health record (EHR) data and patient reported outcomes (PRO) data, but also in a wide range of data types, such as omic data, personal data, demographic data, and so forth. The invention also relates to platforms and approaches to aggregating data from contributing members of a community, compensating or motivating contributing members, and utilizing the data to aid both members and a larger community.

The value of big data has become generally accepted, creating an industry drive to aggregate different types of data in order to use machine learning and other tools to drive discovery. At scale even weak data can be valuable in unlocking links between our health and our genomic information and our daily habits, such as diet, exercise, drinking, smoking, hours of sleep, etc. Therefore, it is valuable to collect an individual's data from health institutions and through direct surveys and interviews. Additionally, it is now possible to collect implicit data through grocery store loyal customer tracking of purchase records, credit card records, online search habits, etc.

In all cases, even though at an aggregate level the data is valuable, there is a significant amount of missing information. Some examples are EHR and PRO data. EHRs are typically filled out by doctors online while meeting with patients. There are at least two types of challenges with these records. First, EHRs are designed primarily as billing systems for medical institutions. They record patient information such as test results, symptoms, and doctors' observations and recommendations, including treatment prescriptions. They do not typically record outcomes after treatment or whether patients followed the prescribed treatment regime. Moreover, doctors and other health professionals do not always use digital entry fields to record information. They often simply write information in unstructured comment fields. Additionally, the nomenclature and ontology used when inputting data is not standardized. There is a major challenge associated with deciphering and decrypting these free form comments.

In the case of PRO records, often patient outcomes are never reported in a system. There is no current method for identifying even when a PRO should be sought. Additionally, PROs might be required periodically over a long period of time. Some diseases and corresponding treatments may last months, years, or be persistent over a lifetime. The longitudinal information that would come from PROs is valuable in determining efficacy of treatments and in stratifying diseases diagnosed based on symptoms, to determine the underlying molecular basis for the disease.

To data solutions to fill in the holes and acquire the missing information have all been focused on using humans to review the data, identify mission information, and manually attempt to fill the gaps. People can for instance read EHR records, including fee form fields, and then populate the digital fields accordingly. Additionally surveyors call individuals and through in person interview they identify PROs, and input the corresponding information into digital database fields. In all cases the solution requires the intervention of an individual, and it is therefor not scalable in terms of labor hours or labor dollars for use with databases of tens of thousands to millions of individuals.

Beyond EHR and PRO data, many other data types may be extremely useful in piecing together an overall picture of the condition, state, or health of an individual and of groups of individuals, as well as for assessing possible pathways for maintaining health, avoiding or treating disease, recognizing and developing treatments, and so forth. But such pathways are hindered by missing or inaccurate data, and by typical “siloing” of data by separate sources, institutions, and so forth, often with no ill intent, and many times with patient or individual confidentiality in mind. At the same time, social media platforms may almost certainly share data, but again typically silo the data for their own purposes, and quite often even without any control by the individuals involved, and little or no quality control.

There is a need for improved technologies for data gathering and quality control, which scalable data aggregation and use. There is a particular need for such technologies that may enhance the control and motivate participation by contributing individuals, while protecting their privacy.

BRIEF DESCRIPTION

In accordance with one aspect of the disclosure, a system comprises a server that, in operation, facilitates interaction with contributing members of an aggregation; a centralized database maintained by an administrative entity that, in operation, stores and aggregates the member-specific contributed data transmitted by contributing members with member-specific contributed data contributed by other contributing members; and processing circuitry maintained by the administrative entity that, in operation, processes member-specific account data received from the contributing members via interface pages to establish member-specific accounts based on the member-specific account data, and attributes a member-specific value to the member-specific accounts based upon respective member-specific contributed data. The processing circuitry analyzes the member-specific contributed data for each member to determine missing or incorrect data, and sends a de-identified communication to respective member to provide missing data or to correct incorrect data.

In accordance with some embodiments, the processing circuitry may determine a quality score based upon the completeness and/or correctness of the member-specific contributed data; and/or the quality score is based at least partially on determined contradictions and/or inconsistencies in the member-specific contributed data; and/or the member-specific value is at least partially upon the quality score; and/or the processing circuitry automatically and without human intervention attempts to complete missing data and/or to correct incorrect data prior to communicating with the contributing member; and/or the database is configured to store member-specific contributed data of different types, and the processing circuitry determines missing or incorrect data of one type based upon analysis of data of a different type; and/or the types of member-specific contributed data comprise at least two of omic data, phenotype data, health data, personal data, familial data and environmental data; and/or the database is configured to store member-specific contributed data of different types, and the processing circuitry determines missing or incorrect data of one type based upon analysis of the same type of data but contributed at different times by the same contributing member; and/or the missing or incorrect data is determined based upon analysis of aggregated data of a plurality of contributing members; and/or the missing or incorrect data comprises at least two of personal data, medical record data, dietary data and wearable device data; and/or the communication comprises a customized survey based upon data determined to be missing and/or incorrect; and/or the communication comprises a recommendation for acquisition of additional data by the contributing member; and/or the processing circuitry transfers an asset amount to each member-specific account based upon the member-specific value; and/or the user-specific value is attributed as a currency and/or a cryptocurrency and/or an ownership share in the database; and/or the processing circuitry is configured to make ledger entries in an immutable and/or cryptographically encoded ledger and/or a blockchain based upon interaction with the contributing members.

In accordance with another aspect of the disclosure, a system comprises a server that, in operation, facilitates interaction with contributing members of an aggregation; a centralized database maintained by an administrative entity that, in operation, stores and aggregates the member-specific contributed data transmitted by contributing members with member-specific contributed data contributed by other contributing members; and processing circuitry maintained by the administrative entity that, in operation, processes member-specific account data received from the contributing members via interface pages to establish member-specific accounts based on the member-specific account data, and attributes a member-specific value to the member-specific accounts based upon respective member-specific contributed data, wherein the processing circuitry analyzes the member-specific contributed data for each member to determine missing or incorrect data; and wherein the database is configured to store member-specific contributed data of different types, and the processing circuitry automatically and without human intervention, provides and/or corrects missing or incorrect data of one type based upon analysis of data of a different type or from a separate contribution event, the types of member-specific contributed data comprise at least two of omic data, phenotype data, health data, personal data, familial data and environmental data.

In accordance with some embodiments of this technique, the database comprises an immutable and/or cryptographically encoded and/or tamper-evident ledger; the processing circuitry sends a de-identified communication to respective contributing members to provide or correct missing or incorrect data, or to confirm the automatic provision of the missing or incorrect data; or any of the specific variations mentioned above may be combined with these embodiments.

In accordance with a further aspect of the disclosure, a computer-implemented method comprises receiving, from the contributing members, member-specific account data and member-specific contributed data, the member-specific contributed data comprising health-related data submitted by each contributing member or data derived therefrom; storing, in a database, the member-specific contributed data; aggregating the member-specific contributed data with member-specific contributed data of other contributing members; establishing a member-specific account for each contributing member based on the member-specific account data; attributing a member-specific value to each member-specific account based upon member-specific contributed data of the respective contributing member; and processing the member-specific contributed data to determine missing or incorrect data, and sending a de-identified communication to respective member to provide missing data or to correct incorrect data.

In accordance with some embodiments of such methods, the database or another component of the system comprises an immutable and/or cryptographically encoded ledger and/or a blockchain. Any of the specific variations mentioned above may be combined with such methods.

In accordance with still another aspect of the disclosure, a system comprises a server that, in operation, facilitates interaction with contributing members of an aggregation; a centralized database maintained by an administrative entity that, in operation, stores and aggregates the member-specific contributed data transmitted by contributing members with member-specific contributed data contributed by other contributing members; and processing circuitry maintained by the administrative entity that, in operation, processes member-specific account data received from the contributing members via interface pages to establish member-specific accounts based on the member-specific account data, and attributes a member-specific value to the member-specific accounts based upon respective member-specific contributed data; wherein the processing circuitry analyzes the member-specific contributed data for each member to determine missing or incorrect data, and sends a de-identified communication to respective member to provide missing data or to correct incorrect data; and wherein the processing circuitry automatically and without human intervention attempts to complete missing data and/or to correct incorrect data prior to communicating with the contributing member.

In accordance with some embodiments of this system, the database is configured to store member-specific contributed data of different types, and the processing circuitry determines missing or incorrect data of one type based upon analysis of data of a different type or data contributed at a different time; and/or the processing circuitry attempts to complete missing data and/or to correct incorrect data of one type based upon analysis of a different type; and/or the processing circuitry attempts to complete missing data and/or to correct incorrect data of one contributing member based upon member-specific contributed data of at least one other contributing member; and/or the processing circuitry attempts to complete missing data and/or to correct incorrect data of one contributing member based upon aggregated member-specific contributed data of a plurality of other contributing members; and/or the types of member-specific contributed data comprise at least two of omic data, phenotype data, health data, personal data, familial data and environmental data; and/or the missing or incorrect data comprises at least two of personal data, medical record data, dietary data and wearable device data; and/or the communication comprises a customized survey based upon data determined to be missing and/or incorrect, or an invitation to provide additional data; and/or the processing circuitry determines a quality score based upon the completeness and/or correctness of the member-specific contributed data; and/or the quality score is based at least partially on determined contradictions and/or inconsistencies in the member-specific contributed data; and/or the processing circuitry re-evaluates the quality score after completion of incomplete data and/or correction of incorrect data; and/or the member-specific value is at least partially upon the quality score; and/or the processing circuitry re-evaluates the member-specific value after completion of incomplete data and/or correction of incorrect data; and/or the processing circuitry transfers an asset amount to each member-specific account based upon the member-specific value; and/or the user-specific value is attributed as a currency and/or a cryptocurrency and/or an ownership share in the database; and/or the processing circuitry is configured to make ledger entries in an immutable and/or cryptographically encoded ledger and/or a blockchain based upon interaction with the contributing members. Methods, including computer-implemented methods may be implemented to utilize such techniques, including any of the specific variations mentioned above.

In accordance with still another aspect of the disclosure, a system comprises a server that, in operation, facilitates interaction with contributing members of an aggregation; a centralized or virtually centralized database maintained by an administrative entity that, in operation, stores and aggregates the member-specific contributed data transmitted by contributing members with member-specific contributed data contributed by other contributing members; and processing circuitry maintained by the administrative entity that, in operation, processes member-specific account data received from the contributing members via interface pages to establish member-specific accounts based on the member-specific account data, and attributes a member-specific value to the member-specific accounts based upon respective member-specific contributed data; wherein the processing circuitry analyzes the member-specific contributed data for each member to determine missing or incorrect data, and sends a de-identified communication to respective member to provide missing data or to correct incorrect data; and wherein the processing circuitry automatically and without human intervention sends follow-up de-identified communications to specific contributing members to prompt contribution of follow-up member-specific contributed data based upon a physical condition of the respective contributing members.

In accordance with some embodiments of this aspect, the processing circuitry sends the follow-up de-identified communications periodically; and/or the processing circuitry sends the follow-up de-identified communications episodically; and/or the processing circuitry sends the follow-up de-identified communications based upon treatment regimes as indicated by the member-specific contributed data for the respective contributing members; and/or the processing circuitry sends the follow-up de-identified communications based upon a condition and/or disease diagnosis as indicated by the member-specific contributed data for the respective contributing members; and/or the follow-up de-identified communications comprise recommendations for acquisition of additional data of the respective contributing members; and/or the member-specific contributed data comprises health-related data, and the recommendations comprise at least one physical examination or test related to physical condition of the respective contributing members; and/or the processing circuitry analyzes the member-specific contributed data of each member to determine at least one most convenient and/or cost effective source for the acquisition of additional data, and the recommendations include an indication of the most convenient and/or cost effective source for each respective recommendation to each respective contributing member; and/or the follow-up communications for one contributing member are based upon member-specific contributed data of at least one other contributing member; and/or the follow-up communications for one contributing member based upon aggregated member-specific contributed data of a plurality of other contributing members; and/or types of member-specific contributed data comprise at least two of omic data, phenotype data, health data, personal data, familial data and environmental data; and/or the follow-up communications comprise a customized survey based upon the physical condition of the respective contributing members; and/or the processing circuitry re-evaluates the member-specific value after receipt of follow-up member-specific contributed data from each respective contributing member; and/or the follow-up communications comprise an indication to each contributing member of the re-evaluation of the member-specific value applicable when the respective contributing member contributes the follow-up member-specific contributed data; and/or the processing circuitry transfers an asset amount to each member-specific account based upon the member-specific value; and/or the user-specific value is attributed as a currency and/or a cryptocurrency and/or an ownership share in the database; and/or the processing circuitry is configured to make ledger entries in an immutable and/or cryptographically encoded ledger and/or a blockchain based upon interaction with the contributing members. Methods, including computer-implemented methods may be implemented to utilize such techniques, including any of the specific variations mentioned above.

In accordance with still another aspect of the disclosure, a system comprises a server that, in operation, facilitates interaction with contributing members of an aggregation; a centralized or virtually centralized database maintained by an administrative entity that, in operation, stores and aggregates the member-specific contributed data transmitted by contributing members with member-specific contributed data contributed by other contributing members; and processing circuitry maintained by the administrative entity that, in operation, processes member-specific account data received from the contributing members via interface pages to establish member-specific accounts based on the member-specific account data, and attributes a member-specific value to the member-specific accounts based upon respective member-specific contributed data; wherein the processing circuitry analyzes the aggregated member-specific contributed data to determine cohorts of contributing members based upon correlations between the member-specific contributed data for each contributing member.

In accordance with some embodiments of such systems, the processing circuitry determines the cohorts by periodic analysis of the aggregated member-specific contributed data; and/or the processing circuitry determines the cohorts by episodic analysis of the aggregated member-specific contributed data; and/or the processing circuitry determines the cohorts based upon analysis of the aggregated member-specific contributed data initiated by at least one contributing member; and/or the processing circuitry determines the cohorts based upon analysis of the aggregated member-specific contributed data initiated by identification of a physical condition potentially detectable from the aggregated member-specific contributed data; and/or the processing circuitry determines the cohorts based upon analysis of the aggregated member-specific contributed data initiated by identification of a new treatment of a physical condition detectable from the aggregated member-specific contributed data; and/or the processing circuitry determines the cohorts based upon analysis of the aggregated member-specific contributed data initiated by identification of a new examination, test, or omic pattern useful in determining a physical condition detectable from the aggregated member-specific contributed data; and/or the processing circuitry determines the cohorts without identification of the contributing members to the administrative entity; and/or the cohorts comprise contributing members sharing a physical condition; and/or the cohorts comprise contributing members sharing a disease state; and/or the cohorts comprise contributing members sharing a potential legal claim; and/or the processing circuitry permits communications between contributing members of a cohort without revealing identification of respective contributing members to the administrative entity; and/or the processing circuitry permits communications between contributing members of a cohort without revealing identification of respective contributing members to other contributing members unless such identification is done by the respective contributing members; and/or types of member-specific contributed data comprise at least two of omic data, phenotype data, health data, personal data, familial data, demographic data, employment data, and environmental data; and/or the determination of cohorts is initiated based upon analysis of one type of data followed by analysis of different types of data; and/or the processing circuitry permits contributing members to opt out of analysis to determine cohorts; and/or the processing circuitry permits contributing members to request that other members contribute additional data to enable or improve a statistical fit of data from potential cohort members of a determined cohort group; and/or the processing circuitry is configured to perform quality control operations on the contributed data prior to determination of the cohorts; and/or the processing circuitry transfers an asset amount to each member-specific account based upon the member-specific value; and/or the user-specific value is attributed as a currency and/or a cryptocurrency and/or an ownership share in the database; and/or the processing circuitry is configured to make ledger entries in an immutable and/or cryptographically encoded ledger and/or a blockchain based upon interaction with the contributing members. Methods, including computer-implemented methods may be implemented to utilize such techniques, including any of the specific variations mentioned above.

In accordance with yet another aspect of the disclosure, a system comprises a server that, in operation, facilitates interaction with contributing members of an aggregation; a centralized or virtually centralized database maintained by an administrative entity that, in operation, stores and aggregates the member-specific contributed data transmitted by contributing members with member-specific contributed data contributed by other contributing members; and processing circuitry maintained by the administrative entity that, in operation, processes member-specific account data received from the contributing members via interface pages to establish member-specific accounts based on the member-specific account data, and attributes a member-specific value to the member-specific accounts based upon respective member-specific contributed data; and a template stored in database and including anticipated events or information in a patient health journey; wherein the processing circuitry automatically and without human intervention sends follow-up de-identified communications to specific contributing members to prompt contribution of follow-up member-specific contributed data based upon the template.

In accordance with some embodiments of such systems, the system comprises a plurality of templates, each template including anticipated events in a different patient health journey; and/or the template is based upon analysis of the aggregated member-specific contributed data indicative of events of other contributing members on the same patient health journey; and/or the template is based on contributed data from members who may have a similar condition or symptoms; and/or the follow-up communications based upon the template relate to a patient health journey initiated by a birth; and/or the follow-up communications based upon the template relate to a patient health journey initiated by symptoms or conditions indicated by the patient-specific contributed data; and/or the follow-up communications based upon the template relate to a patient health journey initiated by a diagnosis indicated by the patient-specific contributed data; and/or the follow-up communications based upon the template relate to a patient health journey initiated by a treatment plan indicated by the patient-specific contributed data; and/or the follow-up communications based upon the template relate to a patient health journey initiated by identification of a physical condition potentially detectable from the aggregated member-specific contributed data; and/or the follow-up communications based upon the template relate to a patient health journey initiated by identification of a new treatment of a physical condition detectable from the aggregated member-specific contributed data; and/or the follow-up communications based upon the template relate to a patient health journey initiated by identification of a new examination or test useful in determining a physical condition detectable from the aggregated member-specific contributed data; and/or the follow-up communications based upon the template comprise a custom report adapted to facilitate a contributing member consulting a medical professional; and/or the follow-up de-identified communications comprise recommendations for acquisition of additional data of the respective contributing members; and/or the member-specific contributed data comprises health-related data, and the recommendations comprise at least one physical examination or test related to physical condition of the respective contributing members; and/or the processing circuitry analyzes the member-specific contributed data of each member to determine at least one most convenient and/or cost effective source for the acquisition of additional data, and the recommendations include an indication of the most convenient and/or cost effective source for each respective recommendation to each respective contributing member; and/or the processing circuitry re-evaluates the member-specific value after receipt of follow-up member-specific contributed data from each respective contributing member; and/or the follow-up communications comprise an indication to each contributing member of the re-evaluation of the member-specific value applicable when the respective contributing member contributes the follow-up member-specific contributed data; and/or the processing circuitry transfers an asset amount to each member-specific account based upon the member-specific value; and/or the user-specific value is attributed as a currency and/or a cryptocurrency and/or an ownership share in the database; and/or the processing circuitry is configured to make ledger entries in an immutable and/or cryptographically encoded ledger and/or a blockchain based upon interaction with the contributing members. Methods, including computer-implemented methods may be implemented to utilize such techniques, including any of the specific variations mentioned above.

