FHIR and Data Provenance

We are beginning an ONC funded Data Provenance research and development  project which we invite you to learn more about.  Data Provenance is one of the most important and least discussed parts of Health Data Exchange.  Affecting security, trust and research and payor usability, data provenance must not only follow HL7 standards but also be accessible and readable, by providers, patients, payors and emergency or field personnel.

We will implement a new FHIR based health systems data provenance API (toolkit) that will improve standards compliance in the provenance generated during the exchange of patient data between EHR systems, HIE Networks and Patient Generated Health Data from a variety of medical devices.  The primary goal is to present readable, actionable data provenance consistently.  Using a mix of CCD-A and full, de-identified patient health records from each participating system, we will start with a sample of 10,000 records per site.  We will identify areas where HL7 provenance standards are not fully or correctly implemented to provide a baseline for gauging the usefulness of the new provenance API.  Where necessary we will have the new API integrated and then run analytics on the same systems after the API is in place to demonstrate successful generation of consistent provenance with a high level of readability.  The readability of the provenance in CCD-A’s and EHR records is potentially important, for trust and for actionability, at the patient, provider and payor levels.

We will be using records from a wide range of systems including Cerner, Epic, Mirth, Nextgen, several cloud based EHR systems used in the field by telemedicine devices and a hybrid EHR in use by one of our rural project areas.  We include in this study one of our USDA-funded rural telemedicine projects which serves the Pacific Region, including the Northern Mariana Islands, Guam and American Samoa.  This region will allow us to sample provenance generated by mobile diagnostic devices used for telemedicine in remote areas and in the field.  This use case for telemedicine involved instances where patient health data must pass through multiple hops to get to a consulting physicians EHR system.

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