Data Provenance in Telemedicine, Patient Generated Health Data and HIE Exchange
An ONC funded dProv Toolkit implementation project
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January 2018 Project Update:
RAIN Live Oak Technology participated in IHE North America Connecathon 2018 as part of the mCSD (Mobile Care Services Discovery) integration profile testing. mCSD is a new IHE profile defining how FHIR (Fast Healthcare Interoperability Resources) can be used to deliver a robust directory/registry service providing information on practitioners, organizations, healthcare services and the relationships between these elements. This profile will allow systems providing full FHIR repositories or those who only wish to provide a directory service to use a shared data model for discovery. The profile defines specific query patterns client systems can use to discover care information, leveraging FHIR’s powerful RESTful approach without requiring a complete FHIR implementation.
To participate in testing, RAIN used the FHIRelate server, a new FHIR data repository implementation based on the service registry developed as part of the PULSE project. FHIRelate expands on the work supported by CAHIE to deliver deliver a full FHIR framework supporting complex queries, resource creation/modification, and retention of past resource versions. Due to its base in PULSE, we chose to test FHIRelate as part of the mCSD profile, which is similar in scope to the CAHIE service registry. This has given us an opportunity to develop the FHIRelate server, adding optional/advanced featured not used in PULSE, and to test it with other industry peers at Connectathon to validate its specification conformance and performance ability.
RAIN participated as both a supplier (FHIRelate acting as a data source) and a consumer (using a web client to run queries) during mCSD testing.
Successful testing was completed with OpenHIE, CorePoint Health and Qvera demonstrating the exchange of queries across systems and simulating a myriad of query patterns defined by IHE, with the Data Provenance Toolkit designed into the tests.
These searches included such discovery actions as finding services of a certain type, looking up locations with physicians who speak a certain language, and searching a record history to view past records. The new mCSD profile enables much richer and more efficient queries than previous models such as HPD, giving a strong opportunity for communities, providers and HIEs to deliver meaningful service/practitioner discovery.
October 2017 Project Update
The growing scope and complexity of digital health records exchange has created a need for tools to better validate, present and organize data provenance to provide reliable information on the origin and authorship of received documents. Increased use of health information exchanges (HIEs) has made available more robust patient health records, but this has created challenges in using and maintaining provenance in records consolidated from multiple data sources spanning numerous providers, labs, and medical organizations. High-needs and chronic care patients, such as veterans and senior citizens, often require care from many facilities, multiple doctors and may have received medical attention while traveling. We now have the HIE technology to bring together these disparate repositories to form a unified medical document, but once in hand, such a document does not convey adequate information regarding the provenance of individual components such as exam notes, lab results, photographic/radiological images, and patient generated health data (PGHD).
Data Provenance, as recommended for implementation by HL7 v3, provides this information and establishes consistency in CCD-A provenance exchange. There is a need to establish a set of tools which ensure that data provenance as a standard will be implemented. Equally important is the development of consistent policies that allow for the efficient adoption of HL7v2 data provenance standards without creating conflicts with regional, state or federal policies.
Our current ONC sponsored project will address this problem through the introduction of enhanced Data Provenance tools applied to participating health record systems to generate, record and exchange metadata on the origin, authorship, and validity of records. Use of digital signatures within the provenance record as a form of identity certification will be studied as well.
These data provenance tools are designed to ensure consistency of provenance through the full continuum of healthcare, from patient generated health data to physician and lab data and back to the patient.
The project is coordinating exchange and provenance tracking between diverse health information organizations—both clinical and patient-centric—to implement and test a new Data Provenance tool set. Designed to deliver uniform, system-independent Provenance originating from a variety of sources and able to be read and interpreted at multiple levels of data exchange. The new tool set will be deployed as a provenance management layer within the data systems of health systems participating in the project to minimize the impact on existing workflow.
We have formed a partnership of healthcare providers, telemedicine providers, and patient engagement organizations to take part in this project and to act as dual provenance generators/consumers, demonstrating interoperability of provenance regardless of which exchange connections it is traversing. Each participant will implement provenance-enabled document creation, exchange, and verification. This will expedite the use of exchange data by providing improved trust, increasing patient engagement and making health information more useful to providers and payors by better ensuring data and identity authenticity.
This project will demonstrate consistent data provenance in multiple health information exchange environments. The dProv app will be applied to One-Step EHR-to-EHR data and image exchanges as well as to the larger exchange environment that includes patients and payors. Exchange settings such as telemedicine where mobile clinical devices are used to send patient data gathered by the attending caregivers, into a cloud-based health record, then to a local clinical EHR and then, via a HIE Network, to consulting physicians EHR will take part in the project.
Take a moment to review our Power Point presentation: