Why bulk data?
To date, the vast majority of work in HL7 Fast Healthcare Interoperability Resources (FHIR®) standards development has been focused on individual member, patient and consumer specific exchange. Improving the ability of trading partners and third-party applications to also access clinical and claim related data at the population level can directly impact healthcare delivery. As early implementations and standards based upon FHIR gain adoption in the industry, there is a greater demand to leverage FHIR to exchange large volumes of data at a population level. It is critical that payers and providers pay attention and get involved in the work that is currently underway. Let’s take a few minutes to discuss this work and how Da Vinci use cases are evaluating the use of emerging solutions.
While there is a myriad of challenges to sort out between partners, we can agree that the ability to easily exchange a significant amount of information can propel population health efforts and patient engagement by enabling providers and patients to use the applications that are easiest and most appropriate. Providing richer patient information through claims data and clinical data can help patients and their providers make better informed decisions about care and follow-up.
Coming out of the SMART project, the FHIR Bulk Data Access (FBDA) standard creates a common approach to handle data sharing at scale. FBDA is an HL7 balloted implementation guide (IG) which allows systems to request and share large volumes of individual patient or population level data utilizing a FHIR API and the newline-delimited JSON (ndjson) file format. The asynchronous approach defined in the FDBA allows a client system to request clinical data consistent with the US core data for interoperability (USCDI) as well as FHIR financial resources. The data server receiving the request then assembles the FHIR data in the ndjson format. The ndjson file format allows a system to read the large data file in a streaming format, which can be more efficient. The ndjson format also maintains the json structure and references between the related FHIR resources.
How does Da Vinci fit in?
Da Vinci members are looking at ways to asynchronously transfer population level and large volumes of member-specific information between trading partners using FHIR. Da Vinci has identified core issues, concerns and potential paths forward to leverage emerging work on the FBDA as part of Da Vinci use cases. I encourage you to carve out time in your schedule to get engaged if your organization isn’t already following this work.
How is Da Vinci going to utilize FHIR bulk data access?
Da Vinci has identified two opportunities to utilize FBDA and test its feasibility for the payer-provider community:
- Da Vinci members have already identified the need to establish and share a member attribution list between payers and providers. The “Risk Based Contract Member Identification” use case will establish a FHIR implementation guide for creating and sharing this attribution list, which may be the basis for requesting data from a payer or provider. We will define how FBDA will be used to request data from a payer or provider and build the appropriate FHIR response by leveraging the framework initially specified in the Payer Data Exchange (PDEx) IG and Clinical Data Exchange (CDex) IG.
- Additionally, the Data Exchange for Quality Measures (DEQM) IG use case group will test the use of FBDA with the existing DEQM framework. We will also test out new operations to support FBDA. We will be using the Controlling Blood Pressure quality measure. This will be tested in the Clinical Reasoning track at the Atlanta HL7 Connectathon.
How can organizations get involved?
The public is invited to join the growing community of HL7 FHIR adopters.
- View upcoming tracks and learn how to join the September HL7 FHIR Connectathon.
- Keep up to date on Da Vinci Use Case progress by monitoring progress and joining the Da Vinci listserv.
Need to know more?
If you have questions, please reach out to Viet Nguyen, Da Vinci Technical Director, at vietnguyen@stratametrics.com, or Jocelyn Keegan, Da Vinci Program Manager at jocelyn.keegan@pocp.com.
Additional resources
http://hl7.org/fhir/us/bulkdata/2019May/index.html
https://github.com/HL7/bulk-data
