Fast Health Interoperability Resources (FHIR) is a web-based, easy to implement, RESTful method for storing and exchanging health data. Apple, Google, and Microsoft, large health IT companies, federal agencies (ONC, CMS, Veterans Administration) and Big Pharma have embraced it. This workshop will present NLM’s open source, web-based, JavaScript support tools for FHIR forms and flowsheets.

The LHC form and flowsheet tools are bookends to a FHIR medical record. The right bookend provides the machinery for building forms and storing the data collected into a FHIR EHR. It implements FHIR Questionnaire, Questionnaire Response, and much of the capability of FHIR’s Structured Data Capture (SDC) specifications including pre-population, data extraction, calculated values, multi-column choice lists, adaptive (PROMIS-like) questionnaires and survey instrument scoring etc. We will explain how many of these capabilities are implemented and demonstrate their use.

The left bookend – LHC FHIR Flowsheet App—generates a flowsheet from an FHIR EHR and has features for collapsing date columns and rows of similar variables to for a more condensed display. It has built in unit conversion to enable the merging of variables with commensurate units including mass to molar conversions. It also includes a compact pixel map showing everything in the flowsheet (abnormal, normal) to ease navigation. We will describe the content of our 10K de-identified medical records set, which provides the grist for the FHIR Flowsheet App and will explain the configurable template that controls it. Participants will interact with a public, test version of the LHC-Flowsheet app with sample data.

All NLM tools are open source and based upon ONC standards and written in JavaScript for easy portability. Participants will have access to the tools after the workshop.

Learning Objective:
After participating in this session, the learner should be better able to:
1) Recognize and describe the FHIR standard and specifications for creating and retrieving medical data.
2) Understand the capabilities of FHIR forms using FHIR Questionnaire and FHIR QuestionnaireResponse resources by demonstrating NLM tools to create and edit (LHC Form Builder), then render (LHC FHIR SDC Questionnaire) such forms.
3) Illustrate how the HAPI FHIR server stores content for all resources in relatively few relational tables, enabling quick revisions of FHIR resource definitions with few performance limitations.
4) Interact with the content of the Indiana 10K Deceased Individuals dataset; use the LHC FHIR flowsheet to review its content and explore novel LHC flowsheet features for reviewing temporal clinical data.
5) Explore novel features of the LHC FHIR flowsheet tool and configure its tailorable template.


Clement McDonald (Presenter)
National Library of Medicine

Presentation Materials: