Guest post by Clem McDonald, MD, Chief Health Data Standards Officer at NLM; Jessica Tenenbaum, PhD, Chief Data Officer for North Carolina’s Department of Health and Human Services; and Liz Amos, MLIS, Special Assistant to the Chief Health Data Standards Officer at NLM.
We all know that whether you get an annual flu shot or smoke affects your health. But nonmedical social and economic factors are also large influences on health. For example, individuals will struggle to control their diabetes if they can’t afford healthy food or are sleeping on the street. Healthy People 2020 describes such circumstances as social determinants of health (SDOH). As our health system shifts to value-based payments models, health care systems are prioritizing outcomes, such as the level of glucose control, rather than how much care is delivered (e.g., the number of visits or tests). To achieve better health outcomes, leading organizations are working to identify and address SDOH needs as well as medical needs.
The North Carolina Department of Health and Human Services (NCDHHS) Healthy Opportunities program identifies four priority domains of non-medical needs that can be detected using the answers to screening questions. Screening for needs in these domains will be a standard operating procedure for all Medicaid beneficiaries as the state transitions its Medicaid program to managed care from fee-for-service. Health care providers will be able to refer individuals to community resources such as food pantries, homeless shelters, transportation services, interpersonal violence counselors, and other services that can address some of these nonmedical needs, and the organizations can then be reimbursed for approved services under Medicaid. A computer-based “closed-loop” referral system will enable the collection of information from social service organizations about the services provided, allowing NCDHHS to facilitate reimbursement, monitor the program, and assess its effectiveness. Electronic systems like the one being used in North Carolina are essential to capturing answers to the SDOH screening questions, triaging individuals to appropriate community resources for intervention, and tracking the effects of those interventions. North Carolina is building a “learning” Department of Health and Human Services, similar to a learning health system, with data collected through services provided used to inform future policy decisions.
The SDOH needs being addressed in North Carolina exist across the country, so there is considerable interest in developing standards-based systems for capturing SDOH data anywhere in the United States without the need for separate development efforts at each stage. A powerful mechanism called Fast Healthcare Interoperability Resources®, or FHIR®, has emerged to enable standardization across a broad spectrum of health care processes. Developed by Health Level Seven International, FHIR is a modern, web-based technology for exchanging health care data that has strong and growing support from various stakeholders in the field of health care, including major electronic health record vendors; the tech industry, including Apple, Microsoft, Google, and Amazon; and federal agencies such as NIH, the Office of the National Coordinator for Health Information Technology, the Centers for Medicare and Medicaid Services, the Food and Drug Administration, and the Agency for Healthcare Research and Quality. NCDHHS is exploring the use of a FHIR-based data-capture tool for collecting SDOH information about nonmedical health needs and delivering the survey results to health care providers who can address the needs identified.
Created in the spirit of collaboration, NLM’s FHIR questionnaire app — an open-source tool that can be used, modified, or incorporated into existing tools by anyone — instantly converts a questionnaire that follows FHIR’s technical specifications into a live web form. It leverages the FHIR standard to collect questionnaire data, and generating a different form is just a matter of feeding the tool a different set of questions. FHIR forms can implement skip logic, the nesting of repeated groups of questions, calculations, validation checks, the repopulation of questions with answers from the individual’s FHIR medical record, and more. Of course, the same tool can also implement many other kinds of forms for capturing health care data, such as surveys that measure patient-reported outcomes. You can search more than 2,000 available questionnaires in NLM’s FHIR questionnaire demo app. Other NLM-developed, open-source FHIR-based tools for managing health care data are available here.
NLM and NCDHHS have worked together to develop an open-source, FHIR-based implementation of North Carolina’s Healthy Opportunities screening questions (see figure 1). Anyone with a FHIR-ready server will be able to download the form, enter data, and then route those data to the appropriate health information technology system.
Let’s get to work screening patients broadly while minimizing clinical documentation burdens through the use of standardized application programming interfaces!
Clem McDonald, MD, is the Chief Health Data Standards Officer at NLM. In this role, he coordinates standards efforts across NLM and NIH, including the FHIR interoperability standard and vocabularies specific to clinical care (LOINC, SNOMED CT, and RxNorm). Dr. McDonald developed one of the nation’s first electronic medical record systems and the first community-wide clinical data repository, the Indiana Network for Patient Care. Dr. McDonald previously served 12 years as Director of the Lister Hill National Center for Biomedical Communications and as scientific director of its intramural research program.
Jessica Tenenbaum, PhD, is the Chief Data Officer for North Carolina’s Department of Health and Human Services. In this role, Dr. Tenenbaum is responsible for the development and oversight of departmental data governance and strategy to enable data-driven policy for improving the health and well-being of North Carolinians. Dr. Tenenbaum is also an Assistant Professor in Duke University’s Department of Biostatistics and Bioinformatics. Dr. Tenenbaum is a member of the Board of Directors for the American Medical Informatics Association and serves on the Board of Scientific Counselors for NLM.
Liz Amos, MLIS, is Special Assistant to the Chief Health Data Standards Officer at NLM. She is a graduate of the University of Tulsa and the University of Oklahoma.
6 thoughts on “Addressing Social Determinants of Health with FHIR Technology”
Thank you for posting this information. It is very relevant to a project I am planning to work on with some fellow researchers in the US and UK.
Response on behalf of Liz Amos:
So glad you found this post helpful. Good luck with your project!
If you have any questions about our tools or resources, feel free to contact me at firstname.lastname@example.org
The HL7 Gravity Project is currently developing a FHIR Implementation Guide to facilitate the documentation, exchange, and aggregation of SDOH data elements. We are in the process of finalizing the food insecurity data set and will move onto housing and transportation in 2020. All are welcome to participate and join upcoming FHIR Connectathon testing events: https://confluence.hl7.org/display/GRAV/The+Gravity+Project
Response on behalf of Liz Amos:
Thanks for sharing this feedback! Looking forward to working with you and others on the Gravity project.