Social Determinants of Health
Represent Social Determinants of Health with LOINC
There is growing recognition that social and behavioral determinants of health (SDH) are important and large contributors to a person's health status.
One barrier to acting on SDH knowledge is that many electronic health records today don’t have easy ways to capture and reuse social and behavioral data into standardized, discrete variables.
This is where LOINC comes in...
LOINC has developed a robust model for representing screening assessments and measures of SDH, including questions, answers, and the collection of such variables into forms. Our goal is for LOINC to serve as a universal catalog and uniform representation of SDH data elements.
LOINC currently includes thousands of such SDH variables. And yet, we are eager to fill in the known gaps as stakeholders identify and adopt common instruments and variables.
LOINC codes for SDH measures recommended by the IOM
The Institute of Medicine has reviewed and endorsed specific measures for core domains of SDH in their reports Capturing Social and Behavioral Domains and Measures in EHRs. Working together with the ONC, the Regenstrief Institute developed a SDH panel of variables in LOINC that represent a minimum set of measures recommended for inclusion in EHRs.
These LOINC terms were referenced as an optional component of the Meaningful Use incentive program’s 2015 Certification Criteria published by the Office of the National Coordinator for Health IT.
Social, psychological and behavioral observations - 2015 Edition Health IT Certification Criteria set
This panel contains the social, psychological, and behavioral observations included in the 2015 Edition Health IT Certification Criteria.
Featured SDH content in LOINC
Out of the thousands of variables in LOINC, here are a few of the SDH highlights.
Humiliation, Afraid, Rape, and Kick questionnaire
The HARK questionnaire is a four-question, self-reported instrument that represents different components of interpersonal violence (IPV), including emotional, sexual, and physical abuse.
Opportunities for leveraging standardized SDH data
The upfront work to capture SDH in a structured, standardized format can lead to downstream benefits. Here are some of the possibilities.
Team-based, patient centered care
Effectively addressing SDH needs requires coordination between health care organizations, social service agencies, public health departments, and other community organizations. Partners may serve different roles, including an intervention site, source of data, and co-manager of a shared population. Standardized SDH data can enable inter-agency collaboration with sharable, understandable data.
Population health management
Providers and payers are increasingly focused on population health management as part of quality and payment transformation initiatives. As more evidence emerges connecting SDH and health, many are designing programs that better address patients’ SDH. To optimize programs and assess impact, providers or payers will need both a global picture of the SDH needs of the populations they serve. That global picture may include the severity of SDH need, trends in SDH need prevalence, related health care interventions. Standardized SDH data in EHRs would facilitate aggregation of these need and intervention data across sites that can be used in program design and evaluation.
As recognition of addressing SDH grows, opportunities are emerging for supporting healthcare-based remuneration for this work. These include direct reimbursement for SDH care, incentives or bonuses related to health care SDH linkages, and risk adjustment activities that adjust capitation or payments based on social risk. For each of these cases, health care organizations will need to document services related to SDH. These initiatives are likely to require that providers systematically track the percentage of patients who have been screened and treated for specific social needs using standardized measures.
Standardized data on SDH needs and interventions would strengthen research at the intersection of social and medical care services. Examples of where standardized data could facilitate research include: estimating SDH prevalence in specific sub-groups; examining SDH outcomes in clinical trials; and understanding how SDH impacts disease progression or prevalence.