Abstract
OBJECTIVE: To prioritize social risks (individual-level social and economic conditions) that may influence a person's health for inclusion in a national survey of Veterans Affairs (VA) healthcare system patients. DATA SOURCES AND STUDY SETTING: Quantitative ratings of candidate survey measures were obtained from a national Advisory Group of researchers, clinicians, Veterans, and VA operations leaders; qualitative input was collected from the Advisory Group and Veterans. STUDY DESIGN: We solicited input on social risk prioritization across four phases: (1) candidate social risks were identified through a literature review and existing screening tools, (2) Advisory Group members (n = 15) individually and anonymously rated social risks on four criteria (impact on health outcomes, impact on patient experience, actionability, and overall prioritization), (3) the Advisory Group discussed collective ratings and provided qualitative feedback about candidate social risks, and 4) Veterans (n = 29) provided qualitative feedback about the draft survey during four Veteran Engagement Group meetings and in survey pretesting with individuals (n = 5). DATA COLLECTION/EXTRACTION METHODS: Selection of social risks for survey inclusion was based on an a priori definition of a social risk and relevance to Veterans (phase 1), quantitative and qualitative input from the Advisory Group (phases 2 and 3), and qualitative Veteran input (phase 4). PRINCIPAL FINDINGS: An initial list of 37 social risks was pared down to 18 for inclusion in a national survey: financial strain, health care/medicine access and affordability, food insecurity, homelessness/housing insecurity, transportation barriers, digital access/literacy, utilities insecurity, social support, caregiver responsibilities, discrimination experiences, interpersonal violence, education, employment, health literacy, legal problems or exposure to the justice system, race/ethnicity, gender identity, and sexual orientation. CONCLUSIONS: Our partner-informed approach combining quantitative and qualitative input offers a road map for other learning health systems seeking to prioritize social risks for evidence generation.