Participation of Veterans Affairs Medical Centers in veteran-centric community-based service navigation networks: A mixed methods study.

OBJECTIVE: To understand the determinants and benefits of cross-sector partnerships between Veterans Affairs Medical Centers (VAMCs) and geographically affiliated AmericaServes Network coordination centers that address Veteran health-related social needs. DATA SOURCES AND SETTING: Semi-structured interviews were conducted with AmericaServes and VAMC staff across seven regional networks. We matched administrative data to calculate the percentage of AmericaServes referrals that were successfully resolved (i.e., requested support was provided) in each network overall and stratified by whether clients were also VAMC patients. STUDY DESIGN: Convergent parallel mixed-methods study guided by Himmelman's Developmental Continuum of Change Strategies (DCCS) for interorganizational collaboration. DATA COLLECTION: Fourteen AmericaServes staff and 17 VAMC staff across seven networks were recruited using snowball sampling and interviewed between October 2021 and April 2022. Rapid qualitative analysis methods were used to characterize the extent and determinants of VAMC participation in networks. PRINCIPAL FINDINGS: On the DCCS continuum of participation, three networks were classified as networking, two as coordinating, one as cooperating, and one as collaborating. Barriers to moving from networking to collaborating included bureaucratic resistance to change, VAMC leadership buy-in, and not having VAMCs staff use the shared technology platform. Facilitators included ongoing communication, a shared mission of serving Veterans, and having designated points-of-contact between organizations. The percentage of referrals that were successfully resolved was lowest in networks engaged in networking (65.3%) and highest in cooperating (85.6%) and collaborating (83.1%) networks. For coordinating, cooperating, and collaborating networks, successfully resolved referrals were more likely among Veterans who were also VAMC patients than among Veterans served only by AmericaServes. CONCLUSIONS: VAMCs participate in AmericaServes Networks at varying levels. When partnerships are more advanced, successful resolution of referrals is more likely, especially among Veterans who are dually served by both organizations. Although challenges to establishing partnerships exist, this study highlights effective strategies to overcome them.

Developing a brief assessment of social risks for the Veterans Health Administration Survey of Healthcare Experiences of Patients.

OBJECTIVE: To determine whether a 6- or 12-month look-back period affected rates of reported social risks in a social risk survey for use in the Veterans Health Administration and to assess associations of social risks with overall health and mental health. STUDY DESIGN: Cross-sectional survey of respondents randomized to 6- or 12-month look-back period. DATA SOURCES AND STUDY SETTING: Online survey with a convenience sample of Veterans in June and July 2021. DATA COLLECTION/EXTRACTION METHODS: Veteran volunteers were recruited by email to complete a survey assessing social risks, including financial strain, adult caregiving, childcare, food insecurity, housing, transportation, internet access, loneliness/isolation, stress, discrimination, and legal issues. Outcomes included self-reported overall health and mental health. Chi-squared tests compared the prevalence of reported social risks between 6- and 12-month look-back periods. Spearman correlations assessed associations among social risks. Bivariate and multivariable logistic regression models estimated associations between social risks and fair/poor overall and mental health. PRINCIPAL FINDINGS: Of 3418 Veterans contacted, 1063 (31.10%) responded (87.11% male; 85.61% non-Hispanic White; median age = 70, interquartile range [IQR] = 61-74). Prevalence of most reported social risks did not significantly differ by look-back period. Most social risks were weakly intercorrelated (median |r| = 0.24, IQR = 0.16-0.31). Except for legal issues, all social risks were associated with higher odds of fair/poor overall health and mental health in bivariate models. In models containing all significant social risks from bivariate models, adult caregiving and stress remained significant predictors of overall health; food insecurity, housing, loneliness/isolation, and stress remained significant for mental health. CONCLUSIONS: Six- and 12-month look-back periods yielded similar rates of reported social risks. Although most individual social risks are associated with fair/poor overall and mental health, when examined together, only adult caregiving, stress, loneliness/isolation, food, and housing remain significant.