Differential effects of a social work staffing intervention on social work access among rural and highly rural Veterans: A cohort study

OBJECTIVE: To evaluate the impact on rural Veterans' access to social work services of a Department of Veterans Affairs (VA) national program to increase social work staffing, by Veterans' rurality, race, and complex care needs. DATA SOURCES AND STUDY SETTING: Data obtained from VA Corporate Data Warehouse, including sites that participated in the social work program between October 1, 2016 and September 30, 2021. STUDY DESIGN: The study outcome was monthly number of Veterans per 1000 individuals with 1+ social work encounters. We used difference-in-differences to estimate the program effect on urban, rural, and highly rural Veterans. Among rural and highly rural Veterans, we stratified by race (American Indian or Alaskan Native, Asian, Black, Native Hawaiian or Other Pacific Islander, and White) and complex care needs (homelessness, high hospitalization risk, and dementia). DATA COLLECTION: We defined a cohort of 740,669 Veterans (32,434,001 monthly observations) who received primary care at a participating site. PRINCIPAL FINDINGS: Average monthly social work use was 8.7 Veterans per 1000 individuals. The program increased access by 49% (4.3 per 1000; 95% confidence interval, 2.2-6.3). Rural Veterans' social work access increased by 57% (5.0; 3.6-6.3). Among rural/highly rural Veterans, the program increased social work access for those with high hospitalization risk by 63% (24.5; 18.2-30.9), and for Veterans experiencing homelessness, 35% (13.4; 5.2-21.7). By race, the program increased access for Black Veterans by 53% (6.1; 2.1-10.2) and for Asian Veterans by 82% (5.1; 2.2-7.9). CONCLUSIONS: At rural VA primary care sites with social work staffing below recommended levels, Black and Asian Veterans and those experiencing homelessness and high hospitalization risk may have unmet needs warranting social work services

Using social risks to predict unplanned hospital readmission and emergency care among hospitalized Veterans

OBJECTIVES: (1) To estimate the association of social risk factors with unplanned readmission and emergency care after a hospital stay. (2) To create a social risk scoring index. DATA SOURCES AND SETTING: We analyzed administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse. Settings were VA medical centers that participated in a national social work staffing program. STUDY DESIGN: We grouped socially relevant diagnoses, screenings, assessments, and procedure codes into nine social risk domains. We used logistic regression to examine the extent to which domains predicted unplanned hospital readmission and emergency department (ED) use in 30 days after hospital discharge. Covariates were age, sex, and medical readmission risk score. We used model estimates to create a percentile score signaling Veterans' health-related social risk. DATA EXTRACTION: We included 156,690 Veterans' admissions to a VA hospital with discharged to home from 1 October, 2016 to 30 September, 2022. PRINCIPAL FINDINGS: The 30-day rate of unplanned readmission was 0.074 and of ED use was 0.240. After adjustment, the social risks with greatest probability of readmission were food insecurity (adjusted probability = 0.091 [95% confidence interval: 0.082, 0.101]), legal need (0.090 [0.079, 0.102]), and neighborhood deprivation (0.081 [0.081, 0.108]); versus no social risk (0.052). The greatest adjusted probabilities of ED use were among those who had experienced food insecurity (adjusted probability 0.28 [0.26, 0.30]), legal problems (0.28 [0.26, 0.30]), and violence (0.27 [0.25, 0.29]), versus no social risk (0.21). Veterans with social risk scores in the 95th percentile had greater rates of unplanned care than those with 95th percentile Care Assessment Needs score, a clinical prediction tool used in the VA. CONCLUSIONS: Veterans with social risks may need specialized interventions and targeted resources after a hospital stay. We propose a scoring method to rate social risk for use in clinical practice and future research