Literature Collection

BACKGROUND: People with long-term physical conditions are more likely to experience distress, depression, or anxiety. Physical-mental comorbidity is associated with lower quality of life, poorer clinical outcomes, and increased mortality than physical conditions alone. People of South Asian origin are the largest minority group in the UK, and more likely to have long-term conditions (LTCs) such as diabetes and heart disease. AIM: To explore how men of South Asian origin with LTCs understand and experience emotional distress as well as the experiences of GPs supporting them. DESIGN AND SETTING: A UK qualitative study interviewing South Asian men with diabetes or coronary heart disease, and GPs working at practices with higher proportions than average in the UK of people of South Asian origin. METHOD: Online semi-structured interviews with South Asian men and GPs were undertaken. Data were analysed via reflexive thematic analysis. Topic guides were modified iteratively as data collection and analysis progressed. An ethnically appropriate patient advisory group of South Asian men was involved in all stages of the research. RESULTS: Seventeen South Asian men with LTCs and 18 GPs were interviewed. Participants described contextualising distress, including LTCs influencing distress and the intersections of social determinants of distress including ethnicity, poverty, and perceptions of prejudice. Participants understood distress as different from depression with the need to negotiate multiple identities as well as integrative paradigms of health. CONCLUSION: This study highlights the influence of social determinants of distress in South Asian men with LTCs. It provides an insight into how primary care has the potential to address health inequalities by considering the intersection of these factors.

OBJECTIVES: Factors associated with treatment retention on medications for opioid use disorder (MOUD) in rural settings are poorly understood. This study examines associations between social determinants of health (SDoH) and MOUD retention among patients with opioid use disorder (OUD) in rural primary care settings. METHODS: We analyzed patient electronic health records from 6 rural clinics. Participants (N = 575) were adult patients with OUD and had any prescription for MOUD from October 2019 to April 2020. MOUD retention was measured by MOUD days and continuity defined as continuous 180 MOUD days with no more than a 7-day gap. Mixed-effect regressions assessed associations between the outcomes and SDoH (Medicaid insurance, social deprivation index [SDI], driving time from home to the clinic), telehealth use, and other covariates. RESULTS: Mean patient MOUD days were 127 days (SD = 50.7 days). Living in more disadvantaged areas (based on SDI) (adjusted relative risk [aRR]: 0.98; 95% confidence interval [CI], 0.98-0.99) and having more than an hour (compared with an hour or less) driving time from home to clinic (aRR: 0.95; 95% CI, 0.93-0.97) were associated with fewer MOUD days. Using telehealth was associated with more MOUD days (aRR: 1.23; 95% CI, 1.21-1.26). In this cohort, 21.7% of the participants were retained on MOUD for at least 180 days. SDoH and use of telehealth were not associated with having continuity of MOUD. CONCLUSIONS: Addressing SDoH (eg, SDI) and providing telehealth (eg, improvements in public transportation, internet access) may improve MOUD days in rural settings.

Background/Objectives: Identifying social determinants of health (SDOH) is important for effective clinical care. The ICD-10 introduced diagnostic categories to describe patients' adverse SDOH, but these codes are infrequently used across health systems, presenting challenges to implement data-driven healthcare. This study illustrates SDOH code utilization within a setting that is recognized as one of the largest integrated healthcare systems across the United States. Methods: Real-world clinical data were used with ICD-10 SDOH records obtained from 13,523 participants randomized into the Diuretic Comparison Project, a pragmatic trial conducted within the Veterans Affairs (VA) Health Care System between 2016 and 2022. SDOH code utilization was assessed across study years and among the specialized outpatient clinics. Results: A total of 29,305 SDOH records were identified, and 99.2% were from outpatient encounters. Social, mental, and housing care services generated the most SDOH records. Moreover, 3894 (28.8%) participants had at least one SDOH record during the 6-year period. Particular, 6.9% of participants had a record in the first year, and this increased to 7.6%, 8.1%, 8.7%, 9.6%, 10.3% in consecutive years. Conclusions: Our results suggest that SDOH code utilization has continued to improve within the VA, but SDOH assessments may not occur annually or be performed systematically within an integrated health setting. Much work is needed to develop universal screening tools and mandate routine SDOH evaluations. Nevertheless, a persistent increase in the counts of ICD-10 SDOH records shows a positive movement towards systematic documentation, supporting service providers to efficiently identify patients with adverse SDOH.

BACKGROUND AND OBJECTIVES: Social factors account for most health outcomes, underscoring the need to address social determinants of health (SDH) to eliminate health disparities. Our objectives are (1) to describe the scope of formal SDH curricula in family medicine residency, (2) to identify residency program characteristics associated with integrated core curriculum components to teach SDH, and (3) to identify barriers to addressing SDH in residency. METHODS: We distributed a cross-sectional survey to all family medicine residency program directors (PDs) accredited by the Accreditation Council for Graduate Medical Education as identified by the Association of Family Medicine Residency Directors. RESULTS: Of 624 eligible program directors, 279 completed the survey (45% response rate). Overall, 41.2% of respondents reported significant formal SDH training in their program. Though a majority (93.9%) agreed that screening for social needs should be a standard of care, most (58.9%) did not use standardized screening tools. The most common barriers to addressing SDH were lack of clinical resources (eg, social workers, legal advocates), lack of community resources (eg, food banks, substance use disorder treatment), and inadequate screening instruments or integration into the electronic medical record system. Availability of referral resources was associated with PDs' increased perception of resident SDH competency. CONCLUSIONS: Nearly all respondents agreed that screening for social needs should be a standard part of care; however, this vision is not yet realized. To better train the next generation of physicians to identify and meaningfully address social needs, additional research is needed. This research might include mixed-methods approaches that incorporate qualitative assessments to define best practices and patient-centered outcomes related to identifying and responding to SDH.

Opioid use and misuse are a widespread problem across the United States. Identifying and targeting social determinants of opioid use may help to identify predictive factors to influence intervention and policy. The purpose of this study was to identify social determinants of opioid use frequency among patients seeking primary care in rural Alabama healthcare facilities. This survey-based study focused on a patient population located in rural west Alabama surveyed for a screening, brief intervention, and referral to treatment program. The screening tool contained demographic information and questions regarding the social determinants of health and opioid use, among others. Adjusted incidence rate ratios (IRRs) for the relationship between social determinants of health and opioid use frequency (in days/month) were estimated in Poisson regression models. Eleven percent of the population self-reported opioid use in the past 30 days. Three social determinants of health measured (level of education, housing stability, and employment status) were identified as having a significant association with the frequency of opioid use. Targeting certain social determinants of health may allow for further predictive interventions to mitigate opioid misuse and potential fatality or mortality.

BACKGROUND: Social functioning (SF), the ability to engage with life and fulfill roles may be a salient "patient important outcome" in addiction treatment. It is not known if medication-assisted treatment (MAT) impacts SF in opioid use disorder (OUD). There is a growing evidence to suggest that men and women are impacted differently by OUD. This study is the largest to date to study sex differences in OUD and explore associations between MAT and SF. METHODS: Data were collected from 2736 participants with OUD, enrolled in MAT for varying lengths of time, in outpatient clinics across Ontario. SF was defined according to the Maudsley Addiction Profile's domains of (1) employment, (2) criminal activity, and (3) interpersonal conflict. Using logistic regression analysis, we examined sociodemographic and clinical factors associated with domains of SF. RESULTS: There were 1544 men (56%) and 1192 women (44%) in this study, and ages varied from 17 to 76 years for men and 18 to 69 years for women. At study entry, participants had been on MAT for a median of 2 years. Compared to men, women reported more psychological (mean MAP score 14/40, SD = 9.55, versus 11/40, SD = 8.64; p < 0.001) and physical symptoms (mean MAP score 17/40, SD = 7.70 versus 14/40, SD = 7.74; p < 0.001). More women reported unemployment(74% versus 58%; p < 0.0001) and interpersonal conflict (46% versus 35%; p < 0.0001). Men were more likely than women to report criminal activity (11%, versus 8%; p = 0.001). Psychological symptoms increased the risk of worse SF, across domains, for men and for women. Every year on MAT was associated with a 7% increase in the odds of women engaging with criminal activity (OR = 1.07, 95% CI 1.02, 1.12, p = 0.006). CONCLUSIONS: Men and women had different SF profiles and psychological symptoms scores while on MAT. The length of time on MAT increased the risk of criminal activity in women, and overall, duration of MAT was not associated with improvement in SF. This may suggest that MAT alone may not support continual improvements in SF in OUD.

IMPORTANCE: Health-related social risks are increasingly recognized as important contributors to health. Compared with individual screening, neighborhood measures are potentially a lower cost, scalable strategy for identifying social risk. OBJECTIVE: To inform health resource planning and social risk screening strategies by comparing self-reported vs neighborhood-level social risk with inpatient, emergency department (ED), and outpatient care. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional analysis of self-reported social risks measured during Medicaid enrollment and neighborhood-level social risk in relation to health care use was conducted. Members of Kaiser Permanente Northern California, a large integrated health care delivery system, who completed the Medicaid Integrated Outcomes Questionnaire from January 1, 2018, to February 29, 2020, were included. Analysis took place from January 8 to November 29, 2024. EXPOSURE: Neighborhood-level social risk (living in the least-resourced Neighborhood Deprivation Index quartile) and self-reported social risk (indicating a need or wanting help with finances, food, housing, or transportation domains). MAIN OUTCOMES AND MEASURES: Hospital and ED admissions, primary care, specialty care, mental health, and social work visits in the year prior to questionnaire completion. Multivariable negative binomial regression models were analyzed for each type of health care use, controlling for demographic characteristics and several health conditions (eg, asthma, hypertension, and chronic pain). RESULTS: Among 13 527 respondents (8631 [63.8%] female; 5289 [39.1%] aged 25-44 years; 2846 [21.0%] Asian, 1986 [14.7%] Black or African American, 3040 [22.5%] Hispanic, 4602 [34.0%] White, and 1053 [7.8%] other race or ethnicity), 33.8% in the most-resourced neighborhood reported at least 1 social risk vs 40.1% in the least-resourced quartile (P < .001). Individual- and neighborhood-level measures were each associated with ED visits (marginal effect estimate for both measures: 0.23; 95% CI, 0.17-0.29). Neither measure was associated with hospital admissions. Individual risk was associated with greater use of all outpatient services (ranging from primary care visit marginal effect estimate: 0.22; 95% CI, 0.13-0.31 to mental health visit marginal effect estimate: 1.21; 95% CI, 0.67-1.75). Neighborhood-level risk was not associated with most outpatient visits and was negatively associated with mental health visits. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, associations were found for hospital and ED use but not outpatient visits, especially mental health visits. These findings suggest that individual social risk screening appears to provide distinct information compared with neighborhood social risk.