Scaling-up social needs screening in practice: a retrospective, cross-sectional analysis of data from electronic health records from Bronx county, New York, USA.

OBJECTIVES: There has been renewed focus on health systems integrating social care to improve health outcomes with relatively less related research focusing on 'real-world' practice. This study describes a health system's experience from 2018 to 2020, following the successful pilot in 2017, to scale social needs screening of patients within a large urban primary care ambulatory network. SETTING: Academic medical centre with an ambulatory network of 18 primary care practices located in an urban county in New York City (USA). PARTICIPANTS: This retrospective, cross-sectional study used electronic health records of 244 764 patients who had a clinical visit between 10 April 2018 and 8 December 2019 across any one of 18 primary care practices. METHODS: We organised measures using the RE-AIM framework domains of reach and adoption to ascertain the number of patients who were screened and the number of providers who adopted screening and associated documentation, respectively. We used descriptive statistics to summarise factors comparing patients screened versus those not screened, the prevalence of social needs screening and adoption across 18 practices. RESULTS: Between April 2018 and December 2019, 53 093 patients were screened for social needs, representing approximately 21.7% of the patients seen. Almost one-fifth (19.6%) of patients reported at least one unmet social need. The percentage of screened patients varied by both practice location (range 1.6%-81.6%) and specialty within practices. 51.8% of providers (n=1316) screened at least one patient. CONCLUSIONS: These findings demonstrate both the potential and challenges of integrating social care in practice. We observed significant variability in uptake across the health system. More research is needed to better understand factors driving adoption and may include harmonising workflows, establishing unified targets and using data to drive improvement.

The association between social needs and chronic conditions in a large, urban primary care population.

There is consensus that social needs influence health outcomes, but less is known about the relationships between certain needs and chronic health conditions in large, diverse populations. This study sought to understand the association between social needs and specific chronic conditions using social needs screening and clinical data from Electronic Health Records. Between April 2018-December 2019, 33,550 adult (≥18y) patients completed a 10-item social needs screener during primary care visits in Bronx and Westchester counties, NY. Generalized linear models were used to estimate prevalence ratios for eight outcomes by number and type of needs with analyses completed in Summer 2020. There was a positive, cumulative association between social needs and each of the outcomes. The relationship was strongest for elevated PHQ-2, depression, alcohol/drug use disorder, and smoking. Those with ≥3 social needs were 3.90 times more likely to have an elevated PHQ-2 than those without needs (95% CI: 3.66, 4.16). Challenges with healthcare transportation was associated with each condition and was the most strongly associated need with half of conditions in the fully-adjusted models. For example, those with transportation needs were 84% more likely to have an alcohol/drug use disorder diagnosis (95% CI: 1.59, 2.13) and 41% more likely to smoke (95% CI: 1.25, 1.58). Specific social needs may influence clinical issues in distinct ways. These findings suggest that health systems need to develop strategies that address unmet social need in order to optimize health outcomes, particularly in communities with a dual burden of poverty and chronic disease.

Toward Understanding Social Needs Among Primary Care Patients With Uncontrolled Diabetes.

INTRODUCTION/OBJECTIVES: Uncontrolled diabetes can lead to major health complications, and significantly contributes to diabetes-related morbidity, mortality, and healthcare costs. Few studies have examined the relationship between unmet social needs and diabetes control among predominantly Black and Hispanic patient populations. METHODS: In a large urban hospital system in the Bronx, NY, 5846 unique patients with diabetes seen at a primary care visit between April 2018 and December 2019 completed a social needs screener. Measures included diabetes control (categorized as Hemoglobin (Hb) A1c <9.0 as controlled and Hb A1C ≥9.0 as uncontrolled), social needs (10-item screen), and demographic covariates, including age, sex, race/ethnicity, insurance status, percentage of block-group poverty, patient's preferred language, and the Elixhauser Comorbidity Index. RESULTS: Twenty-two percent (22%) of the patient sample had at least 1 unmet social need, and the most prevalent unmet social needs were housing issues (including housing quality and insecurity), food insecurity, and lack of healthcare transportation. Logistic regression analysis showed a significant relationship between social needs and uncontrolled diabetes, with more social needs indicating a greater likelihood of uncontrolled diabetes (Adjusted Odds Ratio (AOR) for ≥3 needs: 1.59, 95% CI: 1.26, 2.00). Of the patients with most frequently occurring unmet social needs, lack of healthcare transportation (AOR: 1.54, 95% CI: 1.22, 1.95) and food insecurity (AOR: 1.50, 95% CI: 1.19, 1.89) had the greatest likelihood of having uncontrolled diabetes, after adjusting for covariates. CONCLUSION: Unmet social needs appear to be linked to a greater likelihood of uncontrolled diabetes. Implications for healthcare systems to screen and address social needs for patients with diabetes are discussed.

Unmet Social Needs and No-Show Visits in Primary Care in a US Northeastern Urban Health System, 2018-2019.

Objectives. To characterize the association between social needs prevalence and no-show proportion and variation in these associations among specific social needs.Methods. In this study, we used results from a 10-item social needs screener conducted across 19 primary care practices in a large urban health system in Bronx County, New York, between April 2018 and July 2019. We estimated the association between unmet needs and 2-year history of missed appointments from 41 637 patients by using negative binomial regression models.Results. The overall no-show appointment proportion was 26.6%. Adjusted models suggest that patients with 1 or more social needs had a significantly higher no-show proportion (31.5%) than those without any social needs (26.3%), representing an 19.8% increase (P < .001). We observed a positive trend (P < .001) between the number of reported social needs and the no-show proportion-26.3% for those with no needs, 30.0% for 1 need, 32.1% for 2 needs, and 33.8% for 3 or more needs. The strongest association was for those with health care transportation need as compared with those without (36.0% vs 26.9%).Conclusions. We found unmet social needs to have a significant association with missed primary care appointments with potential implications on cost, quality, and access for health systems.

Social Risks Among Primary Care Patients in a Large Urban Health System.

INTRODUCTION: Health systems are increasingly interested in addressing the social determinants of health via social risk screening. The objective of this study is to understand the variability in the number and types of social risks overall and in population subgroups among primary care patients routinely screened in a large urban health system. METHODS: Between April and December 2018, a total of 24,633 primary care patients completed a 10-item screener across 19 ambulatory sites within a health system in the Bronx, NY. The prevalence of any social risk and specific social risks was estimated overall and for population subgroups. Wald tests were used to determine statistically significant differences by subgroup. Data were analyzed in winter/spring 2019. RESULTS: Twenty percent of patients presented with at least 1 social risk. The most frequently reported risks included housing quality (6.5%) and food insecurity (6.1%). Middle-aged (30-59 years) respondents (24.7%, 95% CI=23.6%, 25.7%) compared with those aged 18-29 years (17.7%, 95% CI=16.4%, 19.2%, p<0.001), and Medicaid patients (24.8%, 95% CI=24.0%, 25.5%) compared with commercially insured patients (11.8%, 95% CI=11.1%, 12.5%, p<0.001), were more likely to report social risks. The strongest predictor of housing quality risk was residing in public housing (15.1%, 95% CI=13.8%, 16.6%) compared with those not in public housing (5.6%, 95% CI=5.3%, 5.9%, p<0.001). Housing quality was the most frequently reported risk for children (aged <18 years) and older adults (aged ≥70 years), whereas, for middle-aged respondents (30-69 years), it was food insecurity. CONCLUSIONS: There are important differences in the prevalence of overall and individual social risks by subgroup. These findings should be considered to inform clinical care and social risk screening and interventions.