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.

Lessons from Launching the Diabetes Prevention Program in a Large Integrated Health Care Delivery System: A Case Study.

There is urgent need for health systems to prevent diabetes. To date, few health systems have implemented the evidence-based Diabetes Prevention Program (DPP), and the few that have mostly partnered with community-based organizations to implement the program. Given the recent decision by the Centers for Medicare & Medicaid Services to reimburse for diabetes prevention, there is likely much interest in how such programs can be implemented within large health systems or how community partnerships can be expanded to support DPP implementation. Beginning in 2010, Montefiore Health System (MHS), a large health care system in the Bronx, NY, partnered with the Young Men's Christian Association (YMCA) of Greater New York to deliver the YMCA's DPP. Over 4 years, 1390 referrals to YMCA's DPP were made; 287 participants attended ≥3 classes, and average weight loss was 3.4%. Because of increased patient demand and internal capacity, MHS assumed responsibility for DPP implementation in May 2015. Fully integrating the program within the health system took 5-6 months, including configuring electronic health record templates/reports, hiring a coordinator, and creating clinical referral workflows/training guides. Billing workflows were designed for risk-based contracts. In the first 11 months of implementation, 1277 referrals were made, and referrals increased over time. Twenty-four class cycles were initiated, and 282 patients began attending classes. Average weight loss among 61 graduates from the Summer/Fall 2015 wave of MDPP classes was 3.8%. Additional opportunities for expansion include training allied health staff, providing patient incentives, increasing master trainer capacity, offering DPP to employees, and securing reimbursement.

Increasing Referrals to a YMCA-Based Diabetes Prevention Program: Effects of Electronic Referral System Modification and Provider Education in Federally Qualified Health Centers.

INTRODUCTION: The Diabetes Prevention Program has been translated to community settings with varying success. Although primary care referrals are used for identifying and enrolling eligible patients in the Diabetes Prevention Program, little is known about the effects of strategies to facilitate and sustain eligible patient referrals using electronic health record systems. METHODS: To facilitate and sustain patient referrals, a modification to the electronic health record system was made and combined with provider education in 6 federally qualified health centers in the Bronx, New York. Referral data from April 2012 through November 2014 were analyzed using segmented regression analysis. RESULTS: Patient referrals increased significantly after the modification of the electronic health record system and implementation of the provider education intervention. Before the electronic system modification, 0 to 2 patients were referred per month. During the following year (September 2013 through August 2014), which included the provider education intervention, referrals increased to 1 to 9 per month and continued to increase to 5 to 11 per month from September through November 2014. CONCLUSIONS: Modification of an electronic health record system coupled with a provider education intervention shows promise as a strategy to identify and refer eligible patients to community-based Diabetes Prevention Programs. Further refinement of the electronic system for facilitating referrals and follow-up of eligible patients should be explored.

Combining clinical and population-level data to understand the health of neighborhoods.

From February through December 2012, we examined responses to health behavior questions integrated into the electronic medical record of primary care centers in the Bronx, New York in the context of New York City Community Health Survey data. We saw a higher proportion of unhealthy behaviors among patients than among the neighborhood population. Analyzing clinical data in the neighborhood context can better target at-risk populations.