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. 2020 Jul;110(S2):S242-S250.
doi: 10.2105/AJPH.2020.305717.

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

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

Kevin P Fiori et al. Am J Public Health. 2020 Jul.

Abstract

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.

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Figures

FIGURE 1—
FIGURE 1—
No-Show Primary Care Proportion Ratios Comparing No Social Risks to One or More, Increasing Number of Needs, and Specific Social Risk Categories for Patients at an Urban Health System: Bronx, NY, April 2018–July 2019 Note. CI = confidence interval; OR = odds ratio. The ratio of no-show proportions was estimated with a Poisson model. aModel 2 adjusted for age, sex, race/ethnicity, preferred language, payer, area-based poverty, public housing status, and Elixhauser comorbidity score. bModel 3 adjusted for each social need plus model 2 covariates.

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