Personal, health system, and geosocial disparities in appointment nonadherence at family medicine clinics in southcentral Pennsylvania, United States

Author:

Tuan Wen‐Jan1ORCID,Weems Ashley2ORCID,Leong Shou Ling2ORCID

Affiliation:

1. Department of Family and Community Medicine, and Public Health Sciences, College of Medicine Pennsylvania State University Hershey Pennsylvania USA

2. Department of Family and Community Medicine, College of Medicine Pennsylvania State University Hershey Pennsylvania USA

Abstract

AbstractBackgroundTo assess the relationship between patients' demographic, health system‐related, and geosocial characteristics and the risk of missed appointments among patients in family medicine practice.MethodsThe study was based on a retrospective cross‐sectional design using electronic health records and neighborhood‐level social determents of health metrics linked by geocoded patients' home address. The study population consisted of patients who had a primary care provider and at least one appointment at 14 family medicine clinics in rural and suburban areas in January–December 2022. Negative binomial regression was utilized to examine the impact of personal, health system, and geosocial effects on the risk of no‐shows and same‐day cancellations.ResultsA total of 258,614 appointments were made from 75,182 patients during the study period, including 7.8% no‐show appointments from 20,256 patients. The analysis revealed that individuals in the ethnic minority groups were 1.24–1.65 times more likely to miss their appointments than their White counterpart. Females and English speakers had 14% lower risk for no‐show. A significant increase (32%–64%) in the odds of no‐shows was found among individuals on Medicaid and uninsured. Persons with prior history of no‐shows or same day cancellations were 6%–27% more likely to miss their appointments. The no‐show risk was also higher among people living in areas experiencing socioeconomic disadvantage.ConclusionThe risk of missed appointments is affected by personal, health system, and geosocial contexts. Future efforts aiming to reduce no‐shows could develop personalized interventions targeting the at‐risk populations identified in the analysis.

Publisher

Wiley

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