The effect of a public transportation expansion on no-show appointments

Laura Barrie Smith, Zhiyou Yang, Ezra Golberstein, Peter Huckfeldt, Ateev Mehrotra, Hannah T. Neprash

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Objective: To test whether there were fewer missed medical appointments (“no-shows”) for patients and clinics affected by a significant public transportation expansion. Study setting: A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016. Study design: We used a difference-in-differences research design to compare whether no-show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time. Data extraction methods: We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same-day, urgent care, and canceled appointments. Principal findings: The probability of no-show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: −0.9 to −0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (−1.6 percentage points [95% CI: −2.4 to −0.8] or 9.5% relative to baseline). Conclusions: Improvements to public transit may improve access to health care, especially for people with low incomes.

Original languageEnglish (US)
Pages (from-to)472-481
Number of pages10
JournalHealth services research
Volume57
Issue number3
DOIs
StatePublished - Jun 2022

Bibliographical note

Funding Information:
This article uses proprietary data from an integrated health care delivery system, made available through a data sharing agreement with the University of Minnesota. The authors are grateful to the Clinical and Translational Science Institute at the University of Minnesota for their help in accessing and using the data. The authors also thank Dr. Jean Abraham and Dr. Jason Cao for their helpful comments and suggestions. Laura Barrie Smith and Zhiyou Yang contributed to this work while completing their doctoral studies at the University of Minnesota. Dr. Smith also appreciates support from the Urban Institute.

Publisher Copyright:
© 2021 Health Research and Educational Trust.

Keywords

  • access
  • demand
  • determinants of health
  • health care organizations and systems
  • population health
  • socioeconomic causes of health
  • utilization of services

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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