Measuring geographical disparities in waiting times for community-based specialist care - a novel statistical application
Havi Murad, Vicki Myers, Arnona Ziv, Rachel Wilf-Miron, Osnat Luxenburg

TL;DR
This paper introduces a new statistical method to measure and compare waiting times for dermatology care across different regions in Israel from 2019 to 2023.
Contribution
The study presents a novel application of piecewise quantile regression to analyze geographical disparities in healthcare waiting times.
Findings
Waiting times increased significantly after the peak of the COVID pandemic, especially in Tel Aviv and J&S regions.
The statistical model successfully predicted 2024 waiting times based on historical data.
Geographical disparities in waiting times highlight the need for targeted resource planning to improve healthcare efficiency.
Abstract
Gaps in provision of healthcare by geographical location have been demonstrated around the world. To detect disparities in waiting times (WT), methods are required for accurate comparison. This study sought to demonstrate a novel statistical application to assess geographical differences in WT and time trends for community dermatologists in Israel between 2019 and 2023. WT were measured using available appointments and actual visits for all dermatologists in all four Israeli Health Maintenance Organizations (HMO). Piecewise quantile regressions were conducted for two periods: 2019–2021 and 2022–2023. Additive and multiplicative models estimated absolute and relative differences in median WT between regions. Expected WT, time trends, and differences from the national level were calculated. Validation of the statistical model was conducted on 2024 data. Between 2019 and 2021, median…
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Taxonomy
TopicsHealthcare Operations and Scheduling Optimization · Healthcare Policy and Management · Hospital Admissions and Outcomes
