Can administrative data replace patient survey data in the monitoring of waiting time for community-based specialist care?

Osnat Luxenburg, Vicki Myers, Arnona Ziv, Yair Goldberg, Mor Saban, Shuli Brammli-Greenberg, Rachel Wilf-Miron

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Waiting time (WT) is commonly measured via both computerized systems and patient surveys. Comparison between these types of data can reveal important issues about the relationship between self-reported survey data and objective administrative measurement of WT. Aim: To compare national wait time data from two sources: patients’ reported waiting time for community specialist appointments in Israel, with waiting time calculated from computerized administrative data, across specialties and geographic areas. Methods: Median WT for > 1 million appointments from over 6,000 physician practices in 5 specialties (ophthalmology, gynecology, otolaryngology, orthopedics, dermatology) were computed via an algorithm, for “specific” and “any” physician in the region, in December 2018. Results were compared with WT reported in a representative national sample survey of 3508 adults during August-December 2018. Results: Similar trends in WT were seen using both methods, with the longest wait times in dermatology, and in the Southern region. Correlation between survey and administrative data was high (r = 0.9, p < 0.01), with greater correlation for specific compared to any physician scenario. Survey respondents reported longer waiting times compared to administrative data. Conclusions: Patient survey data reflected trends in waiting time for community specialists derived from objective administrative data. Routine computation of WT from administrative data can save time and resources invested in patient surveys and provide a continuous, accurate and timely evaluation of trends. Surveys can provide deeper understanding of patient experience. Alternate use of both platforms provides a better understanding of access to care.

Original languageEnglish
JournalHealth Services and Outcomes Research Methodology
DOIs
StateAccepted/In press - 2022

Keywords

  • Administrative data
  • Patient survey
  • Primary care
  • Specialist
  • Waiting time

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