ArticleHealth systems (Basingstoke, England)2018
Static and dynamic appointment scheduling to improve patient access time.
Article in Health systems (Basingstoke, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Intelligent Patient Appointment Schedules.Healthcare (Basel, Switzerland) · 2026Article
- Comparing service delivery models in Finnish dental care: efficiency of the single-visit approach.BMC oral health · 2025Article
- Data in ambulatory care logistics: What modelers need and what practice can offer.Health care management science · 2025Article
- Research on outpatient capacity planning combining lean thinking and integer linear programming.BMC medical informatics and decision making · 2023Article
- Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review.Journal of healthcare engineering · 2022Review
- Patient's decision and experience in the multi-channel appointment context: An empirical study.Frontiers in public health · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Appointment schedules for outpatient clinics have great influence on efficiency and timely access to health care services. The number of new patients per week fluctuates, and capacity at the clinic varies because physicians have other obligations. However, most outpatient clinics use static appointment schedules, which reserve capacity for each patient type. In this paper, we aim to optimise appointment scheduling with respect to access time, taking fluctuating patient arrivals and unavailabilities of physicians into account. To this end, we formulate a stochastic mixed integer programming problem, and approximate its solution invoking two different approaches: (1) a mixed integer programming approach that results in a static appointment schedule, and (2) Markov decision theory, which results in a dynamic scheduling strategy. We apply the methodologies to a case study of the surgical outpatient clinic of the Jeroen Bosch Hospital. We evaluate the effectiveness and limitations of both approaches by discrete event simulation; it appears that allocating only 2% of the capacity flexibly already increases the performance of the clinic significantly.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.