{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T13:44:39Z","timestamp":1777902279148,"version":"3.51.4"},"reference-count":26,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2013,10,18]],"date-time":"2013-10-18T00:00:00Z","timestamp":1382054400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2013,12]]},"abstract":"<jats:p>Patient appointment scheduling (AS) in outpatient clinics is a widely studied subject and plays an important role in facilitating the efficient use of clinical resources and patients\u2019 timely access to quality care. This paper considers two AS systems: open access (OA) and overbooking (OB). Clinics make strategic decisions on selecting an AS system and then make tactical decisions on the efficient or optimal use of the system based on the selection. This study proposes some guidelines for the strategic choice of an AS system. For this purpose, we conduct a discrete-event simulation to compare the two AS systems under various environments. We employ four performance measures for the comparison: overtime work, the proportion of unmet demand, in-clinic waiting times, and the use of appointment time slots. For the analysis, we devise an integrated measure representing a linear combination of the four measures. We divide the analysis into two phases. In the first phase, well-performed OA and OB policies are separately identified, and in the second phase, the two scheduling systems with the identified policies are compared. We find overbooking is more robust to various clinic environments and performs better than open access in general. Along with that result, we additionally suggest some rules for determining best open access and overbooking policies.<\/jats:p>","DOI":"10.1177\/0037549713505332","type":"journal-article","created":{"date-parts":[[2013,10,18]],"date-time":"2013-10-18T21:32:37Z","timestamp":1382131957000},"page":"1459-1473","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":40,"title":["A simulation study of appointment scheduling in outpatient clinics: Open access and overbooking"],"prefix":"10.1177","volume":"89","author":[{"given":"Sangbok","family":"Lee","sequence":"first","affiliation":[{"name":"The Ernest & Julio Gallo Management Program, University of California, Merced, USA"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Daiki","family":"Min","sequence":"additional","affiliation":[{"name":"College of Business Administration, Ewha Womans University, Seoul, Korea"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Jong-hyun","family":"Ryu","sequence":"additional","affiliation":[{"name":"College of Business Management, Hongik University, Sejong, Korea"}],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Yuehwern","family":"Yih","sequence":"additional","affiliation":[{"name":"School of Industrial Engineering, Purdue University, West Lafayette, IN, USA"}],"role":[{"role":"author","vocab":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2013,10,18]]},"reference":[{"key":"bibr1-0037549713505332","volume-title":"NHE projections 2008\u20132018","author":"The Office of the Actuary in the Centers for Medicare and Medicaid Services","year":"2009"},{"key":"bibr2-0037549713505332","author":"Institute of Medicine","year":"2007","journal-title":"Business Week"},{"key":"bibr3-0037549713505332","doi-asserted-by":"publisher","DOI":"10.1080\/07408170802165880"},{"key":"bibr4-0037549713505332","unstructured":"Greenblatte J. 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