Bi-criteria appointment scheduling of patients with heterogeneous service sequences

Saremi, Alireza; Jula, Payman; ElMekkawy, Tarek Y.; Wang, Gary G.

doi:10.1016/j.eswa.2015.01.013

Cited by 30 publications

(38 citation statements)

References 39 publications

(48 reference statements)

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“…Although various patient routings are considered, they consider this as given in their model. Saremi et al [44] address the appointment scheduling of patients with various service sequences as well. They determine the appointment time of each patient in order to optimize a combination of waiting time and completion time.…”

Section: Multi-disciplinary Schedulingmentioning

confidence: 99%

“…Simulation is used to analyze the performance of multiple clinics under a variety of scenarios, including various appointment rules and appointment schedules [9,18,23,25,31,40,43,44], which show significant improvements compared to the current practice in partnering health care centers.…”

Section: Multi-disciplinary Schedulingmentioning

confidence: 99%

“…Both local search methods [42,44] and other meta-heuristics [33] are applied to develop patient schedules, as well as approximate stochastic approaches [30] and simple planning rules [22,41].…”

Section: Multi-disciplinary Schedulingmentioning

confidence: 99%

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Stochastic integer programming for multi-disciplinary outpatient clinic planning

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Hans

2017

Health Care Manag Sci

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Scheduling appointments in a multi-disciplinary clinic is complex, since coordination between disciplines is required. The design of a blueprint schedule for a multidisciplinary clinic with open access requirements requires an integrated optimization approach, in which all appointment schedules are jointly optimized. As this currently is an open question in the literature, our research is the first to address this problem. This research is motivated by a Dutch hospital, which uses a multi-disciplinary cancer clinic to communicate the diagnosis and to explain the treatment plan to their patients. Furthermore, also regular patients are seen by the clinicians. All involved clinicians therefore require a blueprint schedule, in which multiple patient types can be scheduled. We design these blueprint schedules by optimizing the patient waiting time, clinician idle time, and clinician overtime. As scheduling decisions at multiple time intervals are involved, and patient routing is stochastic, we model this system as a stochastic integer program. The stochastic integer program is adapted for and solved with a sample Numerical experiments evaluate the performance of the sample average approximation approach. We test the suitability of the approach for the hospital's problem at hand, compare our results with the current hospital schedules, and present the associated savings. Using this approach, robust blueprint schedules can be found for a multi-disciplinary clinic of the Dutch hospital.

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Section: Multi-disciplinary Schedulingmentioning

confidence: 99%

Section: Multi-disciplinary Schedulingmentioning

confidence: 99%

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Stochastic integer programming for multi-disciplinary outpatient clinic planning

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Vliegen

Hans

2017

Health Care Manag Sci

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“…Today, computer programs and telecommunications are offered to improve the quality of health care services in developing countries (8). Online appointment booking systems, because of their flexibility in planning and time efficienct (9)(10)(11)(12)(13) are a successful solution for physicians and patients in setting clinical appointments (13). This system, has advantages and features, including access to the system at any Copyright © 2018, Shiraz E-Medical Journal.…”

Section: Introductionmentioning

confidence: 99%

“…This system, has advantages and features, including access to the system at any Copyright © 2018, Shiraz E-Medical Journal. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited time and any place, allowing the user to see the physicians' appointments (9), selection of the desired option, editing the recorded information, more favorable relationship between physician and patient, improvement of the efficiency and effectiveness of care (5), cost reduction (11)(12)(13)(14), reduction of the number and volume of employees (7), saving patient information for use in subsequent appointments (11), and reduction of the number of missed appointments (9,11,(13)(14)(15)(16)(17)(18). However, despite the importance of this system, a few studies have been done on its evaluation and existing researches in this field have investigated topics, such as designing a web-based appointment system (19), patient satisfaction of online appointment booking systems (4,20), development of information technology acceptance model for an online appointment booking system in hospitals (21)(22)(23), implementation and use of the online appointment booking system in clinics (15,20), and improving the management of appointments (24,25).…”

Section: Introductionmentioning

confidence: 99%