Approximate dynamic programming approaches for appointment scheduling with patient preferences.
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future po...
| Publicado en: | Artificial Intelligence in Medicine Vol. 85; pp. 16 - 26 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Apr2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=128516020&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128516020 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09333657 3HY jtl: Artificial Intelligence in Medicine issn: 09333657 maglogo: N pubinfo: dt: Apr2018 vid: 85 pid: 1004 pub: Elsevier B.V. artinfo: ui: 128516020 128516020 NLM29482960 128516020 10.1016/j.artmed.2018.02.001 NLM29482960 128516020 ppf: 16 ppct: 10 formats: tig: atl: Approximate dynamic programming approaches for appointment scheduling with patient preferences. aug: au: Li, Xin Wang, Jin Fung, Richard Y.K. affil: Research Center for Modeling and Optimization of Complex Management Systems, College of Management, Shenzhen University, 3688 Nanhai Road, Shenzhen, Guangdong, China sug: subj: Patients Artificial Intelligence Outpatient Service Administration Ambulatory Care Appointments and Schedules Patient Satisfaction Computer Simulation Systems Analysis Human Time Factors Probability Organizational Efficiency Workload Validation Studies Comparative Studies Evaluation Research Multicenter Studies ab: During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future possible requests is also necessary for a successful appointment system. This paper proposes a Markov decision process model for optimizing the scheduling of sequential appointments with patient preferences. In contrast to existing models, the evaluation of a booking decision in this model focuses on the extent to which preferences are satisfied. Characteristics of the model are analysed to develop a system for formulating booking policies. Based on these characteristics, two types of approximate dynamic programming algorithms are developed to avoid the curse of dimensionality. Experimental results suggest directions for further fine-tuning of the model, as well as improving the efficiency of the two proposed algorithms. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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