| A probabilistic model for predicting the probability of no-show in hospital appointments. | |
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MedLine Citation:
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PMID: 21286819 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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The number of no-shows has a significant impact on the revenue, cost and resource utilization for almost all healthcare systems. In this study we develop a hybrid probabilistic model based on logistic regression and empirical Bayesian inference to predict the probability of no-shows in real time using both general patient social and demographic information and individual clinical appointments attendance records. The model also considers the effect of appointment date and clinic type. The effectiveness of the proposed approach is validated based on a patient dataset from a VA medical center. Such an accurate prediction model can be used to enable a precise selective overbooking strategy to reduce the negative effect of no-shows and to fill appointment slots while maintaining short wait times. |
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Authors:
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Adel Alaeddini; Kai Yang; Chandan Reddy; Susan Yu |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-2-1 |
Journal Detail:
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Title: Health care management science Volume: - ISSN: 1386-9620 ISO Abbreviation: - Publication Date: 2011 Feb |
Date Detail:
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Created Date: 2011-2-2 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9815649 Medline TA: Health Care Manag Sci Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Industrial & Systems Engineering, Wayne State University, Detroit, MI, 48202, USA, adel.alaeddini@gmail.com. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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