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Health Care Management Science

, Volume 14, Issue 2, pp 146–157 | Cite as

A probabilistic model for predicting the probability of no-show in hospital appointments

  • Adel Alaeddini
  • Kai Yang
  • Chandan Reddy
  • Susan Yu
Article

Abstract

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.

Keywords

Logistic regression Beta distribution Bayesian inference Healthcare Scheduling 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Adel Alaeddini
    • 1
  • Kai Yang
    • 1
  • Chandan Reddy
    • 2
  • Susan Yu
    • 3
  1. 1.Department of Industrial & Systems EngineeringWayne State UniversityDetroitUSA
  2. 2.Department of Computer ScienceWayne State UniversityDetroitUSA
  3. 3.John D Dingell VA Medical CenterDetroitUSA

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