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Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking

  • Systems-Level Quality Improvement
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

An Author Correction to this article was published on 06 March 2018

This article has been updated

Abstract

The Veterans Health Administration (VHA) is plagued by abnormally high no-show and cancellation rates that reduce the productivity and efficiency of its medical outpatient clinics. We address this issue by developing a dynamic scheduling system that utilizes mobile computing via geo-location data to estimate the likelihood of a patient arriving on time for a scheduled appointment. These likelihoods are used to update the clinic’s schedule in real time. When a patient’s arrival probability falls below a given threshold, the patient’s appointment is canceled. This appointment is immediately reassigned to another patient drawn from a pool of patients who are actively seeking an appointment. The replacement patients are prioritized using their arrival probability. Real-world data were not available for this study, so synthetic patient data were generated to test the feasibility of the design. The method for predicting the arrival probability was verified on a real set of taxicab data. This study demonstrates that dynamic scheduling using geo-location data can reduce the number of unused appointments with minimal risk of double booking resulting from incorrect predictions. We acknowledge that there could be privacy concerns with regards to government possession of one’s location and offer strategies for alleviating these concerns in our conclusion.

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Change history

  • 06 March 2018

    The original version of this article unfortunately contained a mistake. The name of Matthew Gerber was incorrectly spelled as Mathew Gerber. The correct spelling is now presented correctly in this correction article.

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Funding

This research was sponsored by the MITRE Corporation, MITRE Innovation Program number EPF-15-00418, Program Manager: Dr. N. Peter Whitehead.

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Authors and Affiliations

  1. Department of Systems and Information Engineering, University of Virginia, 151 Engineer’s Way, Charlottesville, VA, 22904, USA

    Stephen Adams, William T. Scherer, K. Preston White Jr., Jason Payne, Oved Hernandez & Mathew S. Gerber

  2. Systems Engineering Technical Center, The Mitre Corporation, McClean, VA, USA

    N. Peter Whitehead

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  1. Stephen Adams
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  2. William T. Scherer
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  3. K. Preston White Jr.
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  4. Jason Payne
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  6. Mathew S. Gerber
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Correspondence to Stephen Adams.

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All authors declare that they have no conflicts of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

A correction to this article is available online at https://doi.org/10.1007/s10916-018-0924-7.

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Adams, S., Scherer, W.T., White, K.P. et al. Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking. J Med Syst 41, 182 (2017). https://doi.org/10.1007/s10916-017-0815-3

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