Mathematical Programming and Heuristics for Patient Scheduling in Hospitals: A Survey

Mathematical Programming and Heuristics for Patient Scheduling in Hospitals: A Survey

Daniel Gartner (Cardiff University, UK) and Rema Padman (Carnegie Mellon University, USA)
DOI: 10.4018/978-1-5225-3926-1.ch021

Abstract

The effective and efficient treatment of individual patients subject to scarce hospital resources is an increasingly important and challenging problem for decision makers to address. A recent study by the U.S. Bureau of Labor Statistics listed Registered Nursing among the top occupations in terms of job growth until the year 2022 (American Association of Colleges of Nursing (2015)). This growing demand can be explained in part by the large number of aging baby boomers with multi-morbid health conditions who typically require more treatments and longer length of stay in a variety of healthcare delivery settings (Vetrano et al. (2014)). Given the projected demand growth and reduced mobility of elderly patients, efficient operational research methods have to be developed and deployed for optimizing the process of scheduling the treatment of individual patients in highly resource constrained environments. We will henceforth denote this process as ‘patient scheduling' and provide a problem definition and a review of current approaches in the course of this chapter.
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Definition And Characteristics Of Patient Scheduling

A search for definitions for the term ‘patient scheduling’ revealed that there is lack of precision in its definition. An excellent starting point, however, is provided by Hulshof et al. (2012) who state the following: “Based on the appointment scheduling blueprint developed on the tactical level, patient scheduling comprises scheduling of an appointment in a particular time slot for a particular patient. A patient may require multiple appointments on one or more days. Therefore, we distinguish scheduling a single appointment, combination appointments and appointment series.”

Below is a definition of the term ‘patient scheduling’, followed by some examples.

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