Healthcare Scheduling by Data Mining: Literature Review and Future Directions. Issue 3 (17th September 2012)

• Record Type: Journal Article
• Authors: Rinder, Maria M.; Weckman, Gary; Schwerha, Diana; Snow, Andy; Dreher, Peter A.; Park, Namkyu; Paschold, Helmut; Young, William
• Is Part Of: Journal of healthcare engineering. Volume 3:Issue 3(2012)
• Page Start: 477
• Page End: 502
• Publication Date: 2012-09-17
• Subjects: heuristic methods -- healthcare scheduling -- patient behaviour; Hospital buildings -- Environmental engineering -- Periodicals; Medical technology -- Periodicals; Medical informatics -- Periodicals; 610.28
• DOI: 10.1260/2040-2295.3.3.477
• Languages: English
• ISSNs: 2040-2295

Abstract

Abstract : This article presents a systematic literature review of the application of industrial engineering methods in healthcare scheduling, with a focus on the role of patient behavior in scheduling. Nine articles that used mathematical programming, data mining, genetic algorithms, and local searches for optimum schedules were obtained from an extensive search of literature. These methods are new approaches to solve the problems in healthcare scheduling. Some are adapted from areas such as manufacturing and transportation. Key findings from these studies include reduced time for scheduling, capability of solving more complex problems, and incorporation of more variables and constraints simultaneously than traditional scheduling methods. However, none of these methods modeled no-show and walk-ins patient behavior. Future research should include more variables related to patient and/or environment.