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Managing outpatient flow via an artificial intelligence enabled solution

Author

Listed:
  • Ling Li
  • Fatou Diouf
  • Anjee Gorkhali

Abstract

An intelligent decision support information system is applied to develop an artificial intelligence (AI)‐driven solution to reduce patient waiting time in a hospital without an appointment system to improve healthcare service quality. The bottlenecks were identified, and then the healthcare service process was reengineered through the proposed shortest‐consultation time (SCT) model to increase the capacity for serving patients and the synchronization between capacity and patient arrival patterns. The study made several meaningful observations: (1) It is feasible to apply an AI‐driven solution to reduce patient waiting time in a hospital with no appointment system to improve healthcare service quality; (2) analytical models are helpful in identifying characteristics of patient flow problems; (3) the implementation of a few performance factors gives most of the improvements, and (4) theory of constraint (TOC) is a method that can be applied to improve patient service qualification.

Suggested Citation

  • Ling Li & Fatou Diouf & Anjee Gorkhali, 2022. "Managing outpatient flow via an artificial intelligence enabled solution," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 415-427, May.
    • Handle: RePEc:bla:srbeha:v:39:y:2022:i:3:p:415-427
    DOI: 10.1002/sres.2870
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    References listed on IDEAS

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    1. Li, L. X. & Benton, W. C., 1996. "Performance measurement criteria in health care organizations: Review and future research directions," European Journal of Operational Research, Elsevier, vol. 93(3), pages 449-468, September.
    2. Suresh Chand & Herbert Moskowitz & John Norris & Steve Shade & Deanna Willis, 2009. "Improving patient flow at an outpatient clinic: study of sources of variability and improvement factors," Health Care Management Science, Springer, vol. 12(3), pages 325-340, September.
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