Process improvement approach to investigate low block utilization of operating rooms: A case study

Omar Ashour, Faisal Aqlan, Anne Pedersen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Lean principles and statistical analysis have been successfully implemented to hospitals and healthcare systems. These principles among other process improvement principles aim to detect and eliminate wastes in the system and its processes. In this paper, lean and statistical analysis were applied to systematically investigate the causes of low operating room (OR) block utilization and recommend solutions to improve the utilization. The study was carried out at a tertiary hospital in Pennsylvania. Root cause analysis has identified the main reasons of delays that impact utilization, i.e., waiting in OR after surgery is done due to bed unavailability, delays in preoperative process due to IV insertion difficulty and unavailable beds, and scheduling problems such as late first case starts and unrealistic surgery schedules. Countermeasures were developed, reevaluating the current scheduling practice and developing a scheduling tool are believed to be the best countermeasures in terms of ease of implementation and impact.

Original languageEnglish (US)
Title of host publication6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
PublisherIEOM Society
Pages680-690
Number of pages11
ISBN (Print)9780985549749, 9780985549756
StatePublished - 2016
EventIEOM Detroit Conference, IEOM 2016 - Southfield, United States
Duration: Sep 23 2016Sep 25 2016

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
ISSN (Electronic)2169-8767

Other

OtherIEOM Detroit Conference, IEOM 2016
Country/TerritoryUnited States
CitySouthfield
Period9/23/169/25/16

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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