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A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement

A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement

Jim Ryan, Barbara Doster, Sandra Daily, Carmen Lewis
Copyright: © 2020 |Pages: 26
ISBN13: 9781799824510|ISBN10: 1799824519|EISBN13: 9781799824527
DOI: 10.4018/978-1-7998-2451-0.ch003
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MLA

Ryan, Jim, et al. "A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement." Hospital Management and Emergency Medicine: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2020, pp. 45-70. https://doi.org/10.4018/978-1-7998-2451-0.ch003

APA

Ryan, J., Doster, B., Daily, S., & Lewis, C. (2020). A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement. In I. Management Association (Ed.), Hospital Management and Emergency Medicine: Breakthroughs in Research and Practice (pp. 45-70). IGI Global. https://doi.org/10.4018/978-1-7998-2451-0.ch003

Chicago

Ryan, Jim, et al. "A Case Study Perspective for Balanced Perioperative Workflow Achievement through Data-Driven Process Improvement." In Hospital Management and Emergency Medicine: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 45-70. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2451-0.ch003

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Abstract

Based on a 143-month longitudinal study of an academic medical center, this paper examines operations management practices of continuous improvement, workflow balancing, benchmarking, and process reengineering within a hospital's perioperative operations. Specifically, this paper highlights data-driven efforts within perioperative sub-processes to balance overall patient workflow by eliminating bottlenecks, delays, and inefficiencies. This paper illustrates how dynamic technological activities of analysis, evaluation, and synthesis applied to internal and external organizational data can highlight complex relationships within integrated processes to identify process limitations and potential process capabilities, ultimately yielding balanced patient workflow through data-driven perioperative process improvement. Study implications and/or limitations are also included.

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