An IP-based healthcare provider shift design approach to minimize patient handoffs
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- 作者：Pooyan Kazemian (1)
Yue Dong (2)
Thomas R. Rohleder (3)
Jonathan E. Helm (4)
Mark P. Van Oyen (1) - 关键词：Patient handoffs ; Scheduling ; Integer programming ; ACGME duty ; hour standards ; Shift design ; Shift assignment
- 刊名：Health Care Management Science
- 出版年：2014
- 出版时间：March 2014
- 年：2014
- 卷：17
- 期：1
- 页码：1-14
- 全文大小：958 KB
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Yue Dong (2)
Thomas R. Rohleder (3)
Jonathan E. Helm (4)
Mark P. Van Oyen (1)
1. Department of Industrial and Operations Engineering, University of Michigan, 1205 Beal Ave., Ann Arbor, MI, 48109, USA
2. Multidisciplinary Simulation Center, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
3. Department of Health Sciences Research, Center for the Science of Health Care Delivery, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
4. Kelley School of Business, Indiana University, 1309 East Tenth St., Bloomington, IN, 47405, USA - ISSN：1572-9389
文摘
The new Accreditation Council for Graduate Medical Education (ACGME) duty-hour standards for residents and fellows went into effect in 2011. These regulations were designed to reduce fatigue-related medical errors and improve patient safety. The new shift restrictions, however, have led to more frequent transitions in patient care (handoffs), resulting in greater opportunity for communication breakdowns between caregivers, which correlate with medical errors and adverse events. Recent research has focused on improving the quality of these transitions through standardization of the handoff protocols; however, no attention has been given to reducing the number of transitions in patient care. This research leverages integer programming methods to design a work shift schedule for trainees that minimizes patient handoffs while complying with all ACGME duty-hour standards, providing required coverage, and maintaining physician quality of life. In a case study of redesigning the trainees-schedule for a Mayo Clinic Medical Intensive Care Unit (MICU), we show that the number of patient handoffs can be reduced by 23?% and still meet all required and most desired scheduling constraints. Furthermore, a 48?% reduction in handoffs could be achieved if only the minimum required rules are satisfied.