Accounting for Inpatient Wards When Developing Master Surgical Schedules

Vanberkel, Peter T. and Boucherie, Richard J. and Hans, Erwin W. and Hurink, Johann L. and Lent van, Wineke A.M. and Harten van, Wim H. (2011) Accounting for Inpatient Wards When Developing Master Surgical Schedules. Anesthesia & Analgesia, 112 (6). pp. 1472-1479. ISSN 0003-2999

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Abstract:	Background:As the demand for health care services increases, the need to improve patient flow between departments has likewise increased. Understanding how the master surgical schedule (MSS) affects the inpatient wards and exploiting this relationship can lead to a decrease in surgery cancellations, a more balanced workload, and an improvement in resource utilization. We modeled this relationship and used the model to evaluate and select a new MSS for a hospital. Methods:An operational research model was used in combination with staff input to develop a new MSS. A series of MSSs were proposed by staff, evaluated by the model, and then scrutinized by staff. Through iterative modifications of the MSS proposals (i.e., the assigned operating time of specialties), insight is obtained into the number, type, and timing of ward admissions, and how these affect ward occupancy. Results:After evaluating and discussing a number of proposals, a new MSS was chosen that was acceptable to operating room staff and that balanced the ward occupancy. After implementing the new MSS, a review of the bed-use statistics showed it was achieving a balanced ward occupancy. The model described in this article gave the hospital the ability to quantify the concerns of multiple departments, thereby providing a platform from which a new MSS could be negotiated. Conclusion:The model, used in combination with staff input, supported an otherwise subjective discussion with quantitative analysis. The work in this article, and in particular the model, is readily repeatable in other hospitals and relies only on readily available data
Item Type:	Article
Copyright:	© 2011 International Anesthesia Research Society
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS) Management and Governance (SMG)
Research Chair:	Operations Management and Logistics (OMPL)
Research Group:	Stochastic Operations Research (SOR) Discrete Mathematics and Mathematical Programming (DMMP) Industrial Engineering & Business Information Systems (IEBIS) Health Technology & Services Research (HTSR)
Link to this item:	http://purl.utwente.nl/publications/77099
Official URL:	http://dx.doi.org/10.1213/ANE.0b013e3182159c2f
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