Implementing Algorithms to Reduce Ward Occupancy Fluctuation Through Advanced Planning

Peter T. Vanberkel*, Richard Boucherie, Erwin W. Hans, Johann L. Hurink, Wineke A.M. van Lent, Wim H. van Harten

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

As with many hospitals, NKI-AVL is eager to improve patient access
through intelligent capacity investments. To this end, the hospital expanded its
operating capacity from five to six operating rooms (ORs) and redesigned their
master surgical schedule (MSS) in an effort to improve utilization and decrease
hospital-wide congestion; an MSS is a cyclical schedule specifying when surgical
specialties operate. Designing an efficient MSS is a complex task, requiring
commitment and concessions on the part of competing stakeholders. There are many restrictions which need to be adhered to, including limited specialized equipment and physician availability. These restrictions are, for the most part, known in advance. The relationship between the MSS and the ward, however, is not known in advance and is plagued with uncertainties. For example, it may be known which patient type will be admitted to the ward after surgery; however, the number of patients changes from week to week, and it is not known with certainty how long each patient will stay in the hospital. Inpatient wards, furthermore, are one of the most expensive hospital resources and can be a major source of hospital congestion, as many departments rely on inpatient wards to receive and treat their patients prior to discharge from the hospital (e.g., the emergency department). This congestion leads to long waiting times for patients, patients receiving the wrong level of care, and extended lengths of stay for patients. Well-designed surgical schedules which take into account inpatient ward resources lead to reduced cancellations and higher and balanced utilization. We observed that peaks in the ward occupancy are particularly dependent on the MSS, and, as a result, ward occupancies can be leveled through careful MSS design. Avoiding peaks and leveling ward occupancy across weekdays makes staff scheduling easier and limits the risk of exceeding capacity, which causes congestion and perpetuates inefficiencies throughout the hospital. Working with NKI-AVL we developed an operations research model to support the redesign of theirMSS. The redesigned MSS improved the use of existing ward resources, thereby allowing an additional operating room to be built without additional investments in ward capacity. A post implementation review of bed use statistics validated our model’s projections. The success of the project served as proof-of-concept for our model, which has since been applied in several other hospitals.
Original languageEnglish
Title of host publicationHandbook of Healthcare Logistics
Subtitle of host publicationBridging the Gap between Theory and Practice
PublisherSpringer
Chapter8
Pages129-150
Number of pages22
ISBN (Electronic)978-3-030-60212-3
ISBN (Print)978-3-030-60211-6
DOIs
Publication statusPublished - 30 Mar 2021

Publication series

NameInternational Series in Operations Research & Management Science
PublisherSpringer
Volume302
ISSN (Print)0884-8289
ISSN (Electronic)2214-7934

Keywords

  • Healthcare planning
  • Operations Management
  • Operations Research and Management Science (OR/MS)
  • Operations Research

Fingerprint Dive into the research topics of 'Implementing Algorithms to Reduce Ward Occupancy Fluctuation Through Advanced Planning'. Together they form a unique fingerprint.

Cite this