title: Improving Intensive Care Unit and Ward Utilization by Adapting Master Surgery Schedules.
abstract: With increasing organizational and financial pressure on hospitals, each individual surgical treatment has to be reviewed and planned thoroughly. Apart from the expensive operating room facilities, proper staffing and planning of downstream units, like the wards or the intensive care units (ICUs), should be considered as well. In this article, we outline the relationship between a master surgery schedule (MSS), i.e., the assignment of surgical blocks to medical specialties, and the bed demand in the downstream units using an analytical model. By using historical data retrieved from the clinical information system and a patient flow model, we applied a recently developed algorithm for predicting bed demand based on the MSSs for patients of 3 surgical subspecialties of a hospital. Simulations with 3 different MSSs were performed. The impact on the required amount of beds in the downstream units was analyzed. We show the potential improvements of the current MSS considering 2 main goals: leveling workload among days and reduction of weekend utilization. We discuss 2 different MSSs, one decreasing the weekend ICU utilization by 20% and the other one reducing maximum ward bed demand by 7%. A test with 12 months of real-life data validates the results. The application of the algorithm provides detailed insights for the hospital into the impact of MSS designs on the bed demand in downstream units. It allowed creating MSSs that avoid peaks in bed demand and high weekend occupancy levels in the ICU and the ward.
authors.affiliation: From the *Universitaeres Zentrum fuer Gesundheitswissenschaften am Klinikum Augsburg (UNIKA-T), School of Business and Economics, Universitaet Augsburg, Augsburg, Germany; †Klinik fuer Anaesthesiologie, Klinikum rechts der Isar der TU Muenchen, Munich, Germany; and ‡TUM School of Management, Technische Universitaet Muenchen, Munich, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Fügener
authors.forename: Guenther Michael
authors.initials: GM
authors.lastname: Edenharter
authors.forename: Paskal
authors.initials: P
authors.lastname: Kiefer
authors.forename: Ulrike
authors.initials: U
authors.lastname: Mayr
authors.forename: Julian
authors.initials: J
authors.lastname: Schiele
authors.forename: Fabian
authors.initials: F
authors.lastname: Steiner
authors.forename: Rainer
authors.initials: R
authors.lastname: Kolisch
authors.forename: Manfred
authors.initials: M
authors.lastname: Blobner
mesh_terms: D000465:Algorithms; D001071:Appointments and Schedules; D001509:Bed Occupancy / Q000706:statistics & numerical data*; D017598:Efficiency, Organizational; D007362:Intensive Care Units / Q000592:standards*; D015233:Models, Statistical; D009873:Operating Rooms / Q000706:statistics & numerical data*; D016526:Workload