Monitoring operating room performance with control charts: findings from a Greek public hospital

Author:

Tsironis Loukas K1ORCID,Dimitriadis Sotirios G2,Kehris Evangelos2

Affiliation:

1. Department of Business Administration, University of Macedonia, 156 Egnatia Street, 546 36, Thessaloniki, Greece

2. Department of Business Administration, International Hellenic University, Terma Magnisias, 621 24, Serres, Greece

Abstract

Abstract Objective To describe the development and demonstrate the use of a statistical framework based on statistical quality control (SQC) in order to monitor the performance of operating rooms (ORs). Design Data related to scheduled surgical operations have been collected from the information system of an existing Greek hospital. The data that contain the anesthesia and operation start and completion times of the operations carried out in the 14 ORs of the hospital are analyzed using control p-charts and hypotheses testing. The results obtained provide crucial information to health-care managers. Setting A large Greek public hospital. Participants Real-world data captured on daily basis from January 2015 to November 2017. Intervention The proportion of the idle time of an OR over its total available time is proposed as an OR key performance index. We present two directions of data monitoring and analysis: one that uses control p-charts and a second based on hypotheses testing. The improved Laney’s p΄-chart and the Laney’s approach for cross-sectional data are employed in order to overcome overdispersion that affects OR idle time data. Results The proposed methodology allows hospital management (i) to monitor the percentage of the idle time of an operating room through time and (ii) to identify the ORs that demonstrate exceptionally high or low percentage of idle time at a given period of time. Conclusion SQC charts are simple, yet powerful tools that may support the hospital management in monitoring OR performance and decision-making. The development of a dedicated management information system that automatically captures the required data and constructs the corresponding control charts would support effectively managerial decision-making.

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health,Health Policy,General Medicine

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