Daily surgery caseload prediction: towards improving operating theatre efficiency.

ABSTRACT:

Background

In many hospitals, operating theatres are not used to their full potential due to the dynamic nature of demand and the complexity of theatre scheduling. Theatre inefficiencies may lead to access block and delays in treating patients requiring critical care. This study aims to employ operating theatre data to provide decision support for improved theatre management.

Method

Historical observations are used to predict long-term daily surgery caseload in various levels of granularity, from emergency versus elective surgeries to clinical specialty-level demands. A statistical modelling and a machine learning-based approach are developed to estimate daily surgery demand. The statistical model predicts daily demands based on historical observations through weekly rolling

SUBMITTER: Hassanzadeh H 

PROVIDER: S-EPMC9172609 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature