Operating theatre time utilisation and elective surgery cancellations: A one-month review in a Nigerian teaching hospital
Introduction Globally, healthcare systems face rising costs, inefficiencies, and inequitable resource allocation. In Nigeria, underfunding and systemic inefficiencies limit access to surgical care, preventing many patients from receiving necessary procedures. Operating theatres (OTs), which are...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Orapuh, Inc.
2024-12-01
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| Series: | Orapuh Journal |
| Subjects: | |
| Online Access: | https://orapuh.org/ojs/ojs-3.1.2-4/index.php/orapj/article/view/324 |
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| Summary: | Introduction
Globally, healthcare systems face rising costs, inefficiencies, and inequitable resource allocation. In Nigeria, underfunding and systemic inefficiencies limit access to surgical care, preventing many patients from receiving necessary procedures. Operating theatres (OTs), which are among the most resource-intensive hospital units, are central to improving surgical care but are often underutilised. Auditing OT processes is essential for identifying inefficiencies and supporting strategies to enhance utilisation and reduce cancellations.
Purpose
This study aimed to evaluate OT time utilisation and surgical case cancellations in a Nigerian teaching hospital over one month, focusing on first-case tardiness, prediction bias, turnover time, and cancellations.
Methods
A prospective cross-sectional study was conducted to analyse observational data from OT processes, including first-case tardiness, prediction bias, turnover time, cancellations, and raw utilisation. Hierarchical multiple regression was used to assess the predictive impact of these factors on OT utilisation.
Results
Out of 133 scheduled surgeries, 59 (44.4%) were cancelled. The leading causes of cancellation were patient non-attendance (33.9%) and time constraints (27.1%). Raw OT utilisation was 55.4%, with general surgery recording the highest utilisation (81.5%). First-case tardiness (mean delay: 133.7 ± 46.4 minutes) and prediction bias (mean: 49.9 ± 44.3 minutes) significantly predicted OT utilisation (B = -0.219, p = 0.007; B = 0.305, p = 0.005, respectively). Delayed starts accounted for 5,886 minutes of lost time.
Conclusions
Addressing patient non-attendance through financial counselling and automated reminders, standardising workflows, and enhancing scheduling accuracy with digital tools can reduce delays and cancellations, thereby optimising resource use.
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| ISSN: | 2644-3740 |