Key performance indicators for hospital planning and construction: a systematic review and meta-analysis

钥匙(锁) 荟萃分析 系统回顾 过程管理 管理科学 计算机科学 业务 梅德林 政治学 医学 工程类 计算机安全 内科学 法学
作者
Wenque Liu,Albert P.C. Chan,Man Wai Chan,Amos Darko,Goodenough D. Oppong
出处
期刊:Engineering, Construction and Architectural Management [Emerald Publishing Limited]
标识
DOI:10.1108/ecam-10-2023-1060
摘要

Purpose The successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC). Design/methodology/approach The KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed. Findings Results indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings. Originality/value There is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.

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