Decision making methods in political economy of health policy in crises: A systematic review for hospitals

This systematic review examines the methodological consistency of decision-making approaches applied in hospitals during crises, addressing a critical gap in the political economy of health policy. The study aimed to determine whether these methods produce homogeneous conclusions across different crisis types. Following the JBI Evidence Synthesis methodology, a comprehensive search was conducted, in PubMed, Heal-link, PROSPERO, Scopus, and OSF for studies published between 2000 and 2024. Inclusion criteria focused on empirical research applying structured decision-making or efficiency-assessment methods in hospital contexts affected by crises. Data were transformed and analyzed using KNIME workflows, and the included studies were clustered by crisis type: economic, COVID-19, and personal/organizational. A total of eight studies met the inclusion criteria. Data Envelopment Analysis (DEA) was the most frequently applied technique, primarily to evaluate hospital efficiency. Other methods, such as bootstrapping, Taguchi modeling, and VigilanS algorithms, were used less often. Cluster and correlation analyses revealed substantial methodological heterogeneity among studies, indicating limited coherence in analytical frameworks and outcome measures. The findings confirmed the initial hypothesis: decision-making methodologies employed in hospital crises do not yield homogeneous results. The review highlights that resource rationalization was the predominant response strategy during both financial and COVID-19 crises, whereas personal-crisis contexts were underrepresented. These results emphasize the need for context-sensitive, multi-criteria, and integrative decision-making frameworks capable of capturing the complexity of hospital operations under stress. In conclusion, this study provides the first systematic synthesis of decision-making methods in crisis-affected hospital settings. Its findings hold implications for future health policy design, crisis management, and research methodology, supporting the adoption of more diversified analytical models beyond DEA.