Purpose: The outbreak of the COVID-19 pandemic has significantly impacted healthcare systems, presenting unforeseen challenges that necessitated the implementation of change management strategies to adapt to the new contextual conditions. This study aims to analyze organizational changes within the total hip replacement (THR) surgery pathway at multiple levels, including macro, meso and micro. It employs data triangulation from various sources to gauge the complexity of the change process and comprehend how multi-level decision-making influenced an unexpected shift. Design/methodology/approach: A multicentric, single in-depth case study was conducted using a mixed-methods approach. Data sources included patient-reported outcome measures specific to the THR pathway and carefully structured in-depth interviews administered to managers and clinicians in two healthcare organizations serving the same population. Findings: Decisions made at the macro level resulted in an overall reduction in surgical activities. Organizational changes at the meso level led to a complete cessation or partial reorganization of activities. Micro-level actions for change and adaptation revealed diverse and fragmented change management strategies. Practical implications: Organizations with segmented structures may require a robust and structured department for coordinating change management responses to prevent the entire system from becoming stuck in the absorptive phase of change. However, it is important to recognize that absorptive solutions can serve as a starting point for genuine innovations in change management. Originality/value: The utilization of data triangulation enables the authors to visualize how specific changes implemented in response to the pandemic have influenced the observed outcomes. From a managerial perspective, it provides insights into how future innovations could be introduced.
CITATION STYLE
Da Ros, A., Pennucci, F., & De Rosis, S. (2024). Unlocking organizational change: a deep dive through a data triangulation in healthcare. Management Decision. https://doi.org/10.1108/MD-06-2023-0898
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