Digital transformation in healthcare operations: A guide to the adoption of emerging technologies

Healthcare requires continuous innovation to address rising costs, infrastructure challenges, and global health threats. In this context, digital transformation, enabled by emerging technologies, has become essential. However, this anticipated transformation has yet to fully materialize. Despite the growing interest, current research remains fragmented: case studies explore these technologies in specific operational scenarios, while literature reviews offer broad overviews without addressing their functional implementation in healthcare systems. This study bridges this gap by classifying technological applications found in literature (2019-2024), thereby developing a database of 1084 practices focused on healthcare operations management. Drawing on the Resource-Based View and Contingency Theory, these practices combine three key components: the technological resources employed, the specific implementation contexts, defined by levels of care, healthcare functions, and health categories, and their resulting impacts. Using the FP-Growth algorithm, this research identifies recurrent “technology–context–outcome” patterns, thus deriving a set of optimal contingent configurations that may represent potential future best practices. Building on these findings, a maturity matrix is developed to categorize emerging technologies into four overarching groups (leading, maturing, niche, and lagging) according to their current and prospective integration across healthcare functions. Finally, five propositions formalize the contextual relationships linking technologies, functions, and specific performance outcomes.