Digital transformation in healthcare operations
A guide to the adoption of emerging technologies
Bibliographic Data
| ID | 11238307 |
|---|---|
| Authors | Gianluca Aquilone (University of Salerno), Antonello Cammarano (0000-0002-7922-5864, University of Salerno, corresponding author), Vincenzo Varriale (0000-0003-4382-7350, University of Salerno), Mauro Caputo (0000-0003-3500-4290, University of Salerno) |
| Year | 2026 |
| Volume | 86 |
| Pages | 103319 |
| Publication date | 2026-06-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Technology in Society (JOURNAL) |
| Journal identifiers | ISSN: 0160-791X • E-ISSN: 1879-3274 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.techsoc.2026.103319 |
| OpenAlex | W7138846974 |
| Language | EN |
| References cited | 77 |
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.
Digital health · Digital transformation · Emerging markets · Emerging technologies · Health care · Transformation (genetics · Digital Transformation in Industry · Educational Leadership and Innovation · Healthcare Operations and Scheduling Optimization
The Contingency Theory of Organizations
Beyond Adoption
Digital transformation in healthcare
Does digital transformation improve the firm’s performance? From the perspective of digitalization paradox and managerial myopia
From Triple to Quadruple Aim
Using Theory Elaboration to Make Theoretical Advancements
Scientific procedures and rationales for systematic literature reviews (SPAR‐4‐SLR)
Diffusion of Innovations in Service Organizations
Firm Resources and Sustained Competitive Advantage
The promise of digital healthcare technologies
IoT in healthcare
How to search for literature in systematic reviews and meta-analyses
Healthcare 4.0 digital applications
Healthcare analytics
Discovering technological opportunities of cutting-edge technologies
The effect of digital technologies and staff skill sets on hospital resilience
Application of additive manufacturing for a sustainable healthcare sector
Sustainable I4.0 integration and transition to I5.0 in traditional and digital technological organisations
Digital transformation in healthcare
Digital Transformation in Healthcare
Innovations in Health Care—A Conceptual Framework
Multi-stakeholder preferences for the use of artificial intelligence in healthcare
Advancing Sustainability Assessment of Renewable Energy
Artificial intelligence innovation in healthcare
A Nuanced perspective on blockchain technology and healthcare
Linking manufacturing digitalization and technological Innovation
| Highly cited | No |
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