Global disruptions drive urgent digital overhaul in healthcare enterprises

The COVID-19 pandemic may have accelerated digital ambitions in healthcare, but most enterprises remain critically unprepared for the next disruption. A comprehensive literature review published in Sustainability (2025) analyzes 60 peer-reviewed journal articles and exposes deep-rooted barriers, from data fragmentation to leadership inertia, that undermine transformation across the sector.

Titled “Digital Transformation of Healthcare Enterprises in the Era of Disruptions—A Structured Literature Review”, the study provides a blueprint for navigating these gaps through strategic use of AI, IoT, and other technologies.

What are the primary disruption scenarios and how do they drive healthcare digitization?

Disruption is not merely a background condition, it is a primary driver for digital transformation in healthcare, the study asserts. Three dominant disruption scenarios were identified: pandemics (notably COVID-19), supply chain breakdowns, and cybersecurity threats.

The COVID-19 pandemic served as a historic inflection point, exacerbating demand surges, intensifying panic buying, and pushing medical supply chains to the brink. These challenges brought into sharp relief the fragility of existing operational models. Healthcare providers found themselves battling not just disease, but also logistical dysfunctions and data silos. For instance, respiratory device shortages and disrupted supply chains directly impacted hospital care delivery, necessitating real-time analytics and IoT-enhanced visibility tools to track inventory and production capabilities.

In parallel, cybersecurity emerged as both a disruption and a consequence of digitization. Over 60% of healthcare organizations reported ransomware attacks that compromised not just data but patient safety. Market volatility added another layer of complexity, affecting procurement, pricing, and capacity planning. The study highlights how the integration of digital technologies like AI, digital twins, and blockchain not only responded to these threats but became essential tools to build resilience and anticipate future shocks.

What are the core barriers and enablers of digital transformation in healthcare?

Despite the urgency created by external disruptions, internal constraints remain formidable. The study identifies four principal barriers: resistance to change, regulatory compliance complexity, workforce skill deficits, and poor data interoperability.

Resistance to change is deeply rooted in human behavior, especially within regulated sectors. Employees often default to legacy workflows, especially in contexts with high compliance burdens. Regulatory challenges further compound this inertia. Evolving standards, fragmented coding protocols, and a lack of standardized data structures make integration across health systems an arduous task.

Compounding this is the scarcity of tech-savvy healthcare professionals. Many organizations lack in-house expertise to implement, manage, and scale emerging technologies like AI, IoT, or data analytics. Moreover, fragmented data systems, often operating on incompatible coding schemas like ICD-10 and SNOMED CT, impede effective digital transformation and degrade decision-making.

However, the study also highlights a set of critical enablers that can offset these barriers. Effective change management is cited as the single most important success factor. Organizations that treat transformation as a strategic change initiative, rather than a technological upgrade, fare better. Leadership is instrumental, particularly leaders who embrace collaborative visioning and evidence-based improvisation. Strategic alignment between IT and Operational Technology (OT) departments fosters systems-level integration, enabling real-time tracking, cloud-based collaboration, and AI-powered automation.

Innovation funding mechanisms such as crowdsourcing and medical crowdfunding are also increasingly relevant, especially for startups and SMEs that struggle to secure traditional investment. Platforms like Kickstarter and GoFundMe are enabling early-stage development of diagnostic tools, wearable devices, and blockchain-based patient data systems.

What are the key use cases of digital technologies in the healthcare sector?

The study presents a wide range of digital transformation use cases that have already yielded tangible benefits. Digital twins emerged as the most cited use case, enabling real-time process simulation, capacity planning, and patient flow optimization. In cancer care, AI-integrated digital twins are being used to model individual treatment pathways and predict disease progression.

Artificial Intelligence (AI) itself has multiple applications, from accelerating drug discovery (by reducing virtual screening cycle times by 40%) to optimizing clinical trials and enabling predictive diagnostics. AI-based supply chain tools are helping hospitals predict shortages, automate procurement, and streamline logistics.

The Internet of Things (IoT) is enabling real-time patient monitoring, especially in remote or home-based care settings. IoT-enabled edge computing devices connect hospital infrastructure with diagnostic and patient-tracking tools, facilitating telemedicine and proactive intervention.

Augmented Reality (AR) represents another transformative use case. AR applications have proven effective in surgical planning, remote diagnostics, and immersive training. By reducing training time and administrative overhead, AR improves both patient engagement and staff productivity.

Altogether, these technologies reinforce supply chain resilience, operational efficiency, and patient care personalization, all while mitigating the risks introduced by disruption scenarios. The convergence of these tools with effective leadership and adaptive change management forms the cornerstone of future-ready healthcare systems.