As Orlikowski and Iacono (2001) emphasize, information systems (IS) researchers not only have the opportunity to influence the future, but they also have the responsibility to do so by documenting what digital technologies change, capturing what disappears, and what is being created.
In the healthcare sector, recent years have been marked by massive growth in innovations and the implementation of digital technologies: the development of mobile health, the deployment of digital patient monitoring devices, the operationalization of integrated electronic medical records systems, the introduction of artificial intelligence applied to clinical diagnostics, the development of immersive therapies via virtual reality, and the use of blockchain technology. However, beyond the proliferation of innovative digital devices, what now stands out seems to be of a different order: their interdependence, which nurtures new forms of complexity, the quantification at work (data-intensive medicine), and the unprecedented modes of instantaneous calculation (algorithmic medicine) that support them, as well as the connectivity challenges (telemedicine).
Data analysis and Artificial Intelligence (AI), driven by the acceleration of data collection in the sector, are ushering in disruptions and radical innovations in healthcare. Rapid advancements in AI are creating new opportunities in healthcare. These technologies alone have a transformative power on the industry and society. But through their integration, their disruptive effects increase exponentially, raising new issues.
Thus, the more organizations collect data due to increased integration of digital devices, the more the issue of privacy protection becomes critical. With the dissemination of self-learning algorithms, cybersecurity concerns become even more critical. This new generation of digital innovations also raises new governance questions, particularly regarding the involvement of new stakeholders in healthcare system analysis, represented by the intervention of non-human agents in automated and algorithmic decision systems.
Similarly, explainability, accountability, relationships between healthcare professionals, and the organization of work represent major challenges associated with the use of AI in healthcare organizations. The complexity of algorithms and the colossal volume of data used by AI make it extremely difficult to understand and thus explain the functioning and results produced by AI. The question of responsibility for healthcare professionals and the organizations to which they belong becomes even more acute when they use this technology. From a managerial perspective, the use of AI is a major disruptive element in healthcare management systems, contributing to the transformation of relationships among stakeholders and the emergence of new work organizations that require new skills. Providing patients with broader access to healthcare via telemedicine or connected devices for remote monitoring profoundly changes the organization of care and the role of the patient. It also raises numerous challenges in terms of health equity and trust.
For some, this represents a significant break. For others, technological advancements in healthcare oscillate between continuity and a shift. Many studies have shown that the impact of early generations of information technology on healthcare has been far below expectations. And even though the COVID crisis accelerated the digital transformation of the healthcare sector, the sector, and even more so the medico-social sector, remain marked by slow adoption of innovations in digital health technologies.
The transformative potential of digital technologies in the healthcare sector remains complex to grasp, as it is embedded in structural specificities. The complexity of the domain is related to the multiplicity of competing and/or cooperating actors (industrials, consumers, patients, healthcare professionals, insurance companies), and an institutional environment characterized by multiple levels of regulation and the power of professional bodies. The ongoing challenge of integrating legacy systems, the diversity of technological platforms, and strict regulations pose major interoperability issues. Governments, providers, and users must agree on interoperability and standardization frameworks in a constantly evolving regulatory context. Each new technology integrated into the healthcare pathway introduces a multiplicity of changes in the existing context, creating obstacles and resistance that may affect the social and spatial organization of care, the division of medical and paramedical labor, and interactions among various stakeholders. Power dynamics at play in the healthcare industry are highlighted in studies on IS governance and the direction of AI development, and internal power dynamics within a healthcare organization, as well as external dynamics that often play out between patients and caregivers.
Is the transformative power of digital technologies in healthcare likely to improve the effectiveness and efficiency of healthcare systems? As the World Health Organization (2021) reminds us, digital innovations aim to transform the delivery of healthcare services, making them more accessible, personalized, and potentially more efficient.
Emerging technologies in healthcare present new challenges and renew issues due to the unpredictable discontinuities brought about by technologies like AI and their integration, or even their expansion across the entire sector. They offer significant opportunities for future research and the potential to renew theoretical and methodological approaches in IS management. In order to overcome past difficulties and address the complexity of the field, scholars advocate for interdisciplinary approaches in healthcare and information technology. The healthcare field represents a rich environment from which new theories can be developed and existing theories extended in the field of IS.
This special issue is open to contributions from interdisciplinary and sociotechnical perspectives, often considered one of the foundational viewpoints in IS discipline. Submissions should focus on the ongoing transformations driven by innovative digital health technologies and grasp the magnitude of these changes. Contributions on the medico-social sector, which is currently under-researched, will be appreciated. Contributions may include empirical, theoretical, or meta-analysis papers.