Mind the gap: unveiling the advantages and challenges of artificial intelligence in the healthcare ecosystem

Purpose This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a two-stage trajectory of exploration and development followed by dissemination and adoption. To illuminate the transition from the first to the second stage, we use prospect theory (PT) to offer insights into the effects of risk and uncertainty on individual decision-making, which potentially lead to partially irrational choices. The primary objective is to discern whether clinical decision support systems (CDSSs) can serve as effective means of “cognitive debiasing”, thus countering the perceived risks. Design/methodology/approach This study presents a comprehensive systematic literature review (SLR) of the adoption of clinical decision support systems (CDSSs) in healthcare. We selected English articles dated 2013–2023 from Scopus, Web of Science and PubMed, found using keywords such as “Artificial Intelligence,” “Healthcare” and “CDSS.” A bibliometric analysis was conducted to evaluate literature productivity and its impact on this topic. Findings Of 322 articles, 113 met the eligibility criteria. These pointed to a widespread reluctance among physicians to adopt AI systems, primarily due to trust-related issues. Although our systematic literature review underscores the positive effects of AI in healthcare, it barely addresses the associated risks. Research limitations/implications This study has certain limitations, including potential concerns regarding generalizability, biases in the literature review and reliance on theoretical frameworks that lack empirical evidence. Originality/value The uniqueness of this study lies in its examination of healthcare professionals’ perceptions of the risks associated with implementing AI systems. Moreover, it addresses liability issues involving a range of stakeholders, including algorithm developers, Internet of Things (IoT) manufacturers, communication systems and cybersecurity providers.

Authors

Publication Details

Journal
European Journal of Innovation Management
Published
2025-02-20
DOI
https://doi.org/10.1108/ejim-01-2024-0078
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
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article

Mind the gap: unveiling the advantages and challenges of artificial intelligence in the healthcare ecosystem

Dirk Meissner, Enrica Iannuzzi, Claudio Nigro, Simona Curiello
3 citations
European Journal of Innovation Management
Artificial Intelligence in Healthcare and Education
1.96
article

Mind the gap: unveiling the advantages and challenges of artificial intelligence in the healthcare ecosystem

Dirk Meissner, Enrica Iannuzzi, Claudio Nigro, Simona Curiello
article en
3 citations

Abstract

Purpose This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a two-stage trajectory of exploration and development followed by dissemination and adoption. To illuminate the transition from the first to the second stage, we use prospect theory (PT) to offer insights into the effects of risk and uncertainty on individual decision-making, which potentially lead to partially irrational choices. The primary objective is to discern whether clinical decision support systems (CDSSs) can serve as effective means of “cognitive debiasing”, thus countering the perceived risks. Design/methodology/approach This study presents a comprehensive systematic literature review (SLR) of the adoption of clinical decision support systems (CDSSs) in healthcare. We selected English articles dated 2013–2023 from Scopus, Web of Science and PubMed, found using keywords such as “Artificial Intelligence,” “Healthcare” and “CDSS.” A bibliometric analysis was conducted to evaluate literature productivity and its impact on this topic. Findings Of 322 articles, 113 met the eligibility criteria. These pointed to a widespread reluctance among physicians to adopt AI systems, primarily due to trust-related issues. Although our systematic literature review underscores the positive effects of AI in healthcare, it barely addresses the associated risks. Research limitations/implications This study has certain limitations, including potential concerns regarding generalizability, biases in the literature review and reliance on theoretical frameworks that lack empirical evidence. Originality/value The uniqueness of this study lies in its examination of healthcare professionals’ perceptions of the risks associated with implementing AI systems. Moreover, it addresses liability issues involving a range of stakeholders, including algorithm developers, Internet of Things (IoT) manufacturers, communication systems and cybersecurity providers.

European Journal of Innovation Management
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
1.96
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