The exploitation of data to support decision-making in healthcare: a systematic literature review and future research directions

Luigi Jesus Basile (), Nunzia Carbonara (), Umberto Panniello () and Roberta Pellegrino ()
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Luigi Jesus Basile: LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris]
Nunzia Carbonara: Polytechnic University of Bari / Politecnico di Bari
Umberto Panniello: Polytechnic University of Bari / Politecnico di Bari
Roberta Pellegrino: Polytechnic University of Bari / Politecnico di Bari

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Abstract: The development of new technologies and their continued adoption allow data to be collected, analysed and exploited for decision-making. Data can play an important role in the healthcare industry since it is a complex system where every decision is strongly affected by risk and uncertainty. Although the proliferation of data and the awareness of the importance of new technologies to support decision-making in presence of risk and uncertainty, there is a lack of understanding of the interrelations between data, decision-making process and risk management in healthcare organizations and their role to deliver healthcare services. Pursued by this research gap, the objective of this study is to understand how data can optimize decisions confronted with risk and uncertainty in the main domains (structure, process, outcome) of healthcare organizations. Thus, we conducted a systematic literature review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, by selecting and analysing peer-reviewed journal articles from three databases: Scopus, Web of Science and PubMed. The paper's findings suggest that although data are widely used to optimize the decisions in the healthcare organization domains in presence of risk and uncertainty, there are still many scientific and practice gaps that lead to the definition of a future research agenda.

Keywords: Data-driven; Decision-making; Healthcare; Risk; Uncertainty; Artificial intelligence (search for similar items in EconPapers)
Date: 2025
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Published in Management Review Quarterly, In press, ⟨10.1007/s11301-024-00482-5⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05037727

DOI: 10.1007/s11301-024-00482-5

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