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Applications of artificial neural networks in health care organizational decision-making: A scoping review

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  • Nida Shahid
  • Tim Rappon
  • Whitney Berta

Abstract

Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduced cost. Applications of ANN to diagnosis are well-known; however, ANN are increasingly used to inform health care management decisions. We provide a seminal review of the applications of ANN to health care organizational decision-making. We screened 3,397 articles from six databases with coverage of Health Administration, Computer Science and Business Administration. We extracted study characteristics, aim, methodology and context (including level of analysis) from 80 articles meeting inclusion criteria. Articles were published from 1997–2018 and originated from 24 countries, with a plurality of papers (26 articles) published by authors from the United States. Types of ANN used included ANN (36 articles), feed-forward networks (25 articles), or hybrid models (23 articles); reported accuracy varied from 50% to 100%. The majority of ANN informed decision-making at the micro level (61 articles), between patients and health care providers. Fewer ANN were deployed for intra-organizational (meso- level, 29 articles) and system, policy or inter-organizational (macro- level, 10 articles) decision-making. Our review identifies key characteristics and drivers for market uptake of ANN for health care organizational decision-making to guide further adoption of this technique.

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  • Nida Shahid & Tim Rappon & Whitney Berta, 2019. "Applications of artificial neural networks in health care organizational decision-making: A scoping review," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-22, February.
    • Handle: RePEc:plo:pone00:0212356
    DOI: 10.1371/journal.pone.0212356
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    2. Saurabh Shukla & Mohd Fadzil Hassan & Muhammad Khalid Khan & Low Tang Jung & Azlan Awang, 2019. "An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-31, November.
    3. Jacques Bughin, 2024. "The Role of Firm AI Capabilities in Generative AI-pair Coding," Working Papers TIMES² 2024-076, ULB -- Universite Libre de Bruxelles.
    4. Sabir, Zulqurnain & Said, Salem Ben & Baleanu, Dumitru, 2022. "Swarming optimization to analyze the fractional derivatives and perturbation factors for the novel singular model," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    5. Abreu, Paulo & Santos, Daniel & Barbosa-Povoa, Ana, 2023. "Data-driven forecasting for operational planning of emergency medical services," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    6. Yasmin MOBASHER, 2022. "The Importance Of Implementing Integrated Information Systems In Hospitals," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 12(5), pages 5-21, October.
    7. Çaparoğlu, Ömer Faruk & Ok, Yeşim & Tutam, Mahmut, 2021. "To restrict or not to restrict? Use of artificial neural network to evaluate the effectiveness of mitigation policies: A case study of Turkey," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    8. Pumplun, Luisa & Fecho, Mariska & Islam, Nihal & Buxmann, Peter, 2021. "Machine Learning Systems in Clinics – How Mature Is the Adoption Process in Medical Diagnostics?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124660, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Julian Schiele & Thomas Koperna & Jens O. Brunner, 2021. "Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 65-88, February.
    10. Sudatta Kar & Arpan Kumar Kar & Manmohan Prasad Gupta, 2021. "Modeling Drivers and Barriers of Artificial Intelligence Adoption: Insights from a Strategic Management Perspective," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(4), pages 217-238, October.

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