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Review
. 2019 Feb 19;14(2):e0212356.
doi: 10.1371/journal.pone.0212356. eCollection 2019.

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

Nida Shahid  1   2 , Tim Rappon  1 , Whitney Berta  1
Affiliations
Free PMC article
Review

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

Nida Shahid et al. PLoS One. .
Free PMC article

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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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Conceptual model of a feed-forward and recurrent neural network.
Fig 2
Fig 2. Review process overview.
*Articles excluded for the following reasons: Not ANN or suitable synonym (n = 93), use of ANN unrelated to healthcare organizational decision-making (n = 70), based on iterated exclusion criteria (n = 45), not based on empirical or theoretical research (n = 9), could not access full-text (n = 9).
Fig 3
Fig 3. Article characteristics.
(A) Number of articles by publication year. (B) Number of articles by country.
Fig 4
Fig 4. Types of applications of artificial neural networks identified in the review.
See this image and copyright information in PMC

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Grants and funding

The authors received no specific funding for this work.