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

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.

SUBMITTER: Shahid N

PROVIDER: S-EPMC6380578 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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

Shahid Nida N Rappon Tim T Berta Whitney W

PloS one 20190219 2

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 Busi ...[more]

PMID: 30779785

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Project description:BACKGROUND:Collaborative writing applications (eg, wikis and Google Documents) hold the potential to improve the use of evidence in both public health and health care. The rapid rise in their use has created the need for a systematic synthesis of the evidence of their impact as knowledge translation (KT) tools in the health care sector and for an inventory of the factors that affect their use. OBJECTIVE:Through the Levac six-stage methodology, a scoping review was undertaken to explore the depth and breadth of evidence about the effective, safe, and ethical use of wikis and collaborative writing applications (CWAs) in health care. METHODS:Multiple strategies were used to locate studies. Seven scientific databases and 6 grey literature sources were queried for articles on wikis and CWAs published between 2001 and September 16, 2011. In total, 4436 citations and 1921 grey literature items were screened. Two reviewers independently reviewed citations, selected eligible studies, and extracted data using a standardized form. We included any paper presenting qualitative or quantitative empirical evidence concerning health care and CWAs. We defined a CWA as any technology that enables the joint and simultaneous editing of a webpage or an online document by many end users. We performed qualitative content analysis to identify the factors that affect the use of CWAs using the Gagnon framework and their effects on health care using the Donabedian framework. RESULTS:Of the 111 studies included, 4 were experimental, 5 quasi-experimental, 5 observational, 52 case studies, 23 surveys about wiki use, and 22 descriptive studies about the quality of information in wikis. We classified them by theme: patterns of use of CWAs (n=26), quality of information in existing CWAs (n=25), and CWAs as KT tools (n=73). A high prevalence of CWA use (ie, more than 50%) is reported in 58% (7/12) of surveys conducted with health care professionals and students. However, we found only one longitudinal study showing that CWA use is increasing in health care. Moreover, contribution rates remain low and the quality of information contained in different CWAs needs improvement. We identified 48 barriers and 91 facilitators in 4 major themes (factors related to the CWA, users' knowledge and attitude towards CWAs, human environment, and organizational environment). We also found 57 positive and 23 negative effects that we classified into processes and outcomes. CONCLUSIONS:Although we found some experimental and quasi-experimental studies of the effectiveness and safety of CWAs as educational and KT interventions, the vast majority of included studies were observational case studies about CWAs being used by health professionals and patients. More primary research is needed to find ways to address the different barriers to their use and to make these applications more useful for different stakeholders.

Project description:ObjectivesCognitive and other biases can influence the quality of healthcare decision making. While substantial research has explored how biases can lead to diagnostic or other errors in medicine, fewer studies have examined how they impact the decision making of other healthcare professionals. This scoping review aimed to identify and synthesise a broad range of research investigating whether decisions made by allied health professionals are influenced by cognitive, affective or other biases.Materials and methodsA systematic literature search was conducted in five electronic databases. Title, abstract and full text screening was undertaken in duplicate, using prespecified eligibility criteria designed to identify studies attempting to demonstrate the presence of bias when allied healthcare professionals make decisions. A narrative synthesis was undertaken, focussing on the type of allied health profession, type of decision, and type of bias reported within the included studies.ResultsThe search strategy identified 149 studies. Of these, 119 studies came from the field of psychology, with substantially fewer from social work, physical and occupational therapy, speech pathology, audiology and genetic counselling. Diagnostic and assessment decisions were the most common decision types, with fewer studies assessing treatment, prognostic or other clinical decisions. Studies investigated the presence of over 30 cognitive, affective and other decision making biases, including stereotyping biases, anchoring, and confirmation bias. Overall, 77% of the studies reported at least one outcome that represented the presence of a bias.ConclusionThis scoping review provides an overview of studies investigating whether decisions made by allied health professionals are influenced by cognitive, affective or other biases. Biases have the potential to seriously impact the quality, consistency and accuracy of decision making in allied health practice. The findings highlight a need for further research particularly in professional disciplines outside of psychology, using methods that reflect real life healthcare decision making.

Project description:BackgroundOrganizational health literacy (OHL) aims to respond to the health literacy needs of patients by improving health information and services and making them easier to understand, access, and apply. This scoping review primarily maps criteria characterizing health literate health care organizations. Secondary outcomes are the concepts and terminologies underlying these criteria as well as instruments to measure them.MethodsThe review was carried out following the JBI Manual on scoping reviews. The databases CINAHL, Cochrane Library, JSTOR, PsycINFO, PubMed, Web of Science Core Collection, and Wiley Online Library were searched in July 2020. Three researchers screened the records and extracted the data. The results were synthesized systematically and descriptively.ResultsThe literature search resulted in 639 records. After removing duplicates, screening by title and abstract, and assessing full-texts for eligibility, the scoping review included 60 publications. Criteria for OHL were extracted and assigned to six main categories (with 25 subcategories). The most prevalent topic of organizational health literacy refers to communication with service users. Exemplary criteria regarding this main category are the education and information of service users, work on easy-to-understand written materials as well as oral exchange, and verifying understanding. The six main categories were defined as 1) communication with service users; 2) easy access & navigation; 3) integration & prioritization of OHL; 4) assessments & organizational development; 5) engagement & support of service users, and 6) information & qualification of staff. The criteria were based on various concepts and terminologies. Terminologies were categorized into four conceptual clusters: 1) health literacy in various social contexts; 2) health literate health care organization; 3) organizational behavior, and 4) communication in health care. 17 different assessment tools and instruments were identified. Only some of the toolkits and instruments were validated or tested in feasibility studies.ConclusionsOrganizational health literacy includes a significant number of distinct organizational criteria. The terminologies used in the OHL literature are heterogeneous based on a variety of concepts. A comprehensive, consensus-based conceptual framework on OHL is missing.

Project description:BACKGROUND:Shared decision-making (SDM) is poorly implemented in routine care, despite being promoted by health policies. No reviews have solely focused on an in-depth synthesis of the literature around organizational- and system-level characteristics (i.e., characteristics of healthcare organizations and of healthcare systems) that may affect SDM implementation. A synthesis would allow exploration of interventions to address these characteristics. The study aim was to compile a comprehensive overview of organizational- and system-level characteristics that are likely to influence the implementation of SDM, and to describe strategies to address those characteristics described in the literature. METHODS:We conducted a scoping review using the Arksey and O'Malley framework. The search strategy included an electronic search and a secondary search including gray literature. We included publications reporting on projects that promoted implementation of SDM or other decision support interventions in routine healthcare. We screened titles and abstracts, and assessed full texts for eligibility. We used qualitative thematic analysis to identify organizational- and system-level characteristics. RESULTS:After screening 7745 records and assessing 354 full texts for eligibility, 48 publications on 32 distinct implementation projects were included. Most projects (N =?22) were conducted in the USA. Several organizational-level characteristics were described as influencing the implementation of SDM, including organizational leadership, culture, resources, and priorities, as well as teams and workflows. Described system-level characteristics included policies, clinical guidelines, incentives, culture, education, and licensing. We identified potential strategies to influence the described characteristics, e.g., examples how to facilitate distribution of decision aids in a healthcare institution. CONCLUSIONS:Although infrequently studied, organizational- and system-level characteristics appear to play a role in the failure to implement SDM in routine care. A wide range of characteristics described as supporting and inhibiting implementation were identified. Future studies should assess the impact of these characteristics on SDM implementation more thoroughly, quantify likely interactions, and assess how characteristics might operate across types of systems and areas of healthcare. Organizations that wish to support the adoption of SDM should carefully consider the role of organizational- and system-level characteristics. Implementation and organizational theory could provide useful guidance for how to address facilitators and barriers to change.

Dataset Information

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

Publications

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

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