Literature DB >> 26535769

A Critical Review of the Theoretical Frameworks and the Conceptual Factors in the Adoption of Clinical Decision Support Systems.

Peck Chui Betty Khong1, Eleanor Holroyd, Wenru Wang.   

Abstract

The clinical decision support system is utilized to translate knowledge into evidence-based practice in clinical settings. Many studies have been conducted to understand users' adoption of the clinical decision support system. A critical review was conducted to understand the theoretical or conceptual frameworks used to inform the studies on the adoption of the clinical decision support system. The review identified 15 theoretical and conceptual frameworks using multiple hybrids of theories and concepts. The Technology Acceptance Model was the most frequently used baseline framework combined with frameworks such as the diffusion of innovation, social theory, longitudinal theory, and so on. The results from these articles yielded multiple concepts influencing the adoption of the clinical decision support system. These concepts can be recategorized into nine major concepts, namely, the information system, person (user or patient), social, organization, perceived benefits, emotions, trustability, relevance (fitness), and professionalism. None of the studies found all the nine concepts. That said, most of them have identified the information system, organization, and person concepts as three of its concepts affecting the use of the clinical decision support system. Within each of the concepts, its subconcepts were noted to be very varied. Yet each of these subconcepts has significantly contributed toward the different facets of the concepts. A pluralistic framework was built using the concepts and subconcepts to provide an overall framework construct for future study on the adoption of the clinical decision support system.

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Year:  2015        PMID: 26535769     DOI: 10.1097/CIN.0000000000000196

Source DB:  PubMed          Journal:  Comput Inform Nurs        ISSN: 1538-2931            Impact factor:   1.985


  6 in total

1.  Nurses' Experiences Implementing ePED: An iPad Application to Guide Quality Discharge Teaching.

Authors:  Carol G Klingbeil; Cori Gibson; Norah L Johnson; Michele Polfuss; Karen Gralton; Stacee M Lerret
Journal:  Comput Inform Nurs       Date:  2022-03-30       Impact factor: 2.146

2.  Comparing a Mobile Decision Support System Versus the Use of Printed Materials for the Implementation of an Evidence-Based Recommendation: Protocol for a Qualitative Evaluation.

Authors:  Jhon Camacho; Ana María Medina Ch; Zach Landis-Lewis; Gerald Douglas; Richard Boyce
Journal:  JMIR Res Protoc       Date:  2018-04-13

3.  Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.

Authors:  Huixian Zha; Kouying Liu; Ting Tang; Yue-Heng Yin; Bei Dou; Ling Jiang; Hongyun Yan; Xingyue Tian; Rong Wang; Weiping Xie
Journal:  BMC Med Inform Decis Mak       Date:  2022-08-19       Impact factor: 3.298

Review 4.  A Conceptual Framework to Study the Implementation of Clinical Decision Support Systems (BEAR): Literature Review and Concept Mapping.

Authors:  Jhon Camacho; Manuela Zanoletti-Mannello; Zach Landis-Lewis; Sandra L Kane-Gill; Richard D Boyce
Journal:  J Med Internet Res       Date:  2020-08-06       Impact factor: 5.428

Review 5.  Developing a framework for evidence-based grading and assessment of predictive tools for clinical decision support.

Authors:  Mohamed Khalifa; Farah Magrabi; Blanca Gallego
Journal:  BMC Med Inform Decis Mak       Date:  2019-10-29       Impact factor: 2.796

Review 6.  Human Factors and Technological Characteristics Influencing the Interaction of Medical Professionals With Artificial Intelligence-Enabled Clinical Decision Support Systems: Literature Review.

Authors:  Michael Knop; Sebastian Weber; Marius Mueller; Bjoern Niehaves
Journal:  JMIR Hum Factors       Date:  2022-03-24
  6 in total

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