Impact of a hybrid decision support system to improve the adherence to implantable cardioverter defibrillator therapy guidelines for primary prevention of sudden cardiac death

Vecchio, Nicolás; Belardi, Diego; Benzadón, Mariano; Seoane, Leonardo; Daquarti, Gustavo; Scazzuso, Fernando

doi:10.1016/j.ijmedinf.2018.03.016

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…Another benefit of this technology is that the transformation of clinical knowledge into algorithms allows for the correction of areas where documents (eg, clinical practice guidelines) are ambiguous or unclear [10][11][12][13]. CDSSs have been implemented to support care in several specialties [14][15][16][17][18][19][20], both in developed and developing countries [14,18,21].…”

Section: Introductionmentioning

confidence: 99%

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

Camacho¹,

Zanoletti-Mannello²,

Landis-Lewis³

et al. 2020

Preprint

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BACKGROUND The implementation of clinical decision support systems (CDSS) as an intervention to foster clinical practice change is affected by many factors. Key factors include those associated with behavioral change and also factors associated with the technology acceptance. However, the literature about these subjects is fragmented and originating from two traditionally separated disciplines: Implementation Science and Technology Acceptance. OBJECTIVE In this article, we propose an integrated framework (BEAR – BEhavior and Acceptance fRamework) that bridges the gap between behavioral change and technology acceptance aspects of the implementation of CDSS. METHODS We employed an iterative process to map constructs from four contributing frameworks (TDF - Theoretical Domains Framework, CFIR - Consolidated Framework For Implementation Research, HOT-fit - Human, Organization and Technology-fit, and UTAUT - Unified Theory of Acceptance and Use of Technology) and the findings of six literature reviews, identified through a systematic review of reviews approach. RESULTS The resulting framework comprises 22 domains: Agreement with the decision algorithm; Attitudes; Behavioral Regulation; Beliefs about capabilities; Beliefs about consequences; Contingencies; Demographic characteristics; Effort expectancy; Emotions; Environmental Context and Resources; Goals; Intentions; Intervention characteristics; Knowledge; Memory, Attention and Decision Processes; Patient-health professional relationship; Patient’s preferences; Performance expectancy; Role and Identity; Skills, Ability, Competence; Social influences; and System quality. We demonstrate the use of the framework providing examples from two research projects. CONCLUSIONS We propose an integrated framework that bridges the gap between behavioral change and technology acceptance widening the view established by current models.

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Section: Introductionmentioning

confidence: 99%

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

Camacho¹,

Zanoletti-Mannello²,

Landis-Lewis³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

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

Camacho¹,

Zanoletti-Mannello²,

Landis-Lewis³

et al. 2020

J Med Internet Res

View full text Add to dashboard Cite

Background The implementation of clinical decision support systems (CDSSs) as an intervention to foster clinical practice change is affected by many factors. Key factors include those associated with behavioral change and those associated with technology acceptance. However, the literature regarding these subjects is fragmented and originates from two traditionally separate disciplines: implementation science and technology acceptance. Objective Our objective is to propose an integrated framework that bridges the gap between the behavioral change and technology acceptance aspects of the implementation of CDSSs. Methods We employed an iterative process to map constructs from four contributing frameworks—the Theoretical Domains Framework (TDF); the Consolidated Framework for Implementation Research (CFIR); the Human, Organization, and Technology-fit framework (HOT-fit); and the Unified Theory of Acceptance and Use of Technology (UTAUT)—and the findings of 10 literature reviews, identified through a systematic review of reviews approach. Results The resulting framework comprises 22 domains: agreement with the decision algorithm; attitudes; behavioral regulation; beliefs about capabilities; beliefs about consequences; contingencies; demographic characteristics; effort expectancy; emotions; environmental context and resources; goals; intentions; intervention characteristics; knowledge; memory, attention, and decision processes; patient–health professional relationship; patient’s preferences; performance expectancy; role and identity; skills, ability, and competence; social influences; and system quality. We demonstrate the use of the framework providing examples from two research projects. Conclusions We proposed BEAR (BEhavior and Acceptance fRamework), an integrated framework that bridges the gap between behavioral change and technology acceptance, thereby widening the view established by current models.

show abstract

Impact of a hybrid decision support system to improve the adherence to implantable cardioverter defibrillator therapy guidelines for primary prevention of sudden cardiac death

Cited by 2 publications

References 18 publications

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

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

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

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