Factors influencing decision support system acceptance

Shibl, Rania; Lawley, Meredith; Debuse, Justin C. W.

doi:10.1016/j.dss.2012.09.018

Cited by 154 publications

(100 citation statements)

References 49 publications

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“…The UTAUT model links gender, age, experience, and voluntariness of use as moderators of the impact of the four key constructs on behavioral intention and use behavior. Different improvements of this model in the recent years also stress the importance of other factors such as hedonic motivation, price value, and habit (Pahnila, Siponen, & Zheng, 2011;Venkatesh, Thong, & Xu, 2012), cognitive individual differences, learning, and teaching styles (Lin et al, 2013), and trust (Shibl, Lawley, & Debuse, 2013).…”

Section: The Theoretical Background Of the Unified Theory Of Acceptanmentioning

confidence: 98%

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Dečman

2015

Computers in Human Behavior

210

157

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Section: The Theoretical Background Of the Unified Theory Of Acceptanmentioning

confidence: 98%

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Dečman

2015

Computers in Human Behavior

210

157

View full text Add to dashboard Cite

“…These theories were drawn from the theory of planned behavior, 19,21,24,25,[29][30][31] theory of reasoned action, 19,21,24,25,30,31 sociotechnology theory, 11,32 longitudinal acceptance theory, 3,31 diffusion of innovation theory, 3,26 information technology organization fit, 25 organization theory, 20 Bandura's social learning theory, 26 and intrinsic motivation theory. 29 The most widely used framework was the TAM, which had borrowed its root concepts from the theory of planned behavior and theory of reasoned action.…”

Section: Findings Framework and Theories Underpinning The Studiesmentioning

confidence: 99%

“…32 For the purpose of this study, only the term clinical decision support system was used in order to avoid confusion of names. The CDSSs studied were designed to support a wide range of decisions such as diagnosis and nursing care plan, 28 clinical practice guidelines 26,30 or protocols, 29 diagnosis and treatments, 3,11,[19][20][21][22][23][24][25]32 rehabilitation, 27 and reminder systems. 31 Twelve of the 16 studies were conducted in Western countries (the United States, the United Kingdom, the Netherlands, Spain, and Australia).…”

mentioning

confidence: 99%

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

Khong

Holroyd

Wang

2015

CIN: Computers, Informatics, Nursing

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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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“…A common criticism of CDSSs is their poor usability. 27 Clinicians work in busy environments with demanding time (and other) pressures, and any system that adds to those burdens will not be accepted. Reviews of clinicians' information-seeking behaviour show that a lack of time and formal training with IT systems -as well as having to distract from the current workfl ow and clinical task at hand because decision-making software is often not embedded directly within relevant CISs -resulted in clinicians using colleagues as their fi rst source when seeking information to guide decisions.…”

Section: Challenges To Implementation and Adoption Of Clinical Decisimentioning

confidence: 99%

Decision time for clinical decision support systems

et al. 2014

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KEYWORDS: Clinical decision support systems, decision-making, diagnosis ContextInformation technology (IT) is now commonplace in almost every branch of healthcare. Electronic health records, eprescribing and digital medical imaging are well known to clinicians and have been implemented with varying degrees of success. 1 In addition, clinicians increasingly make use of online repositories such as PubMed and Google Scholar, 2 and specialised search engines such as FindZebra 3 to help answer clinical questions. One often overlooked set of IT tools are clinical decision support systems (CDSSs), which have been defi ned as systems that 'provide clinicians or patients with computer-generated clinical knowledge and patient-related information, intelligently fi ltered or presented at appropriate times, to enhance patient care'. 4 Such CDSSs have been the subject of academic computer science research for more than ABSTRACT 50 years 5 and offer the potential for better supported decision making by clinicians, improved compliance with medical standards and improved clinical effi ciency and safety. 6,7 Nonetheless, utilisation of CDSSs remains limited, and most healthcare IT systems do not include robust CDSS functions that can be widely employed across organisations, clinical presentations and domains. 8 Some of the challenges to implementation of CDSSs relate to the volume of high-quality data required for state-of-the-art systems, the translation of such data to machine-readable states and the mapping of CDSS processes to fi t with existing clinical workfl ows. As a result, successful implementation of CDSSs has tended to be site and domain specifi c, with major diffi culties replicating these successes more extensively throughout healthcare systems. 9 This is in contrast to commercial fi elds such as fi nance, where decision support technologies have been widely deployed. For example, risk-profi ling tools for fi nancial experts have been developed as easy-to-use programs that can assimilate information and guide users through complex fi nancial information and associated decisions tailored to individual customer needs. Healthcare decision making is signifi cantly more complex than fi nancial planning; however, some of the challenges in both domains are similar: large quantities of data need to be linked, integrated and translated to machine readable formats, and expert knowledge is required to contextualise and apply the data in a meaningful way. We discuss some reasons for the limited dissemination and adoption of CDSSs to date and refl ect on the major barriers that need to be overcome for these useful tools to be adopted more widely.

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Factors influencing decision support system acceptance

Cited by 154 publications

References 49 publications

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

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

Decision time for clinical decision support systems

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