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The acceptance of clinical decision support systems among clinicians in the treatment of neck and/or back pain

S M Jansen-Kosterink, M Cabrita, I Flierman
2020 European Journal of Public Health  
Background Clinical Decision Support Systems (CDSSs) are computerized systems using case-based reasoning to assist clinicians in making clinical decisions.  ...  Despite the proven added value to public health, the implementation of CDSS clinical practice is scarce. Particularly, little is known about the acceptance of CDSS among clinicians.  ...  Within this platform the user will be shipwrecked and has to The acceptance of clinical decision support systems among clinicians in the treatment of neck and/or back pain Stephanie Jansen-Kosterink  ... 
doi:10.1093/eurpub/ckaa165.1234 fatcat:iouojg2mtbd5de43tmplkk6ecu

Reasons for declining computerized insulin protocol recommendations: Application of a framework

K. Sward, J. Orme, D. Sorenson, L. Baumann, A.H. Morris
2008 Journal of Biomedical Informatics  
Clinical decision support systems (CDS) can interpret detailed treatment protocols for ICU care providers. In open-loop systems, clinicians can decline protocol recommendations.  ...  Even though our protocol was well-accepted by clinicians overall, noncompliance patterns revealed potential protocol improvement targets, and suggested ways to reduce barriers impeding software use.  ...  Acknowledgments We are indebted to our many R.N. and M.D. clinician colleagues, who enabled the completion of this work.  ... 
doi:10.1016/j.jbi.2008.04.002 pmid:18499528 pmcid:PMC2490709 fatcat:rpudyujkszbjrhybrdlvk2pm3m

The application of technology acceptance and diffusion of innovation models in healthcare informatics

Rod Ward
2013 Health Policy and Technology  
Ward, R. (2013) The application of technology acceptance and diffusion of innovation models in healthcare informatics. Health Policy and Technology, 2 (4). pp. 222-228.  ...  Technology Acceptance Models Various attempts have been made to examine the factors which will influence an individual's decision about the use or otherwise of new technologies.  ...  The Technology Acceptance Model (TAM) focuses on the factors and decision processes an individual will go through in any decision to accept and use a technology (4) .  ... 
doi:10.1016/j.hlpt.2013.07.002 fatcat:rbgnzet3fvavnek7yakp6nlcve

Factors influencing alert acceptance: a novel approach for predicting the success of clinical decision support

Hanna M Seidling, Shobha Phansalkar, Diane L Seger, Marilyn D Paterno, Shimon Shaykevich, Walter E Haefeli, David W Bates
2011 JAMIA Journal of the American Medical Informatics Association  
This information may help improve clinical decision support systems design.  ...  Clinical decision support systems can prevent knowledge-based prescription errors and improve patient outcomes.  ...  Funding This work was supported in part by a fellowship within the postdoctoral program of the German Academic Exchange Service (DAAD), Bonn, Germany; the Health Information Technology Center for Education  ... 
doi:10.1136/amiajnl-2010-000039 pmid:21571746 pmcid:PMC3128393 fatcat:y3sbwec2lvaypf5tcamtnaex2y

Factors influencing decision support system acceptance

Rania Shibl, Meredith Lawley, Justin Debuse
2013 Decision Support Systems  
The purpose of this research was to develop and explore a UTAUT (Unified Theory of Acceptance and Use of Technology) based model of how and why GPs accept DSS.  ...  The developed model indicated that four main factors influence DSS acceptance and use including usefulness (incorporating consultation issue, professional development and patient presence), facilitating  ...  It is therefore important to identify the factors that influence GPs' acceptance of these systems to facilitate their usage and improve decision making.  ... 
doi:10.1016/j.dss.2012.09.018 fatcat:s53nmm4ptbcddfdsagq37ecyze

Assessing Acceptance Level of a Hybrid Clinical Decision Support Systems [chapter]

Georgy Kopanitsa, Ilia V. Derevitskii, Daria A. Savitskaya, Sergey V. Kovalchuk
2021 Studies in Health Technology and Informatics  
We present a user acceptance study of a clinical decision support system (CDSS) for Type 2 Diabetes Mellitus (T2DM) risk prediction.  ...  We employed a Lankton's model to evaluate the user acceptance of the clinical decision support system. Our analysis has proved that without the presence of scales, a physician trust CDSS blindly.  ...  The work of Georgy Kopanitsa was financially supported by the Government of the Russian Federation through the ITMO fellowship program.  ... 
doi:10.3233/shti210802 pmid:34795071 fatcat:544xgmr57nbczhznix746azpsy

Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study

Stefanie Jauk, Diether Kramer, Alexander Avian, Andrea Berghold, Werner Leodolter, Stefan Schulz
2021 Journal of medical systems  
In order to improve quality and safety in healthcare, computerized decision support should predict actionable events and be highly accepted by users.  ...  Despite intense research on machine learning for the prediction of clinical outcomes, the acceptance of the integration of such complex models in clinical routine remains unclear.  ...  Special thanks go to Susanne Rienmüller, Ewald Tax and Birgit Großauer for their ongoing support during the whole study period.  ... 
doi:10.1007/s10916-021-01727-6 pmid:33646459 fatcat:jsvefhcolzekdcqwu7pblptpp4

A six-year repeated evaluation of computerized clinical decision support system user acceptability

Randall W. Grout, Erika R. Cheng, Aaron E. Carroll, Nerissa S. Bauer, Stephen M. Downs
2018 International Journal of Medical Informatics  
Objective-Long-term acceptability among computerized clinical decision support system (CDSS) users in pediatrics is unknown.  ...  We used logistic regression to assess the odds of a favorable response to each question by survey year, clinic role, part-time status, and frequency of CHICA use.  ...  Acknowledgments The authors wish to acknowledge the technical expertise and efforts of the individual members of the Child Health Informatics and Research Development Lab (CHIRDL) team that provides programming  ... 
doi:10.1016/j.ijmedinf.2018.01.011 pmid:29500025 pmcid:PMC5836810 fatcat:jbfuggv6onht7orlrcxcpmzrt4

User Acceptance of Health Information Technology (HIT) in Developing Countries: A Conceptual Model

Abd Rahman Ahlan, Barroon Isma'eel Ahmad
2014 Procedia Technology - Elsevier  
Also works on acceptance of HIT systems were reviewed so as to understand the level of research done in the area.  ...  These limitations can be overcome when researchers study the factors that will affect the user acceptance of these systems, and then consider the factors while developing the systems.  ...  This decision making capability help doctors and other medical experts to manage their patients with ease. These systems are called Clinical Decision Support Systems (CDSS).  ... 
doi:10.1016/j.protcy.2014.10.145 fatcat:2arrxa73hjdfrf54hqi6lqrvfu

Factors influencing trust in medical artificial intelligence for healthcare professionals: a narrative review

Victoria Tucci, Joan Saary, Thomas E. Doyle
2021 Journal of Medical Artificial Intelligence  
features of AI-based diagnostic and clinical decision support systems that contribute to enhanced end-user trust.  ...  However, lack of trust in the output of such complex decision support systems introduces challenges and barriers to adoption and implementation into clinical practice.  ...  Acknowledgments We would like to thank the Biomedic.AI Lab at McMaster University for their on-going support and feedback throughout the process of this study.  ... 
doi:10.21037/jmai-21-25 fatcat:e2yvcpp7pradhadpu7mbnyjiba

Guidance for Evidence-Informed Policies about Health Systems: Linking Guidance Development to Policy Development

John N. Lavis, John-Arne Røttingen, Xavier Bosch-Capblanch, Rifat Atun, Fadi El-Jardali, Lucy Gilson, Simon Lewin, Sandy Oliver, Pierre Ongolo-Zogo, Andy Haines
2012 PLoS Medicine  
This is one paper in a three-part series that sets out how evidence should be translated into guidance to inform policies on health systems and improve the delivery of clinical and public health interventions  ...  Acknowledgments We acknowledge other members of the Task Force on Developing Health Systems Guidance, who include (with their affiliations at the time when the Task Author Contributions Wrote the  ...  first draft of the manuscript: JNL.  ... 
doi:10.1371/journal.pmed.1001186 pmid:22427746 pmcid:PMC3302830 fatcat:ohnen2ir5nfejc6jek4xrtqw7m

Factors Influencing Patients' Acceptance and Adherence to Active Surveillance

D. F. Penson
2012 Journal of the National Cancer Institute. Monographs  
This is particularly germane when considering factors that influence a patient's acceptance of and adherence to active surveillance (AS).  ...  Finally, some of the factors, particularly the heuristic ones, are potentially modifiable and may serve as targets for future interventions to increase acceptance of and adherence to AS.  ...  Rather, this chapter will focus specifically on patient-related factors that influence the acceptance of and adherence to AS in clinically localized prostate cancer.  ... 
doi:10.1093/jncimonographs/lgs024 pmid:23271775 pmcid:PMC3540870 fatcat:t2sy3fccmrheldarp3lgpuqzwm

Barriers and Facilitators to Clinical Decision Support Systems Adoption: A Systematic Review

Srikant Devaraj, Sushil K. Sharma, Dyan J. Fausto, Sara Viernes, Hadi Kharrazi
2014 Journal of Business Administration Research  
The objective of the study was to identify potential barriers and facilitators to improve clinical practice using computer-based Clinical Decision Support System (CDSS).  ...  The keywords ((CDSS OR Clinical Decision Support systems) AND (barrier OR facilitator)) were used to identify CDSS's barriers and facilitators in improving clinical practice.  ...  One such system is the computer-based Clinical Decision Support System (CDSS) developed to provide patient-specific, evidence-based advice in order to overcome some of the challenges facing the healthcare  ... 
doi:10.5430/jbar.v3n2p36 fatcat:x6btshv5ifb4rgkqvix2gdcy3m

Treatment decision aids are unlikely to cut healthcare costs

S. J. Katz
2014 The BMJ (British Medical Journal)  
The factors that contribute to growth in healthcare spending are well known.  ...  The difference has important implications for strategies to influence the outcomes of clinical encounters including costs.  ...  Competing interests: I have read and understood the BMJ Group policy on declaration of interests and declare the following interests: none. Provenance and peer review: Commissioned; not peer reviewed.  ... 
doi:10.1136/bmj.g1172 pmid:24500345 fatcat:lecjwl5afzcarn4klsod5ygyxa

Subjective usability of the CARDSS guideline-based decision support system

Rick Goud, Monique W M Jaspers, Arie Hasman, Niels Peek
2008 Studies in Health Technology and Informatics  
Clinical decision support systems (CDSSs) differ from other health information systems in their aim to directly influence the decision-making behaviour of healthcare professionals.  ...  The questionnaire was returned by 63 respondents (93%) from 27 clinics. Factors that influenced CARDSS' usability were identified using linear regression analysis.  ...  The participating clinics either worked with an intervention version of the system that included decision support functionality, or with a control version that lacked decision support but otherwise had  ... 
pmid:18487730 fatcat:o2tapdghtjgbzousl67ehvrviq
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