Background: Computer-based clinical decision support systems (CDSS) are regarded as a key element to enhance decision-making in a healthcare environment to improve the quality of medical care delivery. The concern of having new CDSS unused is still one of the biggest issues in developing countries for the developers and implementers of clinical IT systems. The main objectives of this study are to determine whether (1) the physician's perceived professional autonomy, (2) involvement in the decision to implement CDSS and (3) the belief that CDSS will improve job performance increase the intention to adopt CDSS. Four hypotheses were formulated and tested.
Methods: A questionnaire-based survey conducted between July 2010 and December 2010. The study was conducted in seven public and five private hospitals in Kuala Lumpur, Malaysia. Before contacting the hospitals, necessary permission was obtained from the Ministry of Health, Malaysia and the questionnaire was vetted by the ethics committee of the ministry. Physicians working in 12 hospitals from 10 different specialties participated in the study. The sampling method used was stratified random sampling and the physicians were stratified based on the specialty. A total of 450 physicians were selected using a random number generator. Each of these physicians was given a questionnaire and out of 450 questionnaires, 335 (response rate--74%) were returned and 309 (69%) were deemed usable.
Results: The hypotheses were tested using Structural Equation Modeling (SEM). Salient results are: (1) Physicians' perceived threat to professional autonomy lowers the intention to use CDSS (p < 0.01); (2) Physicians involvement in the planning, design and implementation increases their intention to use CDSS (p < 0.01); (3) Physicians belief that the new CDSS will improve his/her job performance increases their intention to use CDSS (p < 0.01).
Conclusion: The proposed model with the three main constructs (physician's professional characteristic, involvement and belief) explains 47% of the variance in the intention to use CDSS. This is significantly higher than the models addressed so far. The results will have a major impact in implementing CDSS in developing countries.
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http://dx.doi.org/10.1186/1472-6947-12-142 | DOI Listing |
PLoS One
December 2024
School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.
Introduction: Clinical decision support system (CDSS) is an application used to aid decision-making and provide knowledge regarding treatment, diagnosis, and laboratory testing. Despite the associated benefits, the underutilization of CDSS is causing a global challenge. In Palestine, CDSS remains unimplemented, prompting a study on knowledge levels and factors influencing CDSS acceptance among physicians.
View Article and Find Full Text PDFBMC Psychiatry
March 2024
National Centre for Suicide Research and Prevention, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Background: Self-harm presents a significant public health challenge. Emergency departments (EDs) are crucial healthcare settings in managing self-harm, but clinician uncertainty in risk assessment may contribute to ineffective care. Clinical Decision Support Systems (CDSSs) show promise in enhancing care processes, but their effective implementation in self-harm management remains unexplored.
View Article and Find Full Text PDFDtsch Arztebl Int
April 2024
Institute of General Practice, Goethe University Frankfurt am Main; Pharmacy of University Hospital Frankfurt; Department of Medical Informatics, Biometry and Epidemiology, Ruhr University Bochum; Department of Medical Informatics, Biometry and Epidemiology, Ruhr University Bochum; Institute of General Practice, Goethe University Frankfurt am Main; Working Group General and Family Medicine, Medical Faculty East Westphalia-Lippe, University of Bielefeld; Institute of General Practice, Goethe University Frankfurt am Main; Bergisch Competence Center for Health Economics and Health Services Research, Bergische University Wuppertal; Chair of General Medicine II and Patient Orientation in Primary Care, Institute of General Medicine and Ambulatory Health Care (iamag), University Witten/Herdecke; Working Group for Health Economics and Health Management, Faculty of ; Health Sciences, Bielefeld University; Chairman of the Drug Therapy Management and Drug Therapy Safety Commission, German Society for Internal Medicine (DGIM); Barmer, Wuppertal; Institute of Clinical Pharmacology, University Hospital and Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main; Institute for Evidence-Based Healthcare, Faculty of Health Sciences & Medicine, Bond University, Gold Coast, Queensland, 4229, Australia; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; PMV Research Group, Faculty of Medicine, University Hospital Cologne, University of Cologne; Institute of General Practice, Goethe-University Frankfurt am Main; Department of Family Medicine, Care and Public Health Research Institute, Maastricht University; Department of Public Health and Primary Care, Academic Centre of General Practice, KU Leuven.
Background: Inappropriate drug prescriptions for patients with polypharmacy can have avoidable adverse consequences. We studied the effects of a clinical decision-support system (CDSS) for medication management on hospitalizations and mortality.
Methods: This stepped-wedge, cluster-randomized, controlled trial involved an open cohort of adult patients with polypharmacy in primary care practices (=clusters) in Westphalia-Lippe, Germany.
PLoS One
September 2023
Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
Background: Falls are the leading cause of injury-related mortality and hospitalization among adults aged ≥ 65 years. An important modifiable fall-risk factor is use of fall-risk increasing drugs (FRIDs). However, deprescribing is not always attempted or performed successfully.
View Article and Find Full Text PDFStroke Vasc Neurol
December 2024
Department of Neurology, Beijing Tiantan Hospital, Beijing, China
Background: Given the swift advancements in artificial intelligence (AI), the utilisation of AI-based clinical decision support systems (AI-CDSSs) has become increasingly prevalent in the medical domain, particularly in the management of cerebrovascular disease.
Aims: To describe the design, rationale and methods of a cluster-randomised multifaceted intervention trial aimed at investigating the effect of cerebrovascular disease AI-CDSS on the clinical outcomes of patients who had a stroke and on stroke care quality.
Design: The GOLDEN BRIDGE II trial is a multicentre, open-label, cluster-randomised multifaceted intervention study.
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