Kim J Ploegmakers1, Stephanie Medlock2, Annemiek J Linn3, Yumin Lin3,4, Lotta J Seppälä5, Mirko Petrovic6, Eva Topinkova7,8, Jesper Ryg9,10, Maria Angeles Caballero Mora11, Francesco Landi12, Heinrich Thaler13, Katarzyna Szczerbińska14, Sirpa Hartikainen15, Gulistan Bahat16, Birkan Ilhan17, Yvonne Morrissey18, Tahir Masud19, Nathalie van der Velde5, Julia C M van Weert3. 1. Section of Geriatric Medicine, Department of Internal Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, D3-227, Meibergdreef 9, Amsterdam, 1105AZ, The Netherlands. k.j.ploegmakers@amsterdamumc.nl. 2. Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands. 3. Amsterdam School of Communication Research/ASCoR, University of Amsterdam, Amsterdam, The Netherlands. 4. Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore. 5. Section of Geriatric Medicine, Department of Internal Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, D3-227, Meibergdreef 9, Amsterdam, 1105AZ, The Netherlands. 6. Department of Internal Medicine and Paediatrics (Section of Geriatrics), Ghent University, Ghent, Belgium. 7. Department of Geriatrics and Gerontology, 1st Faculty of Medicine, Charles University, Prague, Czech Republic. 8. Faculty of Health and Social Sciences, South Bohemian University, Ceske Budejovice, Czech Republic. 9. Department of Geriatric Medicine, Odense University Hospital, Odense, Denmark. 10. Geriatric Research Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark. 11. Servicio de Geriatría, Hospital General Universitario de Ciudad Real , Ciudad Real, Spain. 12. Department of Gerontology, Neuroscience and Orthopedics, Catholic University of the Sacred Heart, Rome, Italy. 13. Trauma Center Wien-Meidling, Kundratstrasse 37, 1120, Vienna, Austria. 14. Laboratory for Research on Aging Society, Department of Sociology of Medicine, Epidemiology and Preventive Medicine Chair, Faculty of Medicine, Jagiellonian University Medical College, Kraków, Poland. 15. School of Pharmacy, University of Eastern Finland, Kuopio, Finland. 16. Division of Geriatrics, Department of Internal Medicine, Istanbul Medical School, Istanbul University, Capa, 34093, Istanbul, Turkey. 17. Division of Geriatrics, Department of Internal Medicine, Şişli Hamidiye Etfal Training and Research Hospital, University of Medical Sciences, Istanbul, Turkey. 18. Health Care of Older People, East Kent Hospitals University NHS Foundation Trust, Canterbury, Kent, UK. 19. Nottingham University Hospitals NHS Trust, Nottingham, UK.
Abstract
PURPOSE: Fall-Risk Increasing Drugs (FRIDs) are an important and modifiable fall-risk factor. A Clinical Decision Support System (CDSS) could support doctors in optimal FRIDs deprescribing. Understanding barriers and facilitators is important for a successful implementation of any CDSS. We conducted a European survey to assess barriers and facilitators to CDSS use and explored differences in their perceptions. METHODS: We examined and compared the relative importance and the occurrence of regional differences of a literature-based list of barriers and facilitators for CDSS usage among physicians treating older fallers from 11 European countries. RESULTS: We surveyed 581 physicians (mean age 44.9 years, 64.5% female, 71.3% geriatricians). The main barriers were technical issues (66%) and indicating a reason before overriding an alert (58%). The main facilitators were a CDSS that is beneficial for patient care (68%) and easy-to-use (64%). We identified regional differences, e.g., expense and legal issues were barriers for significantly more Eastern-European physicians compared to other regions, while training was selected less often as a facilitator by West-European physicians. Some physicians believed that due to the medical complexity of their patients, their own clinical judgement is better than advice from the CDSS. CONCLUSION: When designing a CDSS for Geriatric Medicine, the patient's medical complexity must be addressed whilst maintaining the doctor's decision-making autonomy. For a successful CDSS implementation in Europe, regional differences in barrier perception should be overcome. Equipping a CDSS with prediction models has the potential to provide individualized recommendations for deprescribing FRIDs in older falls patients.
PURPOSE: Fall-Risk Increasing Drugs (FRIDs) are an important and modifiable fall-risk factor. A Clinical Decision Support System (CDSS) could support doctors in optimal FRIDs deprescribing. Understanding barriers and facilitators is important for a successful implementation of any CDSS. We conducted a European survey to assess barriers and facilitators to CDSS use and explored differences in their perceptions. METHODS: We examined and compared the relative importance and the occurrence of regional differences of a literature-based list of barriers and facilitators for CDSS usage among physicians treating older fallers from 11 European countries. RESULTS: We surveyed 581 physicians (mean age 44.9 years, 64.5% female, 71.3% geriatricians). The main barriers were technical issues (66%) and indicating a reason before overriding an alert (58%). The main facilitators were a CDSS that is beneficial for patient care (68%) and easy-to-use (64%). We identified regional differences, e.g., expense and legal issues were barriers for significantly more Eastern-European physicians compared to other regions, while training was selected less often as a facilitator by West-European physicians. Some physicians believed that due to the medical complexity of their patients, their own clinical judgement is better than advice from the CDSS. CONCLUSION: When designing a CDSS for Geriatric Medicine, the patient's medical complexity must be addressed whilst maintaining the doctor's decision-making autonomy. For a successful CDSS implementation in Europe, regional differences in barrier perception should be overcome. Equipping a CDSS with prediction models has the potential to provide individualized recommendations for deprescribing FRIDs in older falls patients.