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.

Amsterdam School of Communication Research ASCoR University of Amsterdam Amsterdam The Netherlands

Department of Geriatric Medicine Odense University Hospital Odense Denmark

Department of Geriatrics and Gerontology 1st Faculty of Medicine Charles University Prague Czech Republic

Department of Gerontology Neuroscience and Orthopedics Catholic University of the Sacred Heart Rome Italy

Department of Internal Medicine and Paediatrics Ghent University Ghent Belgium

Department of Medical Informatics Amsterdam Public Health Research Institute Amsterdam UMC University of Amsterdam Amsterdam The Netherlands

Division of Geriatrics Department of Internal Medicine Istanbul Medical School Istanbul University Capa 34093 Istanbul Turkey

Division of Geriatrics Department of Internal Medicine Şişli Hamidiye Etfal Training and Research Hospital University of Medical Sciences Istanbul Turkey

Faculty of Health and Social Sciences South Bohemian University Ceske Budejovice Czech Republic

Geriatric Research Unit Department of Clinical Research University of Southern Denmark Odense Denmark

Health Care of Older People East Kent Hospitals University NHS Foundation Trust Canterbury Kent UK

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

Nottingham University Hospitals NHS Trust Nottingham UK

School of Pharmacy University of Eastern Finland Kuopio Finland

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

Servicio de Geriatría Hospital General Universitario de Ciudad Real Ciudad Real Spain

Trauma Center Wien Meidling Kundratstrasse 37 1120 Vienna Austria

Wee Kim Wee School of Communication and Information Nanyang Technological University Singapore Singapore

See more in PubMed

de Vries M et al (2018) Fall-risk-increasing drugs: a systematic review and meta-analysis: I. Cardiovascular drugs. J Am Med Dir Assoc 19(4):371.e1-371.e9 DOI

Seppala LJ et al (2018) Fall-risk-increasing drugs: a systematic review and meta-analysis: II. Psychotropics. J Am Med Dir Assoc 19:371

Seppala LJ et al (2018) Fall-risk-increasing drugs: a systematic review and meta-analysis: III. Others. J Am Med Dir Assoc 19:371

Gillespie S, Robertson LD, Gillespie MC, Sherrington WJ, Gates C, Clemson S, Lamb LM (2012) Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev 9:2012

Laflamme L, Monárrez-Espino J, Johnell K, Elling B, Möller J (2015) Type, number or both? A population-based matched case-control study on the risk of fall injuries among older people and number of medications beyond fall-inducing drugs. PLoS ONE 10(3):1–12 DOI

Clemson L, Stark S, Pighills AC, Torgerson DJ, Sherrington C, Lamb SE (2019) Environmental interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev 2:2019

Seppala LJ et al (2019) EuGMS task and finish group on fall-risk-increasing drugs (FRIDs): position on knowledge dissemination, management, and future research. Eur Geriatr Med 10(2):275–283 DOI

Bell HT, Steinsbekk A, Granas AG (2015) Factors influencing prescribing of fall-risk-increasing drugs to the elderly: a qualitative study. Scand J Prim Health Care 33(2):107–114 DOI

Strickland J (2015) Translational Biomedical Informatics: A Precision Medicine Perspective, ISBN : 9789811015038

Monteiro L, Maricoto T, Solha I, Ribeiro-Vaz I, Martins C, Monteiro-Soares M (2019) Reducing potentially inappropriate prescriptions for older patients using computerized decision support tools—a systematic review (Preprint). J Med Internet Res 21:11 DOI

Groshaus H, Boscan A, Khandwala F, Holroyd-Leduc J (2012) Use of clinical decision support to improve the quality of care provided to older hospitalized patients. Appl Clin Inform 3(1):94–102 DOI

Meulendijk MC et al (2015) Computerized decision support improves medication review effectiveness: an experiment evaluating the STRIP assistant’s usability. Drugs Aging 32(6):495–503 DOI

Nanji KC et al (2018) Medication-related clinical decision support alert overrides in inpatients. J Am Med Inform Assoc 25(5):476–481 DOI

Van de Velde S et al (2018) A systematic review of trials evaluating success factors of interventions with computerised clinical decision support. Implement Sci 13(1):1–11 DOI

Grol R, Wensing M, Eccles M, Davis D (2005) Improving patient care: the implementation of change in health care, 2nd edn. Elsevier, Edinburgh

Jung M et al (2013) Attitude of physicians towards automatic alerting in computerized physician order entry systems: a comparative international survey. Methods Inf Med 52(2):99–108 DOI

Mulder-Wildemors LGM, Heringa M, Floor-Schreudering A, Jansen PAF, Bouvy ML (2020) Reducing Inappropriate drug use in older patients by use of clinical decision support in community pharmacy: a mixed-methods evaluation. Drugs Aging 37(2):115–123 DOI

Baysari MT, Westbrook JI, Egan B, Day RO (2013) Identification of strategies to reduce computerized alerts in an electronic prescribing system using a Delphi approach. Stud Health Technol Inform 192(1–2):8–12

Boyd CM, Kent DM (2014) Evidence-based medicine and the hard problem of multimorbidity. J Gen Intern Med 29(4):552–553 DOI

Chua AQ et al (2018) Psychosocial determinants of physician acceptance toward an antimicrobial stewardship program and its computerized decision support system in an acute care tertiary hospital. J Am Coll Clin Pharm 1(1):e1–e8 DOI

Trinkley KE et al (2019) Clinician preferences for computerised clinical decision support for medications in primary care: a focus group study. BMJ Heal Care Inf 26(1):1–8

Lupiáñez-Villanueva F et al (2018) Digital agenda for europe benchmarking deployment of eHealth among General Practitioners Internal identification. https://data.europa.eu/doi/10.2759/511610

UNSD (2016) UNSD—Standard country or area codes for statistical use (M49). In: 25. United Nations Statistics Division- Standard Country and Area Codes Classifications (M49). https://unstats.un.org/unsd/methodology/m49/

Kux BR, Majeed RW, Ahlbrandt J, Röhrig R (2017) Factors influencing the implementation and distribution of Clinical Decision Support Systems (CDSS). Stud Health Technol Inform 243:127–131

Lamb SE, Jørstad-Stein EC, Hauer K, Becker C (2005) Development of a common outcome data set for fall injury prevention trials: the prevention of falls network Europe consensus. J Am Geriatr Soc 53(9):1618–1622 DOI

Westerbeek L et al (2021) Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: a systematic review. Int J Med Inform 152:104506 DOI

Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q Manag Inf Syst 13(3):319–339 DOI

Lunney GH (1970) Using analysis of variance with a dichotomous dependent variable: an empirical study 1. J Educ Meas 7(4):263–269 DOI

Lapane KL, Waring ME, Schneider KL, Dubé C, Quilliam BJ (2008) A mixed method study of the merits of e-prescribing drug alerts in primary care. J Gen Intern Med 23(4):442–446 DOI

Tsopra R, Jais JP, Venot A, Duclos C (2014) Comparison of two kinds of interface, based on guided navigation or usability principles, for improving the adoption of computerized decision support systems: application to the prescription of antibiotics. J Am Med Inf Assoc 21(E2):107–116 DOI

Sirajuddin AM, Osheroff JA, Sittig DF, Chuo J, Velasco F, Collins DA (2009) Implementation pearls from a new guidebook on improving medication use and outcomes with clinical decision support. Effective CDS is essential for addressing healthcare performance improvement imperatives. J Healthc Inf Manag 23(4):38–45

Gagnon MP, Nsangou ÉR, Payne-Gagnon J, Grenier S, Sicotte C (2014) Barriers and facilitators to implementing electronic prescription: a systematic review of user groups’ perceptions. J Am Med Informatics Assoc 21(3):535–541 DOI

Mooijaart SP et al (2015) Evidence-based medicine in older patients: How can we do better? Neth J Med 73(5):211–218

Herrera AP, Snipes SA, King DW, Torres-Vigil I, Goldberg DS, Wenberg AD (2010) Disparate inclusion of older adults in clinical trials: priorities and opportunities for policy and practice change. Am J Public Health 100(SUPPL. 1):105–112 DOI

Hofstede G, Hofstede GJ, Minkov M (2010) Cultures and organisation, software of the mind, intercultural cooperation and its importance. ISBN: 978-0-07-177015-6

Singler K, Holm EA, Jackson T, Robertson G, Müller-Eggenberger E, Roller RE (2015) European postgraduate training in geriatric medicine: data of a systematic international survey. Aging Clin Exp Res 27(5):741–750 DOI

Michel JP et al (2008) Europe-wide survey of teaching in geriatric medicine. J Am Geriatr Soc 56(8):1536–1542 DOI

A European survey of older peoples' preferences, and perceived barriers and facilitators to inform development of a medication-related fall-prevention patient portal

Deprescribing practices, habits and attitudes of geriatricians and geriatricians-in-training across Europe: a large web-based survey