Using risk prediction to case-find frail older people at risk of anticholinergic burden for Structured Medication Reviews: a qualitative study exploring the views and perspectives of primary care professionals. (1st April 2022)

• Record Type: Journal Article
• Authors: Mehdizadeh, D; Johnson, O; Petty, D; Faisal, M; Gardner, P
• Is Part Of: International journal of pharmacy practice. Volume 30(2022)Supplement 1
• Page Start: i4
• Page End: i4
• Publication Date: 2022-04-01
• Subjects: Pharmacy -- Practice -- Periodicals; 615.1
• DOI: 10.1093/ijpp/riac021.005
• Languages: English
• ISSNs: 0961-7671

Abstract

Abstract: Introduction: Reviewing anticholinergic medicines is an important consideration in the safe care of frail older people. The cumulative effect of taking multiple anticholinergic medicines, known as anticholinergic burden (AB) (1), is associated with physical and cognitive decline, falls, and hospitalisation (2). There is a need to explore the development of integrated tools within clinical IT systems, to support safer prescribing. This includes the use of risk prediction, to case-find frail older patients at risk of AB for structured medication reviews (SMRs). However, using risk prediction in this context is a new concept, and perspectives of end-users in primary care are unknown. Aim: To explore health care professionals' (HCPs) views and perspectives of risk prediction, to case-find frail older people at risk of AB for SMRs, in order to inform future development and implementation. Methods: In-depth, semi-structured interviews conducted virtually. Data analysis used the inductive thematic analysis method, using Nvivo 12. Recruitment involved advertising a flyer on social media, and snowball sampling. A purposive sample of twenty-five HCPs in primary care were interviewed, including pharmacy professionals, GPs, nurses, and a community-based geriatrician. Results: Six core themes emerged as important factors for future development and implementation, and were mapped to the Theoretical Domains Framework: knowledge and skills, beliefs about capabilities and consequences, decision processes, professional role and identity, motivation and goals, and environmental context and resources. HCPs supported the concept of risk prediction to case-find patients, particularly for more efficient utilisation of health resources. However, despite feeling motivated to reduce anticholinergic prescribing in frail older people, deprescribing in this area was deemed complex, with multiple barriers. A case-finding tool was perceived to be important, but considered only one element of a multi-factorial approach towards safer prescribing, with various other factors influencing decision making processes. HCPs felt prescribing decisions should be made holistically, and not influenced entirely by the outputs of a validated risk prediction tool. Lacking a deeper understanding of AB and frailty was also expressed, with further education and upskilling in deprescribing deemed essential to support uptake. There were concerns that proactive case-finding would lead to an unsustainable number of SMRs. Potential facilitators of future uptake were also identified, including the expansion of the primary care workforce, and financial incentivisation for deprescribing. Conclusion: The concept of a future risk prediction tool was seen positively by HCPs, supporting a case for its development to facilitate the case-finding of at-risk patients for SMRs, in line with NHS policy. However, this study has identified multiple factors which could influence future uptake, having implications for the design and implementation stages. Strengths include the use of inductive thematic analysis, and how in-depth interviews were conducted with a variety of HCPs. Seeking views and perspectives of a risk prediction tool that is currently not in existence has its limitations however, but indeed are invaluable as early insights. HCPs as potential end-users, in addition to patients and the public, are crucial to future developmental phases and must be included as partners in any further research efforts. References: (1) Hilmer SN, Gnjidic D. Prescribing for frail older people. Aust Prescr. 2017;40(5):174-178. doi:10.18773/austprescr.2017.055 (2) Welsh TJ, van der Wardt V, Ojo G, Gordon AL, Gladman JRF. Anticholinergic Drug Burden Tools/Scales and Adverse Outcomes in Different Clinical Settings: A Systematic Review of Reviews. Drugs Aging. 2018 Jun;35(6):523-538. doi: 10.1007/s40266-018-0549-z. PMID: 29736815. Funding disclaimer: This research was funded by the National Institute for Health Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR YHPSTRC). The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care.