Clinical decision-making in benzodiazepine deprescribing by healthcare providers vs. AI-assisted approach.

AIMS: The aim of this study was to compare the clinical decision-making for benzodiazepine deprescribing between a healthcare provider (HCP) and an artificial intelligence (AI) chatbot GPT4 (ChatGPT-4). METHODS: We analysed real-world data from a Croatian cohort of community-dwelling benzodiazepine patients (n = 154) within the EuroAgeism H2020 ESR 7 project. HCPs evaluated the data using pre-established deprescribing criteria to assess benzodiazepine discontinuation potential. The research team devised and tested AI prompts to ensure consistency with HCP judgements. An independent researcher employed ChatGPT-4 with predetermined prompts to simulate clinical decisions for each patient case. Data derived from human-HCP and ChatGPT-4 decisions were compared for agreement rates and Cohen's kappa. RESULTS: Both HPC and ChatGPT identified patients for benzodiazepine deprescribing (96.1% and 89.6%, respectively), showing an agreement rate of 95% (κ = .200, P = .012). Agreement on four deprescribing criteria ranged from 74.7% to 91.3% (lack of indication κ = .352, P < .001; prolonged use κ = .088, P = .280; safety concerns κ = .123, P = .006; incorrect dosage κ = .264, P = .001). Important limitations of GPT-4 responses were identified, including 22.1% ambiguous outputs, generic answers and inaccuracies, posing inappropriate decision-making risks. CONCLUSIONS: While AI-HCP agreement is substantial, sole AI reliance poses a risk for unsuitable clinical decision-making. This study's findings reveal both strengths and areas for enhancement of ChatGPT-4 in the deprescribing recommendations within a real-world sample. Our study underscores the need for additional research on chatbot functionality in patient therapy decision-making, further fostering the advancement of AI for optimal performance.

Community-based pharmacists' role in deprescribing: A systematic review.

AIMS: Community-based pharmacists are an important stakeholder in providing continuing care for chronic multi-morbid patients, and their role is steadily expanding. The aim of this study is to examine the literature exploring community-based pharmacist-initiated and/or -led deprescribing and to evaluate the impact on the success of deprescribing and clinical outcomes. METHODS: Library and clinical trials databases were searched from inception to March 2020. Studies were included if they explored deprescribing in adults, by community-based pharmacists and were available in English. Two reviewers extracted data independently using a pre-agreed data extraction template. Meta-analysis was not performed due to heterogeneity of study designs, types of intervention and outcomes. RESULTS: A total of 24 studies were included in the review. Results were grouped based on intervention method into four categories: educational interventions; interventions involving medication review, consultation or therapy management; pre-defined pharmacist-led deprescribing interventions; and pharmacist-led collaborative interventions. All types of interventions resulted in greater discontinuation of medications in comparison to usual care. Educational interventions reported financial benefits as well. Medication review by community-based pharmacist can lead to successful deprescribing of high-risk medication, but do not affect the risk or rate of falls, rate of hospitalisations, mortality or quality of life. Pharmacist-led medication review, in patients with mental illness, resulting in deprescribing improves anticholinergic side effects, memory and quality of life. Pre-defined pharmacist-led deprescribing did not reduce healthcare resource consumptions but can contribute to financial savings. Short follow-up periods prevent evaluation of long-term sustainability of deprescribing interventions. CONCLUSION: This systematic review suggests community-based pharmacists can lead deprescribing interventions and that they are valuable partners in deprescribing collaborations, providing necessary monitoring throughout tapering and post-follow-up to ensure the success of an intervention.

Identifying self-assessed competencies and areas for improvement within community pharmacist-preceptors support during pre-registration training.

BACKGROUND: Competency frameworks that prompt personal and professional development have become an important component of lifelong learning; they are driven by healthcare professionals' need for development and professional recognition. This study aimed to evaluate the self-assessed competencies of community pharmacist-preceptors by using Croatian Competency Framework (CCF) and to identify competencies to be improved. The secondary aim was to explore the association between community pharmacists' characteristics (i.e. age, education etc.) and self-assessed competency performance. METHODS: The study subjects were community pharmacist-preceptors who provide support to and mentor student trainees enrolled in pre-registration training for pharmacy students. At the beginning of their mentorship, the pharmacist-preceptors assessed their competencies on a four-point Likert scale by using the Croatian Competency Framework (CCF), a validated tool for assessment and self-assessment of community and hospital pharmacists. Data were collected via e-mail in the period from October 2015 to April 2016. RESULTS: Of the 260 community pharmacists approached, final analysis included 223 respondents. The response rate was 85.8%. Community pharmacist-preceptors assessed themselves as the most competent in competencies pertaining to the cluster "Organization and management competencies" (M = 3.64, SD = 0.34), while they considered themselves as the least competent in the competencies pertaining to the cluster "Pharmaceutical public health competencies" (M = 2.75, SD = 0.77). Younger pharmacists with a postgraduate qualification who worked for large pharmacy chains in the capital city area and who had been in their current posts for a shorter period perceived themselves to be more competent. CONCLUSION: This research represents the first analysis of the CCF in practice and identifies community pharmacist-preceptor competencies that require improvement. Consequently, areas for additional professional education were defined. Implementing modalities to measure and support development of preceptors' competences is essential for improvement of student training programmes.

Deprescribing potential of commonly used medications among community-dwelling older adults: insights from a pharmacist's geriatric assessment.

Pharmacist's geriatric assessment can provide valuable insights into potential deprescribing targets, while including important information on various health-related domains. Data collected from a geriatric assessment questionnaire, for 388 patients, from the Croatian cohort of the EuroAgeism H2020 ESR 7 international project, along with guideline-based deprescribing criteria, were used to analyse potentially inappropriate prescribing of four medication groups (benzodiazepines (BZN), proton pump inhibitors (PPI), opioids, and non-steroidal anti-inflammatory drugs (NSAID)), and to assess the deprescribing potential. Binary logistic regression was used to explore the effects of age, gender, number of medicines and diagnoses, self-reported health, frailty score, and healthcare utilization on the likelihood of needing deprescribing. More than half of participants (n = 216, 55.2%) are candidates for deprescribing, with 31.1% of PPI, 74.8% of NSAID, 75% of opioid, and 96.1% of BZN users meeting at least one criterion. Most common criteria for deprescribing were inappropriately long use and safety concerns. Women (aOR = 2.58; p < 0.001), those reporting poor self-reported health (aOR = 5.14; p < 0.001), and those exposed to polypharmacy (aOR = 1.29; p < 0.001) had higher odds of needing to have medicines deprescribed. The high rate of deprescribing potential warrants prompt action to increase patient safety and decrease polypharmacy. Pharmacist's geriatric assessment and deprescribing-focused medication review could be used to lead a personalised approach.