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This study aimed to describe the use of recommendations as a guide for healthcare providers to support patients experiencing medication self‐management problems and to evaluate their feasibility, user‐friendliness and usefulness. Between March and August 2023, 58 hospitalized patients completed a self‐assessment on medication self‐management problems. The problems addressed in this self‐assessment were based on a list of frequently encountered medication self‐management problems from previous research. Consequently, 18 nurses responded to the reported problems using the recommendations. Nurses evaluated the feasibility, user‐friendliness and usefulness of these recommendations through a survey. A total of 217 medication self‐management problems were reported by 58 patients. Nurses intervened in 52% of the problems using the recommendations. According to nurses, the recommendations were user‐friendly and feasible but required a substantial time investment. Considering these pilot‐based results, the recommendations have the potential to be a valuable resource for nurses in practice, though this potential requires further exploration. [ABSTRACT FROM AUTHOR]

Objective: To perform a cost study of pharmacist-led medication reviews in patients with an acute hospitalization for adverse drug events. Method: Emergency department pharmacists performed medication reviews in patients hospitalized after visiting the emergency department for an adverse drug event (ADE). Control patients were hospitalized after an emergency department visit not related to an ADE and received usual care. The costs of the intervention were labour costs of the junior emergency department pharmacist and the cost savings consisted of costs of medication that was stopped or reduced during six months after the intervention. Sensitivity analyses were performed to evaluate different scenarios. Results: In the intervention group (n = 104) 113 medication changes led to stopping or reducing medication, accounting for averted costs of €22,850. In the control group (n = 112) 39 medication changes led to stopping or reducing medication, accounting for averted costs of €299. The mean labour costs of the intervention were €138 per patient, resulting in saved costs of €61 per patient per six months. Sensitivity analyses showed that if the intervention would be performed by a senior clinical pharmacist, there are no cost savings (€-21), if parts of the intervention would be executed by pharmacy technicians (e.g. administrative tasks), cost savings would be augmented to €87, if outliers in costs associated with medication reduction would be excluded, there are no cost savings (€-35) and if the costs of reduced medication were extrapolated to one year, cost savings would be €260. Conclusion: In this study, medication reviews by junior emergency department pharmacists in patients hospitalized after an emergency department visit for an ADE lead to a cost reduction over a six month period. Trial registration: The main study is registered on the ISRCTN registry with trial ID ISRCTN12506329 on 06-03-2022. [ABSTRACT FROM AUTHOR]

Background In the last decade, a fundamental shift in the treatment of cystic fibrosis (CF) took place due to the introduction of CF transmembrane conductance regulator (CFTR) modulators. Adequate medication adherence is a prerequisite for their effectiveness, but little is known about adherence to CFTR modulators. We aimed to assess the extent of medication adherence to CFTR modulators in patients with CF and assess which characteristics are associated with adherence. Methods A systematic review following PRISMA guidelines was performed. Studies needed to report adherence to CFTR modulators. Main outcomes were: 1) level of medication adherence and 2) associations of demographic and/or clinical characteristics with adherence. Results In total, 4082 articles were screened and 21 full-text papers were assessed for eligibility. Ultimately, seven studies were included. Most studies were retrospective and focused on adherence to ivacaftor or lumacaftor–ivacaftor with only one focusing on elexacaftor–tezacaftor–ivacaftor. The majority used pharmacy refill data with adherence determined with the proportion of days covered (PDC) or the medication possession ratio (MPR). One study additionally used electronic monitoring and patient self-reported adherence. Adherence was 0.62–0.99 based on pharmacy data (PDC or MPR), 61% via electronic monitoring and 100% via self-report. Age <18 years appeared to be associated with good adherence, as was a higher lung function. Conclusions Despite the wide variety of adherence methods used, adherence to CFTR modulators is suboptimal, based on objective measures such as pharmacy refill data or electronic monitoring. CFTR modulator adherence measurement and definitions requires more standardisation with a preference for objective and granular methods. [ABSTRACT FROM AUTHOR]

Prescribing cascades occur when patients are prescribed medication to treat the adverse drug reaction of previously prescribed medication. Prescription sequence symmetry analysis (PSSA) can be used to assess the association between two medications in prescription or dispensing databases and thus the potential occurrence of prescribing cascades. In this article, a step-by-step guide is presented for conducting PSSA to assess prescribing cascades. We describe considerations for medication data collection and setting time periods for relevant parameters, including washout window, exposure window, continued exposure interval and blackout period. With two examples, we illustrate the impact of changes in these parameters on the strengths of associations observed. Given the impact seen, we recommend that researchers clearly specify and explain all considerations regarding medication included and time windows set when studying prescribing cascades with PSSA, and conduct subgroup and sensitivity analyses. [ABSTRACT FROM AUTHOR]

Background: A prescribing cascade occurs when medication causes an adverse drug reaction (ADR) that leads to the prescription of additional medication. Prescribing cascades can cause excess medication burden, which is of particular concern in older adults. This study aims to identify and quantify potentially problematic prescribing cascades relevant for clinical practice., Methods: A mixed-methods study was conducted. First, prescribing cascades were identified through literature search. An expert panel (n = 16) of pharmacists and physicians assessed whether these prescribing cascades were potentially problematic. Next, a cohort study quantified potentially problematic prescribing cascades in adults using Dutch community pharmacy data for the period 2015-2020. Additionally, the influence of multiple medications potentially causing the same ADR was evaluated. Prescription sequence symmetry analysis was used to calculate adjusted sequence ratios (aSRs), adjusting for temporal prescribing trends. An aSR >1.0 indicates the occurrence of a prescribing cascade. In a subgroup analysis, aSRs were calculated for older adults., Results: Seventy-six prescribing cascades were identified in literature and three were provided by experts. Of these, 66 (83.5%) were considered potentially problematic. A significant positive aSR for the medication sequence was found for 41 (62.1%) of these prescribing cascades. The highest aSR was found for amiodarone potentially causing hypothyroidism treated with thyroid hormones (4.63 [95% confidence interval 4.40-4.85]), based on 565 incident users. The biggest population (n = 34,645) was found for angiotensin converting enzyme-inhibitors potentially causing urinary tract infections treated with antibiotics. Regarding four potential ADRs, the aSRs were higher for people using multiple medications that cause the same ADR as compared to people using only one of those medications. Among older adults the aSRs remained significant for 37 prescribing cascades., Conclusion: An overview was generated of potentially problematic prescribing cascades relevant for clinical practice. These results can support healthcare providers to intervene and reduce medication burden for older adults., (© 2024 The Author(s). Journal of the American Geriatrics Society published by Wiley Periodicals LLC on behalf of The American Geriatrics Society.)

Aims: Computerized decision support systems (CDSSs) aim to prevent adverse drug events. However, these systems generate an overload of alerts that are not always clinically relevant. Anticoagulants are frequently involved in these alerts. The aim of this study was to investigate the efficiency of CDSS alerts on anticoagulants in Dutch hospital pharmacies., Methods: A multicentre, single-day, cross-sectional study was conducted using a flashmob design in Dutch hospital pharmacies, which have CDSSs that operate on both a national medication surveillance database and on self-developed clinical rules. Hospital pharmacists and pharmacy technicians collected data on the number and type of alerts and time needed for assessing these alerts. The primary outcome was the CDSS efficiency on anticoagulants, defined as the percentage of alerts on anticoagulants that led to an intervention. Secondary outcomes where among other CDSSs efficiency related to any medications and the time expenditure. Descriptive data-analysis was used., Results: Of the 69 hospital pharmacies invited, 42 (61%) participated. The efficiency of CDSS alerts on anticoagulants was 4.0% (interquartile range [IQR] 14.0%) for the national medication surveillance database alerts and 14.3% (IQR 40.0%) for alerts from clinical rules. For any medication, the efficiency was lower: 1.8% (IQR 7.5%) and 13.4% (IQR 21.5%) respectively. The median time for assessing the relevance of all alerts was 2 (IQR 1:21) h/day for pharmacists and 6 (IQR 5:01) h/day for pharmacy technicians., Conclusion: CDSS efficiency is generally low, both for anticoagulants and any medication, while the time investment is high. Optimization of CDSSs is needed., (© 2024 The Author(s). British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Objectives: Patients on oral anticancer therapy regularly experience medication-related problems (MRPs), potentially leading to non-adherence and medication waste. Most studies reporting these experiences have cross-sectional designs. The aim of our study was to explore patient reported MRPs, adherence and waste of oral anticancer medication over time., Methods: A prospective longitudinal quantitative interview study with 4 months follow-up was performed among patients on oral anticancer medication (mainly tyrosine kinase inhibitors, (anti)hormonal therapy, pyrimidine antagonists) using a semi-structured questionnaire. Patients from two Dutch university medical centres were included from March to December 2022 after informed consent was given. Four interviews were performed with 1 month in between. All interviews were audiotaped, after which the data were entered into an electronic case report form. The primary outcome was the mean number of MRPs per patient per interview round. Secondary outcomes were the proportion of patients with at least one MRP, types of MRPs, perceived non-adherence, medication waste (both in general and specifically for anticancer medication), costs of anticancer medication waste, and factors associated with medication waste as mentioned by the patient. Descriptive statistics were used to analyse the data., Results: Forty patients were included with a mean (SD) age of 64 (9) years; 43% were male. The mean number of MRPs per patient was 2.1 in the first interview and 1.2, 1.0 and 0.9 in the second, third and fourth interviews, respectively. Adverse drug reactions were the most frequently reported type of MRPs (30 (75%) patients in the first interview and 19 (65%) in the last interview). Unintentional non-adherence was regularly reported, especially in the first interview. Medication changes were frequent and associated medication waste was mentioned in all interviews., Conclusions: Many patients using oral anticancer treatment report MRPs and this number remains substantial over time., Competing Interests: Competing interests: None declared., (© European Association of Hospital Pharmacists 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Antithrombotics require careful monitoring to prevent adverse events. Safe use can be promoted through so-called antithrombotic stewardship. Clinical decision support systems (CDSSs) can be used to monitor safe use of antithrombotics, supporting antithrombotic stewardship efforts. Yet, previous research shows that despite these interventions, antithrombotics continue to cause harm. Insufficient adoption of antithrombotic stewardship and suboptimal use of CDSSs may provide and explanation. However, it is currently unknown to what extent hospitals adopted antithrombotic stewardship and utilize CDSSs to support safe use of antithrombotics. A semi-structured questionnaire-based survey was disseminated to 12 hospital pharmacists from different hospital types and regions in the Netherlands. The primary outcome was the degree of antithrombotic stewardship adoption, expressed as the number of tasks adopted per hospital and the degree of adoption per task. Secondary outcomes included characteristics of CDSS alerts used to monitor safe use of antithrombotics. All 12 hospital pharmacists completed the survey and report to have adopted antithrombotic stewardship in their hospital to a certain degree. The median adoption of tasks was two of five tasks (range 1-3). The tasks with the highest uptake were: drafting and maintenance of protocols (100%) and professional's education (58%), while care transition optimization (25%), medication reviews (8%) and patient counseling (8%) had the lowest uptake. All hospitals used a CDSS to monitor safe use of antithrombotics, mainly via basic alerts and less frequently via advanced alerts. The most frequently employed alerts were: identification of patients using a direct oral anticoagulant (DOAC) or a vitamin K antagonist (VKA) with one or more other antithrombotics (n = 6) and patients using a VKA to evaluate correct use (n = 6), both reflecting basic CDSS. All participating hospitals adopted antithrombotic stewardship, but the adopted tasks vary. CDSS alerts used are mainly basic in their logic., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: RH is a CMO at Gaston Medical which is a software company that develops medical decision support systems. The other authors report no conflicts., (Copyright: © 2024 Graafsma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Current Clinical Decision Support Systems (CDSSs) generate medication alerts that are of limited clinical value, causing alert fatigue. Artificial Intelligence (AI)-based methods may help in optimizing medication alerts. Therefore, we conducted a scoping review on the current state of the use of AI to optimize medication alerts in a hospital setting. Specifically, we aimed to identify the applied AI methods used together with their performance measures and main outcome measures., Materials and Methods: We searched Medline, Embase, and Cochrane Library database on May 25, 2023 for studies of any quantitative design, in which the use of AI-based methods was investigated to optimize medication alerts generated by CDSSs in a hospital setting. The screening process was supported by ASReview software., Results: Out of 5625 citations screened for eligibility, 10 studies were included. Three studies (30%) reported on both statistical performance and clinical outcomes. The most often reported performance measure was positive predictive value ranging from 9% to 100%. Regarding main outcome measures, alerts optimized using AI-based methods resulted in a decreased alert burden, increased identification of inappropriate or atypical prescriptions, and enabled prediction of user responses. In only 2 studies the AI-based alerts were implemented in hospital practice, and none of the studies conducted external validation., Discussion and Conclusion: AI-based methods can be used to optimize medication alerts in a hospital setting. However, reporting on models' development and validation should be improved, and external validation and implementation in hospital practice should be encouraged., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)