This umbrella review examined systematic reviews of deprescribing studies by characteristics of intervention, population, medicine, and setting. Clinical and humanistic outcomes, barriers and facilitators, and tools for deprescribing are presented. The Medline database was used. The search was limited to systematic reviews and meta-analyses published in English up to April 2022. Reviews reporting deprescribing were included, while those where depre-scribing was not planned and supervised by a healthcare professional were excluded. A total of 94 systematic reviews (23 meta--analyses) were included. Most explored clinical or humanistic outcomes (70/94, 74 %); less explored attitudes, facilitators, or barriers to deprescribing (17/94, 18 %); few focused on tools (8/94, 8.5 %). Reviews assessing clinical or humanistic outcomes were divided into two groups: reviews with deprescribing intervention trials (39/70, 56 %; 16 reviewing specific deprescribing interventions and 23 broad medication optimisation interventions), and reviews with medication cessation trials (31/70, 44 %). Deprescribing was feasible and resulted in a reduction of inappropriate medications in reviews with deprescribing intervention trials. Complex broad medication optimisation interventions were shown to reduce hospitalisation, falls, and mortality rates. In reviews of medication cessation trials, a higher frequency of adverse drug withdrawal events underscores the importance of prioritizing patient safety and exercising caution when stopping medicines, particularly in patients with clear and appropriate indications.

OBJECTIVE: The Drug Burden Index (DBI) calculates a person\'s exposure to anticholinergic and sedative medications. We aimed to review randomized controlled trials (RCTs) of deprescribing interventions that reported the DBI as an outcome, their characteristics, effectiveness in reducing the DBI, and impact on other outcomes.
METHODS: Systematic review with meta-analysis.
METHODS: RCTs of deprescribing interventions where the DBI was measured as a primary or secondary outcome in humans within any setting were included.
METHODS: Electronic databases, citation indexes, and gray literature were searched from April 1, 2007, to September 1, 2023. Quality was assessed using the Cochrane risk-of-bias tool.
RESULTS: Of 1721 records identified, 9 met the inclusion criteria. Six interventions were delivered by pharmacists and 3 were delivered by pharmacists/nurses or pharmacists/geriatricians. All interventions required at least intermediate-level skills and involved multiple components and target groups. Studies were conducted in the community (n = 5), nursing homes (n = 2), and hospitals (n = 2). The mean or median age was ≥75 years and most participants were women in all studies. Most (n = 6) studies were underpowered. The follow-up period ranged from 3 to 12 months. Three studies reported a lower DBI in the intervention group compared with control: 1 pharmacist independent prescriber-delivered in nursing homes (adjusted rate ratio, 0.83; 95% CI, 0.74 to 0.92), 1 pharmacist/nurse practitioner-delivered in hospital (adjusted mean difference (MD), -0.28; 95% CI, -0.51 to -0.04), and 1 geriatrician/pharmacist-delivered in hospital (MD, -0.28; 95% CI, -0.52 to -0.04). Meta-analysis showed no difference in the change in DBI between control and intervention groups in the community including nursing homes (MD, -0.03; 95% CI, -0.08 to 0.01) or hospital setting (MD, -0.19; 95% CI, -0.45 to 0.06). Interventions had inconsistent effects on cognition and no effect on other reported outcomes.
CONCLUSIONS: RCTs of deprescribing interventions had no significant impact on reducing DBI or improving outcomes. Further suitably powered studies are required.

BACKGROUND: Quality of life (QoL) is an important outcome to capture in clinical trials evaluating deprescribing interventions.
OBJECTIVE: We aimed to conduct a scoping review to examine how QoL has been measured in deprescribing trials among older people and identify potentially relevant QoL scales, to better inform QoL measurement in future deprescribing trials.
METHODS: We searched MEDLINE, Embase, PsycINFO, the Cochrane Central Register of Controlled Trials, Google Scholar, Epistemonikos, ClinicalTrials.gov, and reference lists of eligible studies (from inception to October 2023). We included randomized and non-randomized comparative studies with a control group that evaluated deprescribing and polypharmacy reduction interventions in people ≥ 65 years of age and measured QoL as an outcome. We also included studies describing the development and validation of QoL scales related to deprescribing, polypharmacy, or medication burden in adults ≥ 18 years of age. Two independent reviewers screened titles and abstracts, then full texts. Two independent reviewers extracted data from 25% of eligible studies in order to verify agreement, then a single reviewer extracted data from the remaining studies, which a second reviewer cross-checked. We critically appraised scales based on the COSMIN checklist.
RESULTS: We retrieved 7290 articles, of which 52 were eligible for inclusion, including 44 deprescribing trials and eight scale development studies. From these studies, we found 21 scales that have been used in the context of deprescribing/polypharmacy (12 generic scales used in clinical trials and nine medication-specific scales). Variations of the generic EQ-5D were the most used scales. The measurement properties of scales for capturing changes in QoL from deprescribing were uncertain. Medication-specific QoL scales have not been employed in deprescribing clinical trials and thus, their performance in this context is also not clear.
CONCLUSIONS: Several existing QoL scales have been applied to the context of deprescribing/polypharmacy clinical trials, and new scales specific to the problem have been proposed. If deprescribing does impact QoL, our findings suggest it is uncertain whether existing QoL scales can practically and reliably capture such a change or whether any scale is best. However, this review compares various aspects of the scales that researchers and clinicians can consider in decisions about measuring QoL in deprescribing trials, and in planning future research.
BACKGROUND: Open Science Framework: osf.io/aez6w.

Inappropriate polypharmacy is a common occurrence in elderly patients, resulting in increased adverse drug reactions, nonadherence, and increased healthcare costs. Medication review and deprescribing are the primary strategies described in the literature for dealing with problematic polypharmacy. To effectively carry out the medication review, various tools have been developed. These tools can support medication review in a variety of ways. Some tools include a list of medications requiring detailed attention, while others guide medical professionals with principles and algorithms for reviewing and prescribing medicines. A third category of tools focuses on tracking and identifying symptoms that may be due to drug-related problems.

Recent medical advancements have increased life expectancy, leading to a surge in patients affected by multiple chronic diseases and consequent polypharmacy, especially among older adults. This scenario increases the risk of drug interactions and adverse drug reactions, highlighting the need for medication review and deprescribing to reduce inappropriate medications and optimize therapeutic regimens, with the ultimate goal to improving patients\' health and quality of life. This position statement from the Italian Scientific Consortium on medication review and deprescribing aims to describe key elements, strategies, tools, timing, and healthcare professionals to be involved, for the implementation of medication review and deprescribing in different healthcare settings (i.e., primary care, hospital, long-term care facilities, and palliative care). Challenges and potential solutions for the implementation of medication review and deprescribing are also discussed.

Conduct a systematic review to investigate current beliefs, practices, perceptions, and motivations towards deprescribing practices from the healthcare professional perspective in older adults residing in long term care facilities with cardiometabolic conditions, using a narrative approach.
Studies were identified using a literature search of MEDLINE, CINAHL and Web of Science from inception to June 2023 Two reviewers (EH and AA) independently extracted data from each selected study using a standardised self-developed data extraction proforma. Studies reviewed included cross-sectional and observational studies. Data was extracted on baseline characteristics, motivations and beliefs and was discussed using a narrative approach.
Eight studies were identified for inclusion. Deprescribing approaches included complete withdrawal, dose reduction, or switching to an alternative medication, for at least one preventive medication. Most healthcare professionals were willing to initiate deprescribing strategies and stated the importance of such interventions, however many felt inexperienced and lacked the required knowledge to feel comfortable doing so.
Deprescribing is a key strategy when managing older people with cardiometabolic and multiple long term conditions (MLTC). Overall, HCPs including specialists, were happy to explore deprescribing strategies if provided with the relevant training and development to do so. Barriers that still exist include communication and consultation skills, a lack of evidence-based guidance and trust based policies, and a lack of MDT communications and involvement.
PROSPERO CRD42022335106.

Deprescribing is an important intervention across different settings in medicine, but the literature supporting such a practice is still conflicting. Therefore, we aimed to capture the breadth of outcomes reported and assess the strength of evidence of the use of deprescribing for health outcomes.
Umbrella review of systematic reviews of the use of deprescribing searching in Medline, Scopus, and Web of Science until 01 November 2023. The grading of evidence was carried out using the GRADE for intervention studies, whilst data regarding systematic reviews were reported as narrative findings.
Among 456 papers, 12 systematic reviews (six with meta-analysis) for a total of 231 RCTs and 44,193 patients were included. In any setting, deprescribing was able to significantly reduce the number of total and of potentially inappropriate medications (PIMs) in older patients (low certainty of evidence) and to reduce the proportion of participants potentially having several or PIMs (moderate certainty of evidence). In community, supported by a high certainty of evidence, deprescribing was not more effective than standard care in decreasing injurious falls, any falls or number of fallers. In nursing home, deprescribing was associated with a significantly lower PIMs than standard care (very low certainty of evidence). In end-of-life situations, deprescribing significantly reduced mortality rate of approximately 41% (high certainty of evidence).
Deprescribing is a promising intervention across different settings and situations, but a notable gap in the literature concerning its effects on substantial outcomes still exists.

OBJECTIVE: To summarise the evidence regarding which patients might benefit from deprescribing antihypertensive medications.
RESULTS: Older patients with frailty, multi-morbidity and subsequent polypharmacy are at higher risk of adverse events from antihypertensive treatment, and therefore may benefit from antihypertensive deprescribing. It is possible to examine an individual\'s risk of these adverse events, and use this to identify those people where the benefits of treatment may be outweighed by the harms. While such patients might be considered for deprescribing, the long-term effects of this treatment strategy remain unclear. Evidence now exists to support identification of those who are at risk of adverse events from antihypertensive treatment. These patients could be targeted for deprescribing interventions, although the long-term benefits and harms of this approach are unclear.
CONCLUSIONS: Randomised controlled trials are still needed to examine the long-term effects of deprescribing in high-risk patients with frailty and multi-morbidity.

OBJECTIVE: Overtreatment with glucose-lowering treatment (GLT) is frequent and a source of high morbidity and mortality in older adults with type 2 diabetes mellitus (T2DM). This study aimed to identify and synthesize barriers and enablers for deprescribing GLT in older adults (≥65 years) with T2DM.
METHODS: Systematic review of qualitative and mixed-methods studies.
METHODS: Older adults with T2DM, any participants [patients, health care providers (HCPs), caregivers], any settings.
METHODS: Two researchers (and a referred third researcher at all stages) independently screened original articles reporting qualitative and mixed-methods studies exploring barriers and enablers for deprescribing GLT in older adults published during 2010-2023, identified from MEDLINE, Embase, CINAHL, and gray literature. Quality of the included studies was assessed with the Mixed-Methods Appraisal Tool. Verbatim statements on barriers and enablers were extracted, and determinants of behaviors were identified with the Theoretical Domains Framework (TDF) version 2, and related intervention functions (targets for future interventions) were proposed according to the Behavior Change Wheel (BCW).
RESULTS: We identified only 4 studies from 2 countries (United States and the Netherlands), all recently published (2019-2023), that primarily reported barriers to GLT deprescribing from interviews or focus groups of patients or HCPs practicing outpatient medicine. Knowledge, fear, poor communication, inertia, and trust with HCPs were the main determinants of behaviors that influenced deprescribing, and education, training, persuasion and environmental restructuring were the main intervention functions for proposing future interventions. Studies did not cover financial aspects, physician characteristics, or caregiver and family viewpoints.
CONCLUSIONS: The use of a behavioral theory and a validated implementation framework provided a comprehensive approach to identifying barriers and enablers for deprescribing GLT in older adults (≥65 years) with T2DM. The behavioral determinants identified may be useful in tailoring interventions to improve the implementation of GLT deprescribing in older adults in ambulatory settings.

BACKGROUND: The revised Patients\' Attitudes Towards Deprescribing (rPATD) questionnaire was developed to capture beliefs and perceptions of patients about deprescribing. In general, handling of missing data is underreported in survey studies. Underlying mechanisms related to missing data may impact the findings from survey studies.
OBJECTIVE: The aim of this study was to assess the missing data in studies using the rPATD questionnaire through a systematic review and datasets from two studies.
METHODS: First, this review updated a systematic review on the rPATD (and other versions). We searched Medline via OVID, EMBASE, Scopus, Web of Science until 31st January 2023. Missing data reporting and methods to handle them were collected. Second, data from two deprescribing studies were analyzed using three methods of missing data handling: complete case analysis, personal mean substitution, and multiple imputation. We compared the scores from each domain and the associations of the domains with two questions from the rPATD to highlight how using different methods can influence the interpretation of study findings.
RESULTS: We identified 49 studies: 31 (63 %) from this study and 18 (37 %) from the original systematic review. The question or domain with the most missing data could be identified in 9 studies (18.4 %). Missing data management was reported in 19 studies (38.8 %). In one case analysis, the \"Burden\" domain was significantly associated with the question \"I would like to try stopping one of my medicines to see how I feel without it\" using complete case analysis (p = 0.044) or multiple imputation (p = 0.038), but not when using personal mean substitution (p = 0.057).
CONCLUSIONS: Missing data and methods used to handle missing data were underreported in studies using the rPATD questionnaire. The methods should be chosen carefully as our analyses from two distinct studies suggest that they may impact the interpretation of the findings from the questionnaire.