The outcomes of considering goals of care in medication reviews for older adults: a systematic review.

INTRODUCTION: This is a systematic review of prescribing, clinical, patient-reported, and health utilization outcomes of goal-directed medication reviews in older adults. METHODS: A systematic review was conducted using MEDLINE, EMBASE, SCOPUS and CINAHL databases to identify studies examining outcomes of goal-directed medication reviews in humans, with mean/median age ≥ 60 years and in English. RESULTS: Seventeen out of 743 articles identified were included. Whilst there were inconsistent findings regarding changes in the number of medications between groups or post-intervention in one group (n = 6 studies), studies found reductions in drug-related problems (n = 2) and potential to reduce anticholinergics and sedatives (n = 2). Two out of seven studies investigating clinical outcomes found improvements, such as reduced hospital readmissions and improved depression severity. One study found 75% of patients achieved ≥ 1 goals and another found 43% of goals were achieved at six months. Four out of five studies found significant improvements in patient-reported quality of life between groups (n = 2) or post-intervention in one group (n = 2). Both studies investigating cost-effectiveness reported the intervention was cost-effective. CONCLUSIONS: There is evidence of positive impact on medication rationalization, quality of life and cost-effectiveness, supporting goal-directed medication reviews. Larger, longitudinal studies, exploring patient-focused outcomes may provide further insights into the ongoing impact of goal-directed medication reviews.

Impact of a Comprehensive Intervention Bundle Including the Drug Burden Index on Deprescribing Anticholinergic and Sedative Drugs in Older Acute Inpatients: A Non-randomised Controlled Before-and-After Pilot Study.

INTRODUCTION: Implementation of the Drug Burden Index (DBI) as a risk assessment tool in clinical practice may facilitate deprescribing. OBJECTIVE: The purpose of this study is to evaluate how a comprehensive intervention bundle using the DBI impacts (i) the proportion of older inpatients with at least one DBI-contributing medication stopped or dose reduced on discharge, compared with admission; and (ii) the changes in deprescribing of different DBI-contributing medication classes during hospitalisation. METHODS: This before-and-after study was conducted in an Australian metropolitan tertiary referral hospital. Patients aged ≥ 75 years admitted to the acute aged care service for ≥ 48 h from December 2020 to October 2021 and prescribed DBI-contributing medication were included. During the control period, usual care was provided. During the intervention, access to the intervention bundle was added, including a clinician interface displaying DBI score in the electronic medical record. In a subsequent 'stewardship' period, a stewardship pharmacist used the bundle to provide clinicians with patient-specific recommendations on deprescribing of DBI-contributing medications. RESULTS: Overall, 457 hospitalisations were included. The proportion of patients with at least one DBI-contributing medication stopped/reduced on discharge increased from 29.9% (control period) to 37.5% [intervention; adjusted risk difference (aRD) 6.5%, 95% confidence intervals (CI) -3.2 to 17.5%] and 43.1% (stewardship; aRD 12.1%, 95% CI 1.0-24.0%). The proportion of opioid prescriptions stopped/reduced rose from 17.9% during control to 45.7% during stewardship (p = 0.04). CONCLUSION: Integrating a comprehensive intervention bundle and accompanying stewardship program is a promising strategy to facilitate deprescribing of sedative and anticholinergic medications in older inpatients.

A stewardship program to facilitate anticholinergic and sedative medication deprescribing using the drug burden index in electronic medical records.

AIMS: The drug burden index (DBI) measures a person's total exposure to anticholinergic and sedative medications, which are commonly associated with harm. Through incorporating the DBI in electronic medical records (eMR) and implementing a DBI stewardship program, we aimed to determine (i) uptake of the steward's recommendations to deprescribe anticholinergic and/or sedative drugs by the medical team and (ii) whether accepted recommendations were actioned in hospital or recommended for follow-up by the General Practitioner post-discharge. METHODS: A single-arm, non-randomised feasibility study was performed at an Australian tertiary referral metropolitan hospital. The stewardship pharmacist reviewed eMRs of patients aged ≥75 years with DBI scores > 0, during admission. The steward identified and discussed potential opportunities to deprescribe anticholinergic and/or sedative medications with the medical registrars. RESULTS: Amongst 256 patients reviewed, the steward made 170 recommendations for 117 patients. Registrars agreed with 141 recommendations (82.9%) for 95 patients (81.2%), and actioned 115 deprescribing recommendations for 80 patients, most commonly for antidepressants and opioids. The 115 actioned recommendations resulted in 125 changes, with 44 changes to the inpatient drug chart and 81 additional changes recommended post-discharge in the discharge summary. CONCLUSION: Opportunities exist for deprescribing anticholinergic and sedative medications in older inpatients and a DBI stewardship program may help implement these. It is important to capture different outcomes of deprescribing interventions, including in-hospital medication changes, recommendations in the Discharge Summary, sustainability of deprescribing and clinical outcomes.

Polypharmacy and precision medicine.

Precision medicine is an approach to maximise the effectiveness of disease treatment and prevention and minimise harm from medications by considering relevant demographic, clinical, genomic and environmental factors in making treatment decisions. Precision medicine is complex, even for decisions about single drugs for single diseases, as it requires expert consideration of multiple measurable factors that affect pharmacokinetics and pharmacodynamics, and many patient-specific variables. Given the increasing number of patients with multiple conditions and medications, there is a need to apply lessons learned from precision medicine in monotherapy and single disease management to optimise polypharmacy. However, precision medicine for optimisation of polypharmacy is particularly challenging because of the vast number of interacting factors that influence drug use and response. In this narrative review, we aim to provide and apply the latest research findings to achieve precision medicine in the context of polypharmacy. Specifically, this review aims to (1) summarise challenges in achieving precision medicine specific to polypharmacy; (2) synthesise the current approaches to precision medicine in polypharmacy; (3) provide a summary of the literature in the field of prediction of unknown drug-drug interactions (DDI) and (4) propose a novel approach to provide precision medicine for patients with polypharmacy. For our proposed model to be implemented in routine clinical practice, a comprehensive intervention bundle needs to be integrated into the electronic medical record using bioinformatic approaches on a wide range of data to predict the effects of polypharmacy regimens on an individual. In addition, clinicians need to be trained to interpret the results of data from sources including pharmacogenomic testing, DDI prediction and physiological-pharmacokinetic-pharmacodynamic modelling to inform their medication reviews. Future studies are needed to evaluate the efficacy of this model and to test generalisability so that it can be implemented at scale, aiming to improve outcomes in people with polypharmacy.

Correction: Lim et al. Patient-Reported Questionnaires to Identify Adverse Drug Reactions: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 11877.

There was an error in the original publication [...].

Patient-Reported Questionnaires to Identify Adverse Drug Reactions: A Systematic Review.

BACKGROUND: This systematic review aims to summarise available patient-reported questionnaires to detect adverse drug reactions (ADRs) that can be utilised by healthcare professionals in clinical practice and to summarise the psychometric properties (validity, reliability, and responsiveness) of the questionnaires. METHODS: A systematic literature search was conducted using Medline, Pubmed, Embase, and Emcare databases to screen for articles published between January 2000 and July 2020. Data items regarding validity, reliability, and responsiveness were extracted independently by two authors. The methodological quality was assessed using the COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) checklist. RESULTS: A total of 1563 unique article titles were identified after removing duplicates. Following shortlisting of relevant articles, 19 patient-reported ADR questionnaires were identified. Questionnaires most commonly focused on mental health medications (42.1%, n = 8), followed by general questionnaires applicable to any medication (21.1%, n = 4). Many questionnaires did not report assessing the validity and reliability of the measurement tool. For example, only 11 questionnaires (58%) mentioned assessing content validity, in addition to criterion or construct testing. CONCLUSION: This systematic review summarised the available patient-reported questionnaires that can be used in research and clinical practice to identify ADRs. Results of this systematic review highlight the need for more robust validity and reliability testing when developing patient-reported ADR questionnaires.

Deprescribing in the Older Patient: A Narrative Review of Challenges and Solutions.

Polypharmacy is a major challenge in healthcare for older people, and is associated with increased risks of adverse outcomes, such as delirium, falls, frailty, cognitive impairment and hospitalization. There is significant public and professional interest in the role of deprescribing in reducing medication-related harms in older people. We aim to provide a narrative review of 1) the safety and efficacy of deprescribing interventions, 2) the challenges and solutions of deprescribing research and implementation in clinical practice, and 3) the benefits of using Computerized Clinical Decision Support Systems (CCDSS) and Quality Indicators (QIs) in deprescribing research and practice. Deprescribing is an established management strategy to minimize polypharmacy and potentially inappropriate medications. There is limited clinical evidence for its efficacy on global and geriatric outcomes. Various challenges at patient, healthcare professional and healthcare system levels may impact on the success of deprescribing interventions in research and practice. Management strategies that target all levels of the healthcare system are required to overcome these challenges. Future studies may consider large multicenter prospective designs to establish the effects and sustainability of deprescribing interventions on clinical outcomes.

Predictors of Mortality in the Older Population: The Role of Polypharmacy and Other Medication and Chronic Disease-Related Factors.

BACKGROUND: Polypharmacy has been associated with increased mortality but the contribution of different medication-related factors to this is unknown. AIMS: The aim of this study was to identify demographic and medication-related predictors of mortality in the older population. Given the intrinsic link between polypharmacy and multimorbidity, the secondary aim was to examine if the medicines or underlying diseases predicted mortality. METHODS: Patients aged ≥ 65 years from an outpatient multimorbidity clinic were included. Medication-related factors included the medicines count, high-risk medicines, inappropriate medicines duplication, and potential drug-drug and drug-disease interactions. Logistic regression was used to identify mortality predictors within a year of clinic discharge from the outpatient clinic. Patients attend the clinic until medications and comorbidity management have been optimised, at which point they are discharged from the clinic, and their General Practitioner provides ongoing care. RESULTS: A total of 584 patients were included (median age 80.0 years) and 9.9% (n = 58) died within a year of discharge. Demographics, namely age (adjusted odds ratio [aOR] 1.05; 95% CI 1.01-1.09; p = 0.018) and being male (aOR 5.10; 95% CI 2.63-9.88; p < 0.001); chronic disease, namely heart failure (aOR 3.36; 95% CI 1.78-6.35; p < 0.001); and medication-related factors, namely the number of sedative and anticholinergic medicines (aOR 1.66; 95% CI 1.19-2.33; p = 0.003) predicted mortality in the study population. CONCLUSION: Whilst polypharmacy has been defined using the number of medicines in the literature, a combination of demographics, chronic disease and medications predicted mortality in our study. This provides guidance for the development of future tools and guidelines regarding the inclusion of key factors for identifying high-risk patients at risk of adverse health outcomes such as mortality.

Predictors of unplanned hospitalisation in the older population: The role of polypharmacy and other medication and chronic disease-related factors.

OBJECTIVE: To identify demographic and medication-related predictors of unplanned hospitalisation and combine them into a hospitalisation risk score. METHODS: Patients aged ≥65 years from an outpatient multimorbidity clinic were included. Hospitalisation predictors within a year of clinic discharge were identified using logistic regression. A risk score was developed. The area under the curve (AUC) was used to assess its predictive ability, compared to that of the medicines count (definition of polypharmacy). RESULTS: A total of 598 patients were included (median age of 80.0 years). 58.0% (n = 347) were hospitalised within a year of clinic discharge. The AUC for the risk score incorporating age, medicines count, heart failure (HF), atherosclerotic disease and systemic steroids was 0.67 [95% CI 0.62-0.71], compared to 0.62 [95% CI 0.58-0.67] for the medicines count. CONCLUSION: A hospitalisation risk score incorporating demographics, medicines, namely steroids, and diseases such as HF had increased predictive ability compared to the medicines count, providing guidance for developing future polypharmacy tools.

Tools for Assessment of the Appropriateness of Prescribing and Association with Patient-Related Outcomes: A Systematic Review.

BACKGROUND: There are tools and criteria in the literature aimed at distinguishing between appropriate and inappropriate medicines use. However, many have not been externally validated with regard to patient-related outcomes, potentially limiting their use in clinical practice. OBJECTIVES: The aim of the study was to conduct a systematic review to summarise (1) available prescribing appropriateness assessment tools and criteria, and (2) their associations with patient-related outcomes (external validity). METHODS: A systematic review was conducted using MEDLINE, EMBASE and Informit (Health Collection) databases to screen for articles in English that examined (1) tools to assess the appropriateness of prescribing and (2) associations of tools with patient-related outcomes, published between 2000 and 2016, without any limits placed on the study design, participant age or setting. RESULTS: After screening 1710 articles, removing duplicates and shortlisting relevant articles, 42 prescribing assessment tools were identified. Out of the 42 tools, 78.6% (n = 33) provided guidance around stopping inappropriate medications, 28.6% (n = 12) around starting appropriate medications, 61.9% (n = 26) were explicit (criteria based) and 31.0% (n = 13) had been externally validated, with hospitalisation being the most commonly used patient-related outcome (n = 9, 21.4%). CONCLUSION: The results of this systematic review highlight the need for evidence-based and externally validated tools, which combine the different aspects of medication management to optimise patient-related outcomes. PROSPERO registration number: CRD42017067233.

What is polypharmacy? A systematic review of definitions.

BACKGROUND: Multimorbidity and the associated use of multiple medicines (polypharmacy), is common in the older population. Despite this, there is no consensus definition for polypharmacy. A systematic review was conducted to identify and summarise polypharmacy definitions in existing literature. METHODS: The reporting of this systematic review conforms to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) checklist. MEDLINE (Ovid), EMBASE and Cochrane were systematically searched, as well as grey literature, to identify articles which defined the term polypharmacy (without any limits on the types of definitions) and were in English, published between 1st January 2000 and 30th May 2016. Definitions were categorised as i. numerical only (using the number of medications to define polypharmacy), ii. numerical with an associated duration of therapy or healthcare setting (such as during hospital stay) or iii. Descriptive (using a brief description to define polypharmacy). RESULTS: A total of 1156 articles were identified and 110 articles met the inclusion criteria. Articles not only defined polypharmacy but associated terms such as minor and major polypharmacy. As a result, a total of 138 definitions of polypharmacy and associated terms were obtained. There were 111 numerical only definitions (80.4% of all definitions), 15 numerical definitions which incorporated a duration of therapy or healthcare setting (10.9%) and 12 descriptive definitions (8.7%). The most commonly reported definition of polypharmacy was the numerical definition of five or more medications daily (n = 51, 46.4% of articles), with definitions ranging from two or more to 11 or more medicines. Only 6.4% of articles classified the distinction between appropriate and inappropriate polypharmacy, using descriptive definitions to make this distinction. CONCLUSIONS: Polypharmacy definitions were variable. Numerical definitions of polypharmacy did not account for specific comorbidities present and make it difficult to assess safety and appropriateness of therapy in the clinical setting.