Adverse drug reactions (ADRs) represent a major burden on society, resulting in significant morbidity, mortality, and health care costs. Older patients living in the community are particularly susceptible to ADRs, and are at an increased risk of ADR-related hospitalization. This review summarizes the available evidence on ADR-related hospital admission in older patients living in the community, with a particular focus on risk factors for ADRs leading to hospital admission and the need for a prediction tool for risk of ADR-related hospitalization in these individuals. The reported proportion of hospital admissions due to ADRs has ranged from 6% to 12% of all admissions in older patients. The main risk factors or predictors for ADR-related admissions were advanced age, polypharmacy, comorbidity, and potentially inappropriate medications. There is a clear need to design intervention strategies to prevent ADR-related hospitalization in older patients. To ensure the cost-effectiveness of such strategies, it would be necessary to target them to those older individuals who are at highest risk of ADR-related hospitalization. Currently, there are no validated tools to assess the risk of ADRs in primary care. There is a clear need to investigate the utility of tools to identify high-risk patients to target appropriate interventions toward prevention of ADR-related hospital admissions.

Adverse drug reactions (ADRs) are the major cause of medication-related hospital admissions in older patients living in the community. This study aimed to develop and validate a score to predict ADR-related hospitalization in people aged ≥65 years. ADR-related hospitalization and its risk factors were determined using a prospective, cross-sectional study in patients aged ≥65 years admitted to two hospitals. A predictive model was developed in the derivation cohort (n = 768) and the model was applied in the validation cohort (n = 240). ADR-related hospital admission was determined through expert consensus from comprehensive reviews of medical records and patient interviews. The causality and preventability of the ADR were assessed based on the Naranjo algorithm and modified Schumock and Thornton criteria, respectively. In the derivation sample (mean [±SD] age, 80.1±7.7 years), 115 (15%) patients were admitted due to a definite or probable ADR; 92.2% of these admissions were deemed preventable. The number of antihypertensives was the strongest predictor of an ADR followed by presence of dementia, renal failure, drug changes in the preceding 3 months and use of anticholinergic medications; these variables were used to derive the ADR prediction score. The predictive ability of the score, assessed from calculation of the area under the receiver operator characteristic (ROC) curve, was 0.70 (95% confidence interval (CI) 0.65–0.75). In the validation sample (mean [±SD] age, 79.6±7.6 years), 30 (12.5%) patients’ admissions were related to definite or probable ADRs; 80% of these admissions were deemed preventable. The area under the ROC curve in this sample was 0.67 (95% CI 0.56–0.78). This study proposes a practical and simple tool to identify elderly patients who are at an increased risk of preventable ADR-related hospital admission. Further refinement and testing of this tool is necessary to implement the score in clinical practice.

The aim of this study was to investigate the proportion of patients who have suboptimal adherence to oral anticoagulant (OAC), identify the predictors of adherence, and determine whether patient-related factors vary across adherence levels in Australia. Respondents were recruited for an online survey using Facebook. Survey instruments included the Morisky Medication Adherence Scale, the Anticoagulation Knowledge Tool, the Perception of Anticoagulant Treatment Questionnaires, and a modified Cancer Information Overload scale. Predictors of medication adherence were identified using ordinal regression analysis. Of the 386 responses eligible for analysis, only 54.9% reported a high level of adherence. Participants aged 65 years or younger were less likely to have high adherence compared to older participants (odds ratio [OR], 0.54; 95% confidence interval [CI], 0.33-0.88; P = .013), while females were more likely to be highly adherent compared to males (OR, 1.69; 95% CI, 1.08-2.64; P = .023). The analyses showed that age, gender, treatment satisfaction, information overload, concerns about making mistake when taking OACs, and cost of medication were significant predictors of adherence. Self-reported suboptimal adherence to OAC is common among patients with atrial fibrillation. A focus on supporting people who are at higher risk of suboptimal adherence is needed to maximize the benefit of OAC therapy in this population.

Objectives: To use community pharmacy medication records to identify patients whose asthma may not be well managed and then implement and evaluate a multidisciplinary educational intervention to impr...