Abstract
PURPOSE: Older people are at an increased risk of developing adverse drug reactions (ADR) and adverse drug events (ADE). This study aimed to develop and validate a risk prediction model (ADAPTiP) for ADR/ADE in older populations. METHODS: We used the adverse drug reactions in an Ageing PopulaTion (ADAPT) cohort (N = 798; 361 ADR-related admissions; 437 non-ADR-related admissions), a cross-sectional study designed to examine the prevalence and risk factors for ADR-related hospital admissions in patients aged ≥ 65 years. Twenty predictors (categorised as sociodemographic-related, functional ability-related, disease-related, and medication-related) were considered in the development of the model. The model was developed using multivariable logistic regression and was internally validated by fivefold cross-validation. The model was externally validated in a separate prospective cohort from the Centre for Primary Care Research (CPCR) study of ADES. The cross-validated and externally validated model performance was evaluated by discrimination and calibration. RESULTS: The final prediction model, ADAPTiP, included nine predictors: age, chronic lung disease, the primary presenting complaints of respiratory, bleeding and gastrointestinal disorders and syncope on hospital admission and antithrombotics, diuretics, and renin-angiotensin-aldosterone system drug classes. ADAPTiP demonstrated good performance with cross-validated area under the curve of 0.75 [95% CI 0.72;79] and 0.83 [95% CI 0.80;0.87] in the external validation. CONCLUSION: Using accessible information from medical records, ADAPTiP can help clinicians to identify those older people at risk of an ADR/ADE who should be monitored and/or have their medications reviewed to avoid potentially harmful prescribing.