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Geriatrics

Session: Poster Session B

(086) Adverse Drug reactions in an Ageing PopulaTion rIsk Prediction Tool (ADAPtIP): the development of a model for predicting adverse drug reactions in older patients admitted to hospital

Tuesday, August 27, 2024
8:00 AM – 6:00 PM CEST
Location: Convention Hall II

    Presenting Author(s)

  • Juliane Frydenlund, PhD, MSc

    Post Doctoral Research Fellow
    Data Science Centre, School of Population Health, RCSI University of Medicine and Health Science, Ireland

    • Co-Author(s)

  • Nicole Cosgrave, MB Bch BAO BPharm MPharm MRCPI

    Doctor
    Department of Medicine, RCSI University of Medicine and Health Science, Ireland

  • Frank Moriarty, MPharm PhD MPSI (he/him/his)

    Senior Lecturer
    School of Pharmacy and Biomolecular Sciences, RCSI University of Medicine and Health Sciences
    Dublin, Ireland

  • CK

    Ciara Kirke

    National Quality and Patient Safety Directorate at Health Service Executive, Dublin, Ireland, Ireland

  • DW

    David J. Williams

    Professor of Medicine
    Department of Medicine, RCSI University of Medicine and Health Science, Ireland

  • KB

    Kathleen E. Bennett, PhD

    Professor of Biostatistics
    Data Science Centre, School of Population Health, RCSI University of Medicine and Health Sciences, Dublin, Ireland.
    Dublin, Ireland

  • CC

    Caitriona Cahir, PhD

    Data Science Centre, School of Population Health, RCSI University of Medicine and Health Science, Ireland

  • EW

    Emma Wallace

    Department of General Practice, School of Medicine, University College Cork, Ireland, Ireland

Background: Older patients are at an increased risk of developing adverse drug reactions (ADRs). Medication-related harm has been identified internationally as a key area for improvement. ADRs have both direct and indirect health and economic costs and are associated with increased morbidity and mortality in older people.

Objectives: The aim of the study was to develop a risk prediction tool for ADR-related hospital admissions in older populations for use in clinical practice.

Methods: This study used the Adverse Drug Reactions in an Ageing Population (ADAPT) cohort (N=798; N = 361 ADR-related admissions; 437 non-ADR-related admissions), a cross-sectional and prospective cohort study designed to examine the prevalence and risk factors for ADR-related hospital admissions in patients aged ≥ 65yrs. Eighteen risk predictors (categorised as sociodemographic-related, functional ability-related, disease-related, and medication-related) were considered in the development of the model. Multivariable logistic regression models were developed using statistically significant and/or clinically relevant variables to estimate adjusted odds ratios and 95% confidence intervals (CI). Calibration and discriminative performance of the models were assessed by calculating the area under the receiver operator characteristic (AUROC) curve and calibration plots.

Results: The multivariable model included 9 risk predictors: age, medical card status, frailty, chronic lung disease, antithrombotics, diuretics, renin-angiotensin-aldosterone system (RAAS) drugs, NSAIDs and polypharmacy. The AUROC was 0.68 [95%CI: 0.64;0.71] .

Conclusions: We have developed a risk prediction model based on nine variables to help clinicians identify older patients with an increased likelihood of an ADR-related hospital admissions. The model provided an AUROC close to 0.70 which is considered acceptable discrimination capacity for clinical relevance.