825 DEVELOPMENT OF THE ANTICHOLINERGIC MEDICATION INDEX (ACMI). (8th March 2022) - Best, K; Alderson, S; Alldred, D; Bonnet, L; Buchan, I; Butters, O; Farrin, A; Foy, R; Johnson, O; McInerney, C; Mehdizadeh, D; Lawton, T; et al.
Abstract: Introduction: Medications with Anticholinergic (AC) properties, are prescribed to treat a range of conditions. Older people are increasingly likely to be prescribed multiple AC medications, but are also more likely to experience unwanted adverse effects, such as falls and delirium. The risks of adverse outcomes increase with the number and potency of AC medications prescribed. The aim of this study was to use a prognostic modelling approach to develop an AC Medication Index (ACMI) that identifies patients at high risk of AC medication side effects. Methods: The prognostic model was developed using data on patients aged 65–95 years, registered with a general practice contributing data to 'Connected Bradford' in 2019. A Time-dependent Cox model was fitted, with hospital admission for delirium or falls as the composite outcome and AC medications, age, sex and important clinical factors (e.g. dementia, arthritis, urinary incontinence) as predictors. Concordance and Negalkerke's R2 derived from five-fold cross-validation were used to assess model performance. Results: There were 151, 604 patients included in the study, of whom 47, 035 (31.0%) were prescribed ≥1 AC medication during 2019. Codeine, Prednisolone, Furosemide and Amitriptyline were most commonly prescribed with 7.4%, 4.0%, 3.8% and 3.1% of patients prescribed these medications at least once in 2019, respectively. During 2019, 6, 078 (4.0%) patients experienced a hospital admission with delirium or a fall, with the rate being increased in those prescribed ≥1 AC medication during 2019 (4.8% vs 3.7%; p < 0.001). The prognostic model yielded a discrimination statistic of 0.86 with an R2 of 0.1. Conclusion: The model used to develop the ACMI shows good discrimination. External validation will soon be performed using data from the SAIL databank and the ACMI will be further developed as a tool for use in primary care.