Deriving the anticholinergic medication index for delirium and falls in older people: development and external validation of a risk prediction model
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective To develop the anticholinergic medication index (ACMI), a new anticholinergic burden measure derived from a clinical prediction model for falls and delirium, scoring 88 anticholinergic medicines prescribed in primary care.Design Development and external validation of a risk prediction model.Setting UK primary and secondary care data from Connected Bradford and the Secure Anonymised Information Linkage (SAIL) databank, 1 January 2019 to 31 December 2019.Participants For development cohort, 71 757 Bradford and Craven residents aged >65 years on 1 January 2019 who contributed data to Connected Bradford between 1 January 2019 and 31 December 2019. For external validation cohort, 678 134 Welsh residents aged >65 years on 1 January 2019 who contributed data to SAIL between 1 January 2019 and 31 December 2019.Main outcome measures Composite outcome of hospital admission for delirium or hospital admission for a fall or fracture (as an indicator of an injurious fall) during the study period.Results 71 757 patients (4147 (5.8%) with the composite outcome) comprised the development cohort and 678 134 patients (43 675 (6.4%) with the composite outcome) comprised the external validation cohort. Based on anticholinergic medications recorded in electronic health records as predictors, a prediction model for falls and delirium was developed and validated. Model coefficients for anticholinergic medications were transformed into ACMI scores. Of 88 anticholinergic medications, codeine, prednisolone, and furosemide were the most commonly prescribed (8.3%, 6.5%, and 6.0% of patients prescribed these anticholinergic drugs at least once in the development cohort, respectively). Model discrimination and calibration in the development cohort was good (C index=0.794, R 2=0.06, calibration slope=0.97). The model performed well in external validation with good discrimination (C index=0.721, 95% confidence interval (CI) 0.718 to 0.734, R2=0.04) but with some evidence of miscalibration (calibration slope=0.69). The ACMI medications were scored 0.1 (desloratadine) to 2.3 (amantadine).Conclusions The ACMI was designed to be implemented in primary care to automatically calculate anticholinergic burden. Combined with the model predicted risk of delirium or falls, the ACMI allows clinicians to prioritise patients for structured medication reviews to reduce overprescribing.
Source: BMJ Medicine
Authors: Kate E Best, Olly Butters, Pieta Georgina Schofield, Oliver Todd, Sarah Alderson, David P Alldred, Laura Bonnett, Iain Buchan, Amanda Farrin, Owen Johnson, Ciarán McInerney, David Mehdizadeh, Tom Lawton, Rebecca Lawton, Farag Shuweidhi, Lauren E Walker, Robert West, Bridget Young, Munir Pirmohamed, Bethan Copsey, Aseel S Abuzour, Sarah E Rodgers, Andrew Clegg
Language: English
Subfield: Geriatrics and Gerontology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,679
Funders: Wellcome Trust, National Institute for Health and Care Research, British Heart Foundation, Department of Health and Social Care, Public Health Agency, Chief Scientist Office, Scottish Government Health and Social Care Directorate, Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Health and Social Care Research and Development Division, Leeds Biomedical Research Centre, Health Data Research UK
OpenAlex ID: W7225243220
