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Researchers developed the Anticholinergic Medication Index (ACMI) to identify older patients whose combined medication effects may raise their risk of delirium or falls. Its clinical decision-support version is live in two NHS trusts, while further pilots are examining wider use. The source reports the tool can flag risk and support medication reviews; it does not report that ACMI has already reduced falls or delirium.
Researchers have developed a medication risk tool designed to help NHS clinicians identify people aged 65 and older who may be at increased risk of delirium or falls from taking several medicines with anticholinergic effects. Its clinical decision-support version is already in use at two NHS trusts, although the report does not show that the tool has reduced either outcome.
The Anticholinergic Medication Index (ACMI) scores the combined anticholinergic burden from a patient’s medicines, with the model developed around risks of delirium and falls. Anticholinergic effects can be a main purpose of a medicine or an unintended effect of drugs prescribed for other conditions. The concern is that these effects can accumulate when a patient takes multiple medicines with them.
In a pilot at general practices in Bradford, the tool automatically generated lists of patients aged 65 and over, alongside each person’s ACMI score, the medicines contributing to it and a predicted one-year risk of a fall or delirium. The information is intended to help pharmacists prioritize patients for a structured medication review, rather than calculate risk for each person manually.
A clinical decision-support version, called the Anticholinergic Medication Index Clinical Decision Support System (ACMICS), has been embedded in electronic patient records and is live in two NHS trusts, according to the research team. It recalculates scores when an anticholinergic medicine is started or stopped. The underlying model was developed and tested using health records from nearly 750,000 adults over 65, including data from West Yorkshire and a national dataset in Wales. The study was published in BMJ Medicine.
Flagging Risk During Prescribing
The tool addresses a practical gap between knowing that medication effects can pose risks and identifying which patients may need a closer review. Because ACMI is designed to appear within existing electronic patient records, it can present scores and contributing medicines as part of clinicians’ normal workflow, rather than requiring a separate calculation.
That could help primary care teams and hospital pharmacists direct limited review time toward patients with higher predicted risk. Researchers say falls and delirium can have serious effects on older people’s health and well-being and carry costs for the NHS. However, the source describes a risk-identification and prescribing-support tool; it does not provide evidence that its use has yet prevented falls, delirium or dementia.
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From Risk Model to NHS Records
Anticholinergic medicines are prescribed for a range of conditions, and not every medicine with anticholinergic effects is prescribed primarily for that reason. Researchers describe the combined effects of multiple such medicines as anticholinergic burden. The reported concerns include delirium and falls, as well as other possible side effects such as constipation, difficulty emptying the bladder and dry mouth.
The team derived the index using anonymized linked health records from Connected West Yorkshire and tested it with data from the SAIL Databank in Wales. The paper reports development and external validation of a risk prediction model. The researchers also produced a technical specification intended to help other organizations build an equivalent system into their own electronic records.
“Approximately 50% of older adults are prescribed at least one anticholinergic medication annually in the U.K.”
— Dr. Kate Best, associate professor of applied statistics at the University of Leeds and the study’s first author
Outcome Benefits Still Unproven
The available report does not give results showing whether use of ACMI has reduced the number of falls or delirium cases, changed prescribing, or improved patients’ health. It also does not specify how many patients have been assessed through the live systems, the cost of implementation, or how the tool performs across different patient groups. A predicted one-year risk is an estimate, not a certainty that an individual will experience an event.
Although the model was tested using large datasets, the details provided here do not include its accuracy measures or explain how clinicians should balance a high score against the benefits of medicines needed to treat other conditions. Medication changes remain decisions for a patient’s clinical team; the source does not recommend stopping a medicine without review.
Hospital Pilots Will Test Wider Use
The research team is piloting ACMI in several geriatric medicine and orthopedic hip fracture wards to assess whether it is feasible to use more widely in secondary care. The pilots may provide information about how the tool fits hospital workflows and whether more NHS organizations can adopt it using the technical specification.
The report does not give a timetable for those pilots or say when results will be published. Further evidence on implementation, prescribing changes and patient outcomes would be needed to judge whether the system reduces harm, beyond identifying patients for review.
Key Questions
What does the ACMI tool do?
The Anticholinergic Medication Index scores the combined anticholinergic effects of a patient’s medicines and is designed to help clinicians identify older people who may need a medication review.
Is the tool already being used in the NHS?
Yes. The clinical decision-support version, ACMICS, is reported to be live in two NHS trusts. The team is also piloting the tool in several hospital wards.
Has ACMI been shown to prevent falls or delirium?
The report does not provide evidence that ACMI has reduced falls or delirium. It describes a tool for predicting risk and supporting clinicians to prioritize medication reviews.
Does a high score mean a patient should stop a medicine?
No such instruction is reported. The score is intended to inform a structured review; decisions about starting, changing or stopping medicines should be made by the patient’s clinical team.
Source: medicalxpress.com
