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Clustering for Detection of Population Groups at Risk from Anticholinergic Medication

Authors: Amirali Shirazibeheshti, Tarik Radwan, Alireza Ettefaghian, Farbod Khanizadeh, George Wilson, Cristina Luca


Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. This work evaluates the association between the average risk score and measures of socioeconomic status (index of multiple deprivation) and health (index of health and disability). The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, suggesting that females are more at risk from this kind of multiple medication. The risk may be monitored and controlled in a healthcare management system that is well-equipped with tools implementing appropriate techniques of artificial intelligence.

Keywords: Anticholinergic medication, socioeconomic status, deprivation, clustering, risk analysis.

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[1] Nagham Ailabouni, Dee Mangin, and Prasad S Nishtala. Defeat-polypharmacy: deprescribing anticholinergic and sedative medicines feasibility trial in residential aged care facilities. Int. J. Clin. Pharm., 41(1):167–178, 2019.
[2] Nicholas C Arpey, Anne H Gaglioti, and Marcy E Rosenbaum. How socioeconomic status affects patient perceptions of health care: a qualitative study. Journal of primary care & community health, 8(3):169–175, 2017.
[3] John Billings, Lisa Zeitel, Joanne Lukomnik, Timothy S Carey, Arthur E Blank, and Laurie Newman. Impact of socioeconomic status on hospital use in new york city. Health affairs, 12(1):162–173, 1993.
[4] Malaz Boustani, Noll Campbell, Stephanie Munger, Ian Maidment, and Chris Fox. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health, 2008.
[5] Aging Brain Care. Anticholinergic cognitive burden scale. products. ACB scale - legal size.pdf, 2012.
[6] Laurie Ferret, Gregoire Ficheur, Emeline Delaviez, Michel Luyckx, Sophie Quenton, Regis Beuscart, Emmanuel Chazard, and Jean-Baptiste Beuscart. Inappropriate anticholinergic drugs prescriptions in older patients: analysing a hospital database. Int. J. Clin. Pharm., 40(1):94–100, 2018.
[7] Chris Fox, Kathryn Richardson, Ian D Maidment, George M Savva, Fiona E Matthews, David Smithard, Simon Coulton, Cornelius Katona, Malaz A Boustani, and Carol Brayne. Anticholinergic medication use and cognitive impairment in the older population: the medical research council cognitive function and ageing study. Journal of the American Geriatrics Society, 59(8):1477–1483, 2011.
[8] Kwanghee Jun, Young-Mi Ah, Sunghee Hwang, Jee Eun Chung, and Ju-Yeun Lee. Prevalence of anticholinergic burden and risk factors amongst the older population: analysis of insurance claims data of korean patients. International journal of clinical pharmacy, 42(2):453–461, 2020.
[9] Eun Kyung Lee and Yu Jeung Lee. Prescription patterns of anticholinergic agents and their associated factors in korean elderly patients with dementia. Int. J. Clin. Pharm., 35(5):711–718, 2013.
[10] Keita Matsuo, Masafumi Yamada, Kevin Bylykbashi, Miralda Cuka, Yi Liu, and Leonard Barolli. Implementation of an iot-based e-learning testbed: Performance evaluation using mean-shift clustering approach considering four types of brainwaves. In 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), pages 203–209. IEEE, 2018.
[11] AJ McMichael, E Zafeiridi, Michelle Ryan, EL Cunningham, AP Passmore, and Bernadette McGuinness. Anticholinergic drug use and risk of mortality for people with dementia in northern ireland. Aging & mental health, 25(8):1475–1482, 2021.
[12] Jure Mur, Simon R Cox, Riccardo E Marioni, Graciela Muniz-Terrera, and Tom C Russ. Increase in anticholinergic burden in the uk from 1990 to 2015: a uk biobank study. medRxiv, 2020.
[13] Stefan Noble, David McLennan, Michael Noble, Emma Plunkett, Nils Gutacker, Mary Silk, and Gemma Wright. The english indices of deprivation 2019. Office of the Deputy Prime Minister, Neighbourhood Renewal Unit, London, 2019.
[14] Mohammed Saji Salahudeen, Prasad S Nishtala, and Stephen B Duffull. The influence of patient characteristics on anticholinergic events in older people. Dementia and geriatric cognitive disorders extra, 5(3):530–541, 2015.
[15] Konstantinos Tsamakis, Romayne Gadelrab, Mimi Wilson, Anne M Bonnici-Mallia, Labib Hussain, Gayan Perera, Emmanouil Rizos, Jayati Das-Munshi, Robert Stewart, and Christoph Mueller. Dementia in people from ethnic minority backgrounds: Disability, functioning, and pharmacotherapy at the time of diagnosis. Journal of the American Medical Directors Association, 22(2):446–452, 2021.
[16] LM Ward, B Stanley, N Greenlaw, S-A Cooper, C Pacitti, A Henderson, J Gibson, and D Kinnear. Risk of anticholinergic burden in adults with intellectual disabilities: a scottish retrospective cohort study of n= 17 220. Journal of Intellectual Disability Research, 65(9):813–830, 2021.