Clustering for Detection of Population Groups at Risk from Anticholinergic Medication

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Population Groups at Risk from Anticholinergic Medication</title> <meta name="description" content="Clustering for Detection of Population Groups at Risk from Anticholinergic Medication"> <meta name="keywords" content="Anticholinergic medication, socioeconomic status, deprivation, clustering, risk analysis."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Clustering for Detection of Population Groups at Risk from Anticholinergic Medication"> <meta name="citation_author" content="Amirali Shirazibeheshti"> <meta name="citation_author" content="Tarik Radwan"> <meta name="citation_author" content="Alireza Ettefaghian"> <meta name="citation_author" content="Farbod Khanizadeh"> <meta name="citation_author" content="George Wilson"> <meta name="citation_author" content="Cristina Luca"> <meta name="citation_publication_date" content="2022/04/06"> <meta 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action="https://publications.waset.org/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value=""> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 33093</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Clustering for Detection of Population Groups at Risk from Anticholinergic Medication</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Amirali%20Shirazibeheshti">Amirali Shirazibeheshti</a>, <a href="https://publications.waset.org/search?q=Tarik%20Radwan"> Tarik Radwan</a>, <a href="https://publications.waset.org/search?q=Alireza%20Ettefaghian"> Alireza Ettefaghian</a>, <a href="https://publications.waset.org/search?q=Farbod%20Khanizadeh"> Farbod Khanizadeh</a>, <a href="https://publications.waset.org/search?q=George%20Wilson"> George Wilson</a>, <a href="https://publications.waset.org/search?q=Cristina%20Luca"> Cristina Luca</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>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.</p> <iframe src="https://publications.waset.org/10012501.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Anticholinergic%20medication" title="Anticholinergic medication">Anticholinergic medication</a>, <a href="https://publications.waset.org/search?q=socioeconomic%20status" title=" socioeconomic status"> socioeconomic status</a>, <a href="https://publications.waset.org/search?q=deprivation" title=" deprivation"> deprivation</a>, <a href="https://publications.waset.org/search?q=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/search?q=risk%20analysis." title=" risk analysis."> risk analysis.</a> </p> <a href="https://publications.waset.org/10012501/clustering-for-detection-of-population-groups-at-risk-from-anticholinergic-medication" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012501/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012501/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012501/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012501/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012501/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012501/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012501/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012501/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012501/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012501/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012501.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1070</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[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. <br>[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. <br>[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. <br>[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. <br>[5] Aging Brain Care. Anticholinergic cognitive burden scale. www.agingbraincare.org/uploads/ products. 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International journal of clinical pharmacy, 42(2):453–461, 2020. <br>[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. <br>[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. <br>[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. <br>[12] Jure Mur, Simon R Cox, Riccardo E Marioni, Graciela Muniz-Terrera, and Tom C Russ. 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Clustering for Detection of Population Groups at Risk from Anticholinergic Medication