Data mining the comorbid associations between dementia and various kinds of illnesses using a medicine database. (August 2018)

• Record Type: Journal Article
• Authors: Chen, Pei Hua; Yang, Fu-Yi; Lee, Ding-Dar; Yang, Meng-Han
• Is Part Of: Computers & electrical engineering. Volume 70(2018)
• Page Start: 12
• Page End: 20
• Publication Date: 2018-08
• Subjects: Comorbidity -- Data mining -- Dementia -- Medication -- National health insurance program; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.05.014
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: As people's average life expectancy has significantly improved, the prevalence of dementia among elderly people has increased. The symptoms of dementia might influence patients' interpersonal relationships and their ability to work. This study was based on the nationwide dataset applied from the National Health Insurance program of Taiwan, and two types of medication ingredients, which are constantly prescribed for dementia patients, were used for case selection. This study included 5041 case patients and 13, 902 control patients who were matched with age, gender, and index date. Using logistic regression, the current study has identified the comorbid associations between dementia and various kinds of illnesses. Advanced stratification analyses revealed that some comorbid illnesses associated with dementia only exists in subgroups of patients with specific age, gender, or prescription for dementia drugs. The mined characteristics would be helpful in managing patients with dementia.