Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network

Yuji Sase, Daiki Kumagai, Teppei Suzuki, Hiroko Yamashina, Yuji Tani, Kensuke Fujiwara, Takumi Tanikawa, Hisashi Enomoto, Takeshi Aoyama, Wataru Nagai and Katsuhiko Ogasawara
Additional contact information
Yuji Sase: Faculty of Medical Informatics, Hokkaido Information University, Hokkaido 069-8585, Japan
Daiki Kumagai: School of Health Sciences, Hokkaido University, Hokkaido 060-0812, Japan
Teppei Suzuki: Art & Sports Business, Iwamizawa, Hokkaido University of Education, Hokkaido 068-8642, Japan
Hiroko Yamashina: Faculty of Health Sciences, Hokkaido University, Hokkaido 060-0812, Japan
Yuji Tani: Department of Medical Informatics and Hospital Management, Asahikawa Medical University, Hokkaido 078-8510, Japan
Kensuke Fujiwara: Graduate School of Commerce, Otaru University of Commerce, Hokkaido 047-8501, Japan
Takumi Tanikawa: Faculty of Health Sciences, Hokkaido University of Science, Hokkaido 006-8585, Japan
Hisashi Enomoto: Iwamizawa City, Hokkaido 068-0828, Japan
Takeshi Aoyama: Iwamizawa City, Hokkaido 068-0828, Japan
Wataru Nagai: Iwamizawa City, Hokkaido 068-0828, Japan
Katsuhiko Ogasawara: Faculty of Health Sciences, Hokkaido University, Hokkaido 060-0812, Japan

IJERPH, 2020, vol. 17, issue 15, 1-10

Abstract: Objective : This study aims to determine the characteristics of Type 2 diabetic patients who are more likely to cause high-cost medical expenses using the Bayesian network model. Methods : The 2011–2015 receipt data of Iwamizawa city, Japan were collected from the National Health Insurance Database. From the record, we identified patients with Type 2 diabetes with the following items: age, gender, area, number of days provided medical services, number of diseases, number of medical examinations, annual healthcare expenditures, and the presence or absence of hospitalization. The Bayesian network model was applied to identify the characteristics of the patients, and four observed values were changed using a model for patients who paid at least 3607 USD a year for medical expenses. The changes in the conditional probability of the annual healthcare expenditures and changes in the percentage of patients with high-cost medical expenses were analyzed. Results : After changing the observed value, the percentage of patients with high-cost medical expense reimbursement increased when the following four conditions were applied: the patient “has ever been hospitalized”, “had been provided medical services at least 18 days a year”, “had at least 14 diseases listed on medical insurance receipts”, and “has not had specific health checkups in five years”. Conclusions : To prevent an excessive rise in healthcare expenditures in Type 2 diabetic patients, measures against complications and promoting encouragement for them to undergo specific health checkups are considered as effective.

Keywords: health economics; bayesian network; diabetes; National Health Insurance; medical costs; specific health checkups (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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