Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network
<i>Objective</i>: 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. <i>Methods</i>: The 2011–2015 receipt data of Iwamizawa city, Japan were collected from the...
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doaj-a688fd6dfc39430f9d36641229a077402020-11-25T03:02:15ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012020-07-01175271527110.3390/ijerph17155271Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian NetworkYuji Sase0Daiki Kumagai1Teppei Suzuki2Hiroko Yamashina3Yuji Tani4Kensuke Fujiwara5Takumi Tanikawa6Hisashi Enomoto7Takeshi Aoyama8Wataru Nagai9Katsuhiko Ogasawara10Faculty of Medical Informatics, Hokkaido Information University, Hokkaido 069-8585, JapanSchool of Health Sciences, Hokkaido University, Hokkaido 060-0812, JapanArt & Sports Business, Iwamizawa, Hokkaido University of Education, Hokkaido 068-8642, JapanFaculty of Health Sciences, Hokkaido University, Hokkaido 060-0812, JapanDepartment of Medical Informatics and Hospital Management, Asahikawa Medical University, Hokkaido 078-8510, JapanGraduate School of Commerce, Otaru University of Commerce, Hokkaido 047-8501, JapanFaculty of Health Sciences, Hokkaido University of Science, Hokkaido 006-8585, JapanIwamizawa City, Hokkaido 068-0828, JapanIwamizawa City, Hokkaido 068-0828, JapanIwamizawa City, Hokkaido 068-0828, JapanFaculty of Health Sciences, Hokkaido University, Hokkaido 060-0812, Japan<i>Objective</i>: 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. <i>Methods</i>: 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. <i>Results</i>: 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”. <i>Conclusions</i>: 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.https://www.mdpi.com/1660-4601/17/15/5271health economicsbayesian networkdiabetesNational Health Insurancemedical costsspecific health checkups |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuji Sase Daiki Kumagai Teppei Suzuki Hiroko Yamashina Yuji Tani Kensuke Fujiwara Takumi Tanikawa Hisashi Enomoto Takeshi Aoyama Wataru Nagai Katsuhiko Ogasawara |
spellingShingle |
Yuji Sase Daiki Kumagai Teppei Suzuki Hiroko Yamashina Yuji Tani Kensuke Fujiwara Takumi Tanikawa Hisashi Enomoto Takeshi Aoyama Wataru Nagai Katsuhiko Ogasawara Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network International Journal of Environmental Research and Public Health health economics bayesian network diabetes National Health Insurance medical costs specific health checkups |
author_facet |
Yuji Sase Daiki Kumagai Teppei Suzuki Hiroko Yamashina Yuji Tani Kensuke Fujiwara Takumi Tanikawa Hisashi Enomoto Takeshi Aoyama Wataru Nagai Katsuhiko Ogasawara |
author_sort |
Yuji Sase |
title |
Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network |
title_short |
Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network |
title_full |
Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network |
title_fullStr |
Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network |
title_full_unstemmed |
Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network |
title_sort |
characteristics of type-2 diabetics who are prone to high-cost medical care expenses by bayesian network |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1661-7827 1660-4601 |
publishDate |
2020-07-01 |
description |
<i>Objective</i>: 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. <i>Methods</i>: 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. <i>Results</i>: 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”. <i>Conclusions</i>: 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. |
topic |
health economics bayesian network diabetes National Health Insurance medical costs specific health checkups |
url |
https://www.mdpi.com/1660-4601/17/15/5271 |
work_keys_str_mv |
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