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タイトル: | Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan |
著者: | Ohki, Yu Ikeda, Yuichi https://orcid.org/0000-0002-9929-3813 (unconfirmed) Kunisawa, Susumu Imanaka, Yuichi |
著者名の別形: | 大木, 有 池田, 裕一 國澤, 進 今中, 雄一 |
キーワード: | Hospitals Linear regression analysis Inpatients Outpatients Statistical models Health care providers Random walk Trees |
発行日: | Aug-2022 |
出版者: | Public Library of Science (PLoS) |
誌名: | PLOS ONE |
巻: | 17 |
号: | 8 |
論文番号: | e0266211 |
抄録: | The aging world population requires a sustainable and high-quality healthcare system. To examine the efficiency of medical cooperation, medical provider and physician networks were constructed using patient claims data. Previous studies have shown that these networks contain information on medical cooperation. However, the usage patterns of multiple medical providers in a series of medical services have not been considered. In addition, these studies used only general network features to represent medical cooperation, but their expressive ability was low. To overcome these limitations, we analyzed the medical provider network to examine its overall contribution to the quality of healthcare provided by cooperation between medical providers in a series of medical services. This study focused on: i) the method of feature extraction from the network, ii) incorporation of the usage pattern of medical providers, and iii) expressive ability of the statistical model. Femoral neck fractures were selected as the target disease. To build the medical provider networks, we analyzed the patient claims data from a single prefecture in Japan between January 1, 2014 and December 31, 2019. We considered four types of models. Models 1 and 2 use node strength and linear regression, with Model 2 also incorporating patient age as an input. Models 3 and 4 use feature representation by node2vec with linear regression and regression tree ensemble, a machine learning method. The results showed that medical providers with higher levels of cooperation reduce the duration of hospital stay. The overall contribution of the medical cooperation to the duration of hospital stay extracted from the medical provider network using node2vec is approximately 20%, which is approximately 20 times higher than the model using strength. |
著作権等: | © 2022 Ohki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
URI: | http://hdl.handle.net/2433/279285 |
DOI(出版社版): | 10.1371/journal.pone.0266211 |
PubMed ID: | 36001543 |
出現コレクション: | 学術雑誌掲載論文等 |
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