Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박정민 | - |
dc.date.accessioned | 2022-11-09T02:21:09Z | - |
dc.date.available | 2022-11-09T02:21:09Z | - |
dc.date.issued | 2021-11 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, v. 18, NO. 21, article no. 11469, Page. 1-18 | en_US |
dc.identifier.issn | 1661-7827;1660-4601 | en_US |
dc.identifier.uri | https://www.mdpi.com/1660-4601/18/21/11469 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/176520 | - |
dc.description.abstract | Disease severities are the outcomes of an inpatient visit classification that assigns a diagnostic related group, including risk of mortality and severity of illness. Although widely used in healthcare, the analysis of factors affecting disease severities has not been adequately studied. In this study, we analyze the relationships between demographics and chronic conditions and specify their influence on disease severities. Descriptive statistics are used to investigate the relationships and the prevalence of chronic conditions. To evaluate the influence of demographic factors and chronic conditions on disease severities, several multinomial logistic regression models are performed and prediction models for disease severities are conducted based on National Inpatient Sample data for 2016 provided by the Healthcare Cost and Utilization Project database in the United States. The rate of patients with a chronic illness is 88.9% and the rate of patients with more than two chronic conditions is 67.6%; further, the rate is 62.7% for females, 73.9% for males, and 90% for the elderly. A high level of disease severity commonly appears in patients with more than two chronic conditions, especially in the elderly. For patients without chronic conditions, disease severities show a lower or safe level, even in the elderly.</p> | en_US |
dc.description.sponsorship | This work was partly supported by the Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korean government(MSIT) (No. 2020-0-01373),Artificial Intelligence Graduate School Program(Hanyang University) and the research fund of Hanyang University (HY-202100000320016). This research was supported by a grant of the Korea Health Technology R & D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HC20C0118). This research was funded by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1G1A1006626). | en_US |
dc.language | en | en_US |
dc.publisher | MDPI | en_US |
dc.subject | chronic disease | en_US |
dc.subject | demographic | en_US |
dc.subject | disease | en_US |
dc.subject | mortality | en_US |
dc.subject | severity of illness | en_US |
dc.subject | prevalence | en_US |
dc.title | Relationships between Demographic Factors and Chronic Conditions with Disease Severities | en_US |
dc.type | Article | en_US |
dc.relation.no | 21 | - |
dc.relation.volume | 18 | - |
dc.identifier.doi | 10.3390/ijerph182111469 | en_US |
dc.relation.page | 1-18 | - |
dc.relation.journal | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | - |
dc.contributor.googleauthor | Nguyen, Van Cuong | - |
dc.contributor.googleauthor | Park, Jungmin | - |
dc.sector.campus | S | - |
dc.sector.daehak | 간호대학 | - |
dc.sector.department | 간호학과 | - |
dc.identifier.pid | jminpark | - |
dc.identifier.orcid | https://orcid.org/0000-0002-5837-2494 | - |
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