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Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data
OBJECTIVE: The nature of physical comorbidities in patients with mental illness may differ according to diagnosis and personal characteristics. We investigated this complexity by conventional logistic regression and network analysis. METHODS: A health insurance claims data in Korea was analyzed. For...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Neuropsychiatric Association
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9233950/ https://www.ncbi.nlm.nih.gov/pubmed/35753688 http://dx.doi.org/10.30773/pi.2022.0068 |
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author | Kim, Ho Joon Shin, Sam Yi Jeong, Seong Hoon |
author_facet | Kim, Ho Joon Shin, Sam Yi Jeong, Seong Hoon |
author_sort | Kim, Ho Joon |
collection | PubMed |
description | OBJECTIVE: The nature of physical comorbidities in patients with mental illness may differ according to diagnosis and personal characteristics. We investigated this complexity by conventional logistic regression and network analysis. METHODS: A health insurance claims data in Korea was analyzed. For every combination of psychiatric and physical diagnoses, odds ratios were calculated adjusting age and sex. From the patient-diagnosis data, a network of diagnoses was constructed using Jaccard coefficient as the index of comorbidity. RESULTS: In 1,017,024 individuals, 77,447 (7.6%) were diagnosed with mental illnesses. The number of physical diagnoses among them was 11.2, which was 1.6 times higher than non-psychiatric groups. The most noticeable associations were 1) neurotic illnesses with gastrointestinal/pain disorders and 2) dementia with fracture, Parkinson’s disease, and cerebrovascular accidents. Unexpectedly, the diagnosis of metabolic syndrome was only scarcely found in patients with severe mental illnesses (SMIs). However, implicit associations between metabolic syndrome and SMIs were suggested in comorbidity networks. CONCLUSION: Physical comorbidities in patients with mental illnesses were more extensive than those with other disease categories. However, the result raised questions as to whether the medical resources were being diverted to less serious conditions than more urgent conditions in patients with SMIs. |
format | Online Article Text |
id | pubmed-9233950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Korean Neuropsychiatric Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-92339502022-07-08 Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data Kim, Ho Joon Shin, Sam Yi Jeong, Seong Hoon Psychiatry Investig Original Article OBJECTIVE: The nature of physical comorbidities in patients with mental illness may differ according to diagnosis and personal characteristics. We investigated this complexity by conventional logistic regression and network analysis. METHODS: A health insurance claims data in Korea was analyzed. For every combination of psychiatric and physical diagnoses, odds ratios were calculated adjusting age and sex. From the patient-diagnosis data, a network of diagnoses was constructed using Jaccard coefficient as the index of comorbidity. RESULTS: In 1,017,024 individuals, 77,447 (7.6%) were diagnosed with mental illnesses. The number of physical diagnoses among them was 11.2, which was 1.6 times higher than non-psychiatric groups. The most noticeable associations were 1) neurotic illnesses with gastrointestinal/pain disorders and 2) dementia with fracture, Parkinson’s disease, and cerebrovascular accidents. Unexpectedly, the diagnosis of metabolic syndrome was only scarcely found in patients with severe mental illnesses (SMIs). However, implicit associations between metabolic syndrome and SMIs were suggested in comorbidity networks. CONCLUSION: Physical comorbidities in patients with mental illnesses were more extensive than those with other disease categories. However, the result raised questions as to whether the medical resources were being diverted to less serious conditions than more urgent conditions in patients with SMIs. Korean Neuropsychiatric Association 2022-06 2022-06-15 /pmc/articles/PMC9233950/ /pubmed/35753688 http://dx.doi.org/10.30773/pi.2022.0068 Text en Copyright © 2022 Korean Neuropsychiatric Association https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Kim, Ho Joon Shin, Sam Yi Jeong, Seong Hoon Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data |
title | Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data |
title_full | Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data |
title_fullStr | Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data |
title_full_unstemmed | Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data |
title_short | Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data |
title_sort | nature and extent of physical comorbidities among korean patients with mental illnesses: pairwise and network analysis based on health insurance claims data |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9233950/ https://www.ncbi.nlm.nih.gov/pubmed/35753688 http://dx.doi.org/10.30773/pi.2022.0068 |
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