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Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis
BACKGROUND: The decreased life expectancy and care costs of mental disorders could be enormous. However, research that compares mortality and utilization concurrently across the major category of mental disorders is absent. This study investigated all-cause mortality and medical utilization among pa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081626/ https://www.ncbi.nlm.nih.gov/pubmed/32188440 http://dx.doi.org/10.1186/s12913-020-05089-6 |
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author | Wang, Jong-Yi Chang, Cheng-Chen Lee, Meng-Chen Li, Yi-Jhen |
author_facet | Wang, Jong-Yi Chang, Cheng-Chen Lee, Meng-Chen Li, Yi-Jhen |
author_sort | Wang, Jong-Yi |
collection | PubMed |
description | BACKGROUND: The decreased life expectancy and care costs of mental disorders could be enormous. However, research that compares mortality and utilization concurrently across the major category of mental disorders is absent. This study investigated all-cause mortality and medical utilization among patients with and without mental disorders, with an emphasis on identifying the psychiatric category of high mortality and low medical utilization. METHODS: A total of 570,250 individuals identified from the 2002–2013 Taiwan National Health Insurance Reearch Database consistuted 285,125 psychiatric patients and 285,125 non-psychiatric peers through 1:1 dual propensity score matching (PSM). The expenditure survival ratio (ESR) was proposed to indicate potential utilization shortage. The category of mental disorders and 13 covariates were analyzed using the Cox proportional hazard model and general linear model (GLM) through SAS 9.4. RESULTS: PSM analyses indicated that mortality and total medical expenditures per capita were both significantly higher in psychiatric patients than those in non-psychiatric patients (all P <.0.0001). Patients with substance use disorders were reported having the youngest ages at diagnosis and at death, with the highest 25.64 of potential years of life loss (YPLL) and relevant 2904.89 of ESR. Adjusted Cox model and GLM results indicated that, compared with anxiety disorders, affective disorders and substance use disorders were significantly associated with higher mortality (HR = 1.246 and 1.064, respectively; all P < 0.05); schizophrenia was significantly associated with higher total medical expenditures per capita (P < 0.0001). Thirteen additional factors were significantly associated with mortality or utilization (all P < 0.05). CONCLUSION: Substance use disorders are the category of highest YPLL but notably in insufficient utilization. Health care utilization in patients with substance use disorders should be augmented timely after the diagnosis, especially toward home and community care. The factors related to mortality and utilization identified by this study merit clinical attention. |
format | Online Article Text |
id | pubmed-7081626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70816262020-03-23 Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis Wang, Jong-Yi Chang, Cheng-Chen Lee, Meng-Chen Li, Yi-Jhen BMC Health Serv Res Research Article BACKGROUND: The decreased life expectancy and care costs of mental disorders could be enormous. However, research that compares mortality and utilization concurrently across the major category of mental disorders is absent. This study investigated all-cause mortality and medical utilization among patients with and without mental disorders, with an emphasis on identifying the psychiatric category of high mortality and low medical utilization. METHODS: A total of 570,250 individuals identified from the 2002–2013 Taiwan National Health Insurance Reearch Database consistuted 285,125 psychiatric patients and 285,125 non-psychiatric peers through 1:1 dual propensity score matching (PSM). The expenditure survival ratio (ESR) was proposed to indicate potential utilization shortage. The category of mental disorders and 13 covariates were analyzed using the Cox proportional hazard model and general linear model (GLM) through SAS 9.4. RESULTS: PSM analyses indicated that mortality and total medical expenditures per capita were both significantly higher in psychiatric patients than those in non-psychiatric patients (all P <.0.0001). Patients with substance use disorders were reported having the youngest ages at diagnosis and at death, with the highest 25.64 of potential years of life loss (YPLL) and relevant 2904.89 of ESR. Adjusted Cox model and GLM results indicated that, compared with anxiety disorders, affective disorders and substance use disorders were significantly associated with higher mortality (HR = 1.246 and 1.064, respectively; all P < 0.05); schizophrenia was significantly associated with higher total medical expenditures per capita (P < 0.0001). Thirteen additional factors were significantly associated with mortality or utilization (all P < 0.05). CONCLUSION: Substance use disorders are the category of highest YPLL but notably in insufficient utilization. Health care utilization in patients with substance use disorders should be augmented timely after the diagnosis, especially toward home and community care. The factors related to mortality and utilization identified by this study merit clinical attention. BioMed Central 2020-03-18 /pmc/articles/PMC7081626/ /pubmed/32188440 http://dx.doi.org/10.1186/s12913-020-05089-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Wang, Jong-Yi Chang, Cheng-Chen Lee, Meng-Chen Li, Yi-Jhen Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
title | Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
title_full | Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
title_fullStr | Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
title_full_unstemmed | Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
title_short | Identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
title_sort | identification of psychiatric patients with high mortality and low medical utilization: a population-based propensity score-matched analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081626/ https://www.ncbi.nlm.nih.gov/pubmed/32188440 http://dx.doi.org/10.1186/s12913-020-05089-6 |
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