Cargando…
On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses
PURPOSE: When examining the nexus of physician mental health disorders and healthcare quality from the empirical perspective, mental health disorders are frequently associated with cyclical patterns corresponding to cyclic seasonality, mood swings, emission of air pollution and business cycles, the...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638657/ https://www.ncbi.nlm.nih.gov/pubmed/37953809 http://dx.doi.org/10.2147/RMHP.S429516 |
_version_ | 1785133642851287040 |
---|---|
author | Chen, Wen-Yi Lin, Feng-Li |
author_facet | Chen, Wen-Yi Lin, Feng-Li |
author_sort | Chen, Wen-Yi |
collection | PubMed |
description | PURPOSE: When examining the nexus of physician mental health disorders and healthcare quality from the empirical perspective, mental health disorders are frequently associated with cyclical patterns corresponding to cyclic seasonality, mood swings, emission of air pollution and business cycles, the potential asymmetric effects of physician mental health disorders on healthcare quality have not received adequate attention from researchers. Therefore, the purpose of this study is to explore the asymmetric relationship between physician mental health disorders and healthcare quality during the pandemic outbreak in Taiwan. METHODS: Daily data for care quality indicators and physician mental health disorders were collected from the National Insurance Research Database in Taiwan, and the quantile-on-quantile regression model was applied to proceed with our analyses. RESULTS: Our results indicated that the overall aggregate effects of each quantile of physician mental health disorders on the cumulative quantiles of healthcare quality are negative (positive) for the 14-day readmission rate (preventable hospitalization rate and non-urgent ED-visit rate). Positively (negatively) cumulative effects of each quantile of physician mental health disorders were detected in the middle (low and high) quantiles of the preventable hospitalization rate. The cumulative effects of each quantile of physician mental health disorders on the high (low and middle) quantiles of the 14-day readmission rate are negative (positive), but the cumulative effects on various quantiles of the non-urgent ED-visit rate exhibit the opposite pattern. CONCLUSION: The observed variation in the relationship between physician mental health disorders and different quantiles of healthcare quality suggests the need for tailored strategic interventions based on distinct levels of healthcare quality when addressing the higher risk of physician mental health disorders during the pandemic outbreak conditions. |
format | Online Article Text |
id | pubmed-10638657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-106386572023-11-11 On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses Chen, Wen-Yi Lin, Feng-Li Risk Manag Healthc Policy Original Research PURPOSE: When examining the nexus of physician mental health disorders and healthcare quality from the empirical perspective, mental health disorders are frequently associated with cyclical patterns corresponding to cyclic seasonality, mood swings, emission of air pollution and business cycles, the potential asymmetric effects of physician mental health disorders on healthcare quality have not received adequate attention from researchers. Therefore, the purpose of this study is to explore the asymmetric relationship between physician mental health disorders and healthcare quality during the pandemic outbreak in Taiwan. METHODS: Daily data for care quality indicators and physician mental health disorders were collected from the National Insurance Research Database in Taiwan, and the quantile-on-quantile regression model was applied to proceed with our analyses. RESULTS: Our results indicated that the overall aggregate effects of each quantile of physician mental health disorders on the cumulative quantiles of healthcare quality are negative (positive) for the 14-day readmission rate (preventable hospitalization rate and non-urgent ED-visit rate). Positively (negatively) cumulative effects of each quantile of physician mental health disorders were detected in the middle (low and high) quantiles of the preventable hospitalization rate. The cumulative effects of each quantile of physician mental health disorders on the high (low and middle) quantiles of the 14-day readmission rate are negative (positive), but the cumulative effects on various quantiles of the non-urgent ED-visit rate exhibit the opposite pattern. CONCLUSION: The observed variation in the relationship between physician mental health disorders and different quantiles of healthcare quality suggests the need for tailored strategic interventions based on distinct levels of healthcare quality when addressing the higher risk of physician mental health disorders during the pandemic outbreak conditions. Dove 2023-11-06 /pmc/articles/PMC10638657/ /pubmed/37953809 http://dx.doi.org/10.2147/RMHP.S429516 Text en © 2023 Chen and Lin. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Chen, Wen-Yi Lin, Feng-Li On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses |
title | On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses |
title_full | On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses |
title_fullStr | On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses |
title_full_unstemmed | On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses |
title_short | On the Asymmetric Relationship Between Physician Mental Health Disorders on Quality of Healthcare Under the COVID-19 Pandemic in Taiwan: Quantile on Quantile Regression Analyses |
title_sort | on the asymmetric relationship between physician mental health disorders on quality of healthcare under the covid-19 pandemic in taiwan: quantile on quantile regression analyses |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638657/ https://www.ncbi.nlm.nih.gov/pubmed/37953809 http://dx.doi.org/10.2147/RMHP.S429516 |
work_keys_str_mv | AT chenwenyi ontheasymmetricrelationshipbetweenphysicianmentalhealthdisordersonqualityofhealthcareunderthecovid19pandemicintaiwanquantileonquantileregressionanalyses AT linfengli ontheasymmetricrelationshipbetweenphysicianmentalhealthdisordersonqualityofhealthcareunderthecovid19pandemicintaiwanquantileonquantileregressionanalyses |