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

Abstract

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.

On the Association Between Demographic Structural Change and the Effectiveness of Nurse Staffing Policy for Inpatient Care: Evidence from Taiwan

“…Consequently, the empirical results derived from our models should not be extrapolated to individual behavior changes at specific ages in response to PNR adjustments in hospitals, in order to mitigate the risk of ecological fallacies. 62 Second, despite the frequent use of the 14-day readmission rate as an indicator of inpatient care quality, 27 , 45 , 46 it is important to recognize that the likelihood of 14-day readmission may be particularly sensitive within the older population, who are more likely to experience severe illness, multiple chronic conditions, and pronounced comorbidity levels. 46 Consequently, we have advocated for prudence in our discussion regarding the interplay between demographic structural changes and the effectiveness of nurse staffing policy for inpatient care.…”

“…The data utilized for this research were sourced from multiple databases: the Open Database of Taiwan’s National Health Insurance (managed by the National Health Insurance Administrative), the Healthcare Quality Database of the Center of Quality Management (under the administration of the Joint Commission of Taiwan), and the Macroeconomics Statistics Database (administered by the Directorate General of Budget, Accounting, and Statistics). Specifically, data pertaining to inpatient care quality (quantified by 14-day readmission rates), 27 , 45 , 46 labor input (measured through PNR denoting the average number of patients cared for by one nurse per shift), 27 and length of stay per admission (utilized to control for the severity of illnesses) 47 were collected for medical centers, regional hospitals, and district hospitals. These data were employed in the estimation of the hospital production function outlined in the data analysis section below.…”