Association between compliance with quality indicators and hospitalisation expenses in patients with heart failure: a retrospective study using quantile regression model in China

Abstract

ObjectiveTo explore the association between compliance with quality indicators and hospitalisation expenses in patients with heart failure.DesignGeneralised linear model and quantile regression model were used to examine the association between compliance with five quality indicators and hospitalisation expenses.SettingGrade A hospital in Fujian Province, China.ParticipantsData on 2568 heart failure admissions between 2010 and 2015 were analysed.ResultsThe median (IQR) of hospitalisation expenses of 2568 patients was ¥10.9 (¥6.9–¥31.6) thousand. The rates of compliance with five quality indicators were 90.3% for evaluation of left ventricular function, 43.8% for diuretics, 62.0% for ACE inhibitors (ACEI) or angiotensin receptor blockers (ARB), 67.4% for beta-blockers, and 58.9% for aldosterone receptor antagonists. After adjustment for gender, age, residence, method of payment, number of diseases before admission, number of diseases at admission, number of emergency treatments during hospital stay and length of stay, patients who received evaluation for left ventricular function, diuretics, or ACEI or ARB had lower hospitalisation expenses, and patients who received beta-blockers had higher hospitalisation expenses, compared with their counterparts in generalised linear models. Differences in hospitalisation expenses between compliance and non-compliance with quality indicators became larger across quantile levels of hospitalisation expenses, and were found to be statistically significant when quantile level exceeded 0.80 (¥39.7 thousand) in quantile regression models.ConclusionsThe quality of care for patients with heart failure was below the target level. There was a negative relationship between compliance with quality indicators and hospitalisation expenses at the extreme quantile of expenses. More attention should be given to patients who may experience extreme expenses, and effective measures should be taken to improve the quality of care they receive.

Letter by Norris-Grey et al Regarding Article, “Multiple Vulnerabilities to Health Disparities and Incident Heart Failure Hospitalization in the REGARDS Study”

“…Data from Fu et al 3 looking into the relationship between compliance of quality indicators and health expenses in China revealed a negative correlation at the extreme quantile of expenses. It can be argued that SDVs may reduce compliance to quality indicators as SDVs act as a barrier to adequate quality of care.…”

Identify hospitalization cost drivers of traumatic fracture patients in China using quantile regression and backpropagation neural network

“…Recently, quantile regression (QR) and backpropagation neural network (BPNN) has been applied to shed such light on healthcare studies [5][6][7][8]. QR models relationship between predictors and the response variable across different quantiles without strict normal distributional assumptions like ordinal least square regression, providing more nuanced understanding of the data, especially when data distribution is heavily skewed with outliers [9][10][11][12].…”