Trading quality for quantity? Evidence from patient level data in China

Abstract

In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impact of the number of hospital admissions per day on a patient’s length of stay (LOS) and hospital mortality rate using both ordinary least squares (OLS) and instrumental variable (IV) methods. To deal with potential endogeneity problems and accurately identify the impact of medical staff configuration on medical quality, the daily air quality index was selected as the IV. Furthermore, we examined the differential effects of hospital admissions on the quality of care across different hospital tiers. We used the data from a random sample of 10% of inpatients from a city in China, covering the period from January 2014 to June 2019. Our final regression analysis included a sample of 167 disease types (as per the ICD-10 classification list) and 862,722 patient cases from 517 hospitals. According to our results, the LOS decreased and hospital mortality rate increased with an increasing number of admissions. Using the IV method, for every additional hospital admission, there was a 6.22% (p < 0.01) decrease in LOS and a 1.86% (p < 0.01) increase in hospital mortality. The impact of healthcare staffing levels on the quality of care varied between different hospital tiers. The quality of care in secondary hospitals was most affected by the number of admissions, with the average decrease of 18.60% (p < 0.05) in LOS and the increase of 6.05% (p < 0.01) in hospital mortality for every additional hospital admission in our sample. The findings suggested that the supply of medical services in China should be increased and a hierarchical diagnosis and treatment system should be actively promoted.

Risk factor identification and prediction models for prolonged length of stay in hospital after acute ischemic stroke using artificial neural networks

“…In addition to hospitalization costs, prolonged LOS may be associated with the increased use of healthcare resources, negatively affecting hospital capacity and medical personnel availability, reducing the quality of care, and preventing other patients from receiving inpatient care ( 15 , 16 ). Furthermore, patients with acute ischemic stroke (AIS) having prolonged LOS are more likely to develop complications such as hospital-acquired infections or gastrointestinal bleeding ( 17 , 18 ).…”

Identifying Risk Factors for Prolonged Length of Stay in Hospital and Developing Prediction Models for Patients with Cardiac Arrest Receiving Targeted Temperature Management

“…Furthermore, longer LOS may reduce the quality and efficiency of healthcare. Prolonged LOS may affect the capacity of hospital beds and the availability of healthcare personnel to accommodate patients, which may decrease the healthcare quality and deny other patients access to inpatient care [ 12 , 13 , 14 ]. Extended hospital stays may also result in patients being more susceptible to hospital-acquired infections and lead to less favorable outcomes [ 12 , 15 ].…”