Temporal patterns and clinical characteristics of healthcare-associated infections in surgery patients: A retrospective study in a major Chinese tertiary hospital

Abstract

BackgroundGiven the preventable nature of most healthcare-associated infections (HAIs), it is crucial to understand their characteristics and temporal patterns to reduce their occurrence. MethodsA retrospective analysis of medical record cover pages from a Chinese hospital information system was conducted for surgery inpatients from 2010 to 2019. Association rules mining (ARM) was employed to explore the association between disease, procedure, and HAIs. Joinpoint models were used to estimate the annual HAI trend. The time series of each type of HAI was decomposed to analyze the temporal patterns of HAIs. ResultsThe study included data from 623,290 surgery inpatients over 10 years, and a significant decline in the HAI rate was observed. Compared with patients without HAIs, those with HAIs had a longer length of stay (29 days vs. 9 days), higher medical costs (96226.57 CNY vs. 22351.98 CNY), and an increased risk of death (6.42% vs. 0.18%). The most common diseases for each type of HAI differed, although bone marrow and spleen operations were the most frequent procedures for most HAI types. ARM detected that some uncommon diagnoses could strongly associate with HAIs. The time series pattern varied for each type of HAI, with the peak occurring in January for respiratory system infections, and in August and July for surgical site and bloodstream infections, respectively. ConclusionsOur findings demonstrate that HAIs impose a significant burden on surgery patients. The differing time series patterns for each type of HAI highlight the importance of tailored surveillance strategies for specific types of HAI.