Impact of healthcare-associated infection on healthcare services and survival of patients with cancer: a propensity score-matched retrospective study.

backgroundHealthcare-associated infections (HAI) lead to poor patient outcomes, including morbidity, mortality, length of hospital stay (LOS) and costs. However, limited data exists on the impact of HAI on LOS, cost at different quantiles and the survival of patients with cancer.

objectiveTo assess the impact of HAIs on LOS, costs, and survival of cancer patients.

methodsThis retrospective cohort study used data from January 2017 to December 2018 from a tertiary cancer hospital in Henan. Patient demographic data were sourced from the hospital's electronic medical records. Inclusion criteria were primary cancer diagnoses (ICD codes C00-C97). We balanced the distribution of baseline characteristics between patients with HAI and without using propensity score matching. Quantile regression can estimate how independent variables affect dependent variables at different quantiles. We conducted a quantile regression that assessing the impact of HAI on LOS and costs for patients with cancer and using Kaplan-Meier survival curves to compare the survival.

resultsOur study included 291,535 patients with cancer, among of whom 4,784(1.6%) were diagnosed with HAI and 286,748 were not. Patients with HAI exhibited significantly longer hospital stays, with a mean duration of 26.1 days (range: 17.0 to 40.6 days), compared to their counterparts without HAIs, who had an average stay of 7.2 days (range: 4.0 to 14.0 days) (p < 0.01). Economically, the average hospitalization cost for patients without HAI was $1575.8 (range: 865.6 to 3106.3), substantially lower than the $8710.8 (range: $4073.8 to 13434.0) observed for patients with HAI (p < 0.01). After adjusting for confounders in quantile regression models, HAI was associated with a median increase in LOS of 11.4 (95% confidence interval (CI): 10.9-12.0) days and with excess costs of USD 3449.3 (95% CI: 3281.9-3616.7). The hazard ratio (HR) of death for patients with an HAI was significantly higher than for patients without an HAI (HR: 1.62, 95% CI: 1.50-1.74).

conclusionHAI prolongs the LOS, increases hospital costs, and worsens the survival of patients with cancer compared with other diseases. Our quantile regression results indicate that the impact of HAI on hospitalization costs and LOS is more pronounced among patients with higher baseline costs and longer LOS (e.g., at the 95th percentile). This suggests that patients with more severe conditions or advanced disease stages are more vulnerable to the adverse effects of HAI. RELEVANCE TO CLINICAL PRACTICE: Targeted surveillance and preventive interventions, such as early infection screening and strict adherence to infection control protocols, should focus on high-risk patients with prolonged LOS and high costs. By preventing infections in these patients, we can more effectively reduce the additional burden of HAI on costs and LOS. This study informs clinical practice and decision-making for nurses and nursing educators who manage HAI. PATIENT OR PUBLIC CONTRIBUTION: Patients and healthcare professionals helped in data collection at the Hospital.