ArticleFrontiers in public health2026
Propensity score matching assessment of direct medical charges for patients with healthcare-associated infections.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Importance: Healthcare-associated infections (HAIs) represent a significant source of harm related to healthcare delivery and are associated with substantial costs. A more precise estimation of the economic burden imposed by these infections can assist healthcare providers and payers in justifying investments in prevention strategies. Objective: To quantify the direct economic burden of healthcare-associated infections and identify the specific types of HAIs that impose the greatest economic costs. Methods: This is a retrospective case-control study. We enrolled all inpatients with hospitalizations lasting three calendar days or longer (from January 2023 to December 2024) at a Grade A tertiary hospital in Shenzhen, China, and propensity score matching (PSM) was applied for analysis. Demographic/clinical characteristics and direct medical costs were extracted from the EMR-integrated data analytics platform. In contrast, HAI surveillance data and laboratory parameters were sourced from the real-time HAI monitoring system. Results: Following PSM, the HAI group had significantly higher median total hospitalization costs than the non-HAI group (USD 7,158 vs. USD 1,212; Conclusion: The HAI group incurred higher total hospitalization charges compared to the non-HAI group, with increases observed across all individual charge components, including pharmaceuticals and laboratory test charges, which were the primary drivers of the overall increase. Among the various types of HAIs, CLABSIs resulted in the highest laboratory charges, while LRTIs were identified as the most prevalent and demonstrated significantly increased direct medical charges.
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