ArticleScientific reports2024
The influence of adverse events on inpatient outcomes in a tertiary hospital using a diagnosis-related group database.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Risk factors associated with nursing-sensitive adverse events in older hospitalised patients: A retrospective chart review.International journal of nursing studies advances · 2026Article
- High-magnification inpatient cases under DIP payment reform: prevalence, cost burden, and risk factors in an NHC-administered hospital in China.Frontiers in public health · 2026Observational
- A real-world study on the influence of unplanned reoperations on hospitalized patients using the diagnosis-related group.Annals of medicine · 2025Article
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6 authors.
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Abstract
Adverse events (AEs) are a significant concern for healthcare systems. However, it is difficult to evaluate their influence because of the complexity of various medical services. This study aimed to assess the influence of AEs on the outcomes of hospitalized patients using a diagnosis-related group (DRG) database. We conducted a case-control study of hospitalized patients at a multi-district tertiary hospital with 2200 beds in China, using data from a DRG database. An AE refers to an unintended physical injury caused or contributed to by medical care that requires additional hospitalization, monitoring, treatment, or even death. Relative weight (RW), a specific indicator of DRG, was used to measure the difficulty of diagnosis and treatment, disease severity, and medical resources utilized. The primary outcomes were hospital length of stay (LOS) and hospitalization costs. The secondary outcome was discharge to home. This study applied DRG-based matching, Hodges-Lehmann estimate, regression analysis, and subgroup analysis to evaluate the influence of AEs on outcomes. Two sensitivity analyses by excluding short LOS and changing adjustment factors were performed to assess the robustness of the results. We identified 2690 hospitalized patients who had been divided into 329 DRGs, including 1345 patients who experienced AEs (case group) and 1345 DRG-matched normal controls. The Hodges-Lehmann estimate and generalized linear regression analysis showed AEs led to prolonged LOS (unadjusted difference, 7 days, 95% confidence interval [CI] 6-8 days; adjusted difference, 8.31 days, 95% CI 7.16-9.52 days) and excess hospitalization costs (unadjusted difference, $2186.40, 95% CI: $1836.87-$2559.16; adjusted difference, $2822.67, 95% CI: $2351.25-$3334.88). Logistic regression analysis showed AEs were associated with lower odds of discharge to home (unadjusted odds ratio [OR] 0.66, 95% CI 0.54-0.82; adjusted OR 0.75, 95% CI 0.61-0.93). The subgroup analyses showed that the results for each subgroup were largely consistent. LOS and hospitalization costs increased significantly after AEs in complex diseases (RW ≥ 2) and in relation to high degrees of harm subgroups (moderate harm and above groups). Similar results were obtained in sensitivity analyses. The burden of AEs, especially those related to complex diseases and severe harm, is significant in China. The DRG database serves as a valuable source of information that can be utilized for the evaluation and management of AEs.
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