PDF(Pubmed)
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.
摘要：
不良事件（AE）是医疗保健系统的重要关注点。然而,由于各种医疗服务的复杂性，很难评估它们的影响。本研究旨在使用诊断相关组（DRG）数据库评估AEs对住院患者预后的影响。我们对中国一家拥有2200张床位的多地区三级医院的住院患者进行了病例对照研究，使用DRG数据库中的数据。AE是指由需要额外住院治疗的医疗护理引起或促成的非预期身体伤害。监测,治疗,甚至死亡。相对重量(RW),DRG的特定指标，用来衡量诊断和治疗的难度，疾病严重程度,和医疗资源的利用。主要结果是住院时间（LOS）和住院费用。次要结果是出院回家。本研究应用了基于DRG的匹配，霍奇斯-莱曼估计,回归分析，和亚组分析评估AE对结局的影响。通过排除短LOS和改变调整因子进行了两项敏感性分析，以评估结果的稳健性。我们确定了2690名住院患者，他们被分为329个DRG，包括1345例出现AE的患者（病例组）和1345例DRG匹配的正常对照。Hodges-Lehmann估计和广义线性回归分析显示，AE导致LOS延长(未经调整的差异，7天,95%置信区间[CI]6-8天；调整后的差异，8.31天，95%CI7.16-9.52天)和超额住院费用(未调整差额，$2186.40，95%CI：$1836.87-$2559.16；调整后的差额，2822.67美元，95%CI：2351.25美元-3334.88美元）。Logistic回归分析显示，AEs与出院回家的几率较低相关（未调整比值比[OR]0.66，95%CI0.54-0.82；调整后OR0.75，95%CI0.61-0.93）。亚组分析表明，每个亚组的结果基本一致。在复杂疾病（RW≥2）和与高度伤害亚组（中度伤害及以上组）相关的AE后，LOS和住院费用显着增加。在敏感性分析中获得了类似的结果。AE的负担，特别是那些与复杂疾病和严重危害有关的疾病，在中国意义重大。DRG数据库是有价值的信息源，可用于评估和管理AE。
