Nghiem Son, Afoakwah Clifford, Scuffham Paul, Byrnes Joshua
Centre for Applied Health Economics, School of Medicine and Dentistry, Griffith University, 170 Kessels Rd, Nathan, QLD 4111, Australia.
Menzies Health Institute Queensland, G40, Gold Coast Campus, Griffith University QLD 4222, Australia.
Infect Prev Pract. 2021 Dec 13;4(1):100198. doi: 10.1016/j.infpip.2021.100198. eCollection 2022 Mar.
Hospital-acquired complications (HACs) are costly and associated with adverse health outcomes, although they can be avoided. Administrative linkage health data have become more accessible and can be used to monitor and reduce HAC.
This study aims to use linkage administrative data to benchmark the safety performance of hospitals and estimate the feasible magnitude that HAC can be reduced. We also identify risk factors associated with HACs, and estimate the effects of HACs on adverse health outcomes and hospital costs.
This is a retrospective linkage cohort study. The cohort includes 371,040 inpatient multiple-day admissions of 83,025 cardiovascular disease patients admitted to public hospitals in 2010 with follow-ups until 2015.Data envelopment analysis was applied to benchmark the patient safety performance of hospitals. Logistic regression was used to examine the odds of HAC and its effects on in-hospital mortality and 30-day readmission. Generalised linear models were used to identify the impacts of HACs on hospital costs and the length of hospital stay.
On average, 9.3% of multiple-day hospital admissions were associated with HACs. The average HAC rate can be reduced by two percentage points if all hospitals achieve the safety record of best-practice hospitals. Old age and multiple comorbidities were major driving factors of HACs.
Cardiovascular disease patients with HAC have a higher risk of death, stay longer in hospitals and incur higher health care costs. The average HAC rates can be reduced by two percentage points by learning from best-practice hospitals operating in the same region.
医院获得性并发症(HACs)成本高昂且与不良健康后果相关,尽管这些并发症是可以避免的。行政关联健康数据变得更容易获取,可用于监测和减少HAC。
本研究旨在利用关联行政数据对医院的安全绩效进行基准评估,并估计HAC可降低的可行幅度。我们还确定与HAC相关的风险因素,并估计HAC对不良健康后果和医院成本的影响。
这是一项回顾性关联队列研究。该队列包括2010年入住公立医院的83025名心血管疾病患者的371040例多日住院病例,随访至2015年。数据包络分析用于对医院的患者安全绩效进行基准评估。逻辑回归用于检验HAC的几率及其对住院死亡率和30天再入院率的影响。广义线性模型用于确定HAC对医院成本和住院时间的影响。
平均而言,9.3%的多日住院病例与HAC相关。如果所有医院都达到最佳实践医院的安全记录,平均HAC率可降低两个百分点。老年和多种合并症是HAC的主要驱动因素。
患有HAC的心血管疾病患者死亡风险更高,住院时间更长,医疗费用更高。通过向同一地区运营的最佳实践医院学习,平均HAC率可降低两个百分点。