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使用优化的统计过程控制图对手术部位感染增加情况进行早期识别和应对——早期2RIS试验:一项多中心阶梯楔形整群随机对照试验

Early recognition and response to increases in surgical site infections using optimised statistical process control charts-The early 2RIS trial: A multicentre stepped wedge cluster randomised controlled trial.

作者信息

Baker Arthur W, Ilieş Iulian, Benneyan James C, Lokhnygina Yuliya, Foy Katherine R, Lewis Sarah S, Wood Brittain, Baker Esther, Crane Linda, Crawford Kathryn L, Cromer Andrea L, Padgette Polly, Roach Linda, Adcock Linda, Nehls Nicole, Salem Joseph, Bratzler Dale, Dellinger E Patchen, Greene Linda R, Huang Susan S, Mantyh Christopher R, Anderson Deverick J

机构信息

Division of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.

Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.

出版信息

EClinicalMedicine. 2022 Oct 17;54:101698. doi: 10.1016/j.eclinm.2022.101698. eCollection 2022 Dec.

Abstract

BACKGROUND

Traditional approaches for surgical site infection (SSI) surveillance have deficiencies that delay detection of SSI outbreaks and other clinically important increases in SSI rates. We investigated whether use of optimised statistical process control (SPC) methods and feedback for SSI surveillance would decrease rates of SSI in a network of US community hospitals.

METHODS

We conducted a stepped wedge cluster randomised trial of patients who underwent any of 13 types of common surgical procedures across 29 community hospitals in the Southeastern United States. We divided the 13 procedures into six clusters; a cluster of procedures at a single hospital was the unit of randomisation and analysis. In total, 105 clusters were randomised to 12 groups of 8-10 clusters. All participating clusters began the trial in a 12-month baseline period of control or "traditional" SSI surveillance, including prospective analysis of SSI rates and consultative support for SSI outbreaks and investigations. Thereafter, a group of clusters transitioned from control to intervention surveillance every three months until all clusters received the intervention. Electronic randomisation by the study statistician determined the sequence by which clusters crossed over from control to intervention surveillance. The intervention was the addition of weekly application of optimised SPC methods and feedback to existing traditional SSI surveillance methods. Epidemiologists were blinded to hospital identity and randomisation status while adjudicating SPC signals of increased SSI rates, but blinding was not possible during SSI investigations. The primary outcome was the overall SSI prevalence rate (PR=SSIs/100 procedures), evaluated via generalised estimating equations with a Poisson regression model. Secondary outcomes compared traditional and optimised SPC signals that identified SSI rate increases, including the number of formal SSI investigations generated and deficiencies identified in best practices for SSI prevention. This trial was registered at ClinicalTrials.gov, NCT03075813.

FINDINGS

Between Mar 1, 2016, and Feb 29, 2020, 204,233 unique patients underwent 237,704 surgical procedures. 148,365 procedures received traditional SSI surveillance and feedback alone, and 89,339 procedures additionally received the intervention of optimised SPC surveillance. The primary outcome of SSI was assessed for all procedures performed within participating clusters. SSIs occurred after 1171 procedures assigned control surveillance (prevalence rate [PR] 0.79 per 100 procedures), compared to 781 procedures that received the intervention (PR 0·87 per 100 procedures; model-based PR ratio 1.10, 95% CI 0.94-1.30, =0.25). Traditional surveillance generated 24 formal SSI investigations that identified 120 SSIs with deficiencies in two or more perioperative best practices for SSI prevention. In comparison, optimised SPC surveillance generated 74 formal investigations that identified 458 SSIs with multiple best practice deficiencies.

INTERPRETATION

The addition of optimised SPC methods and feedback to traditional methods for SSI surveillance led to greater detection of important SSI rate increases and best practice deficiencies but did not decrease SSI rates. Additional research is needed to determine how to best utilise SPC methods and feedback to improve adherence to SSI quality measures and prevent SSIs.

FUNDING

Agency for Healthcare Research and Quality.

摘要

背景

传统的手术部位感染(SSI)监测方法存在缺陷,会延迟对SSI暴发及其他临床上重要的SSI发生率升高的检测。我们调查了在美国社区医院网络中,使用优化的统计过程控制(SPC)方法及反馈进行SSI监测是否会降低SSI发生率。

方法

我们在美国东南部29家社区医院中,对接受13种常见外科手术中任意一种的患者进行了一项阶梯式楔形整群随机试验。我们将这13种手术分为6组;单个医院的一组手术为随机化和分析单位。总共105组被随机分为12组,每组8 - 10组。所有参与组在为期12个月的对照或“传统”SSI监测基线期开始试验,包括对SSI发生率进行前瞻性分析以及为SSI暴发和调查提供咨询支持。此后,每隔三个月有一组从对照监测过渡到干预监测,直至所有组都接受干预。由研究统计学家进行电子随机化,确定各组从对照监测过渡到干预监测的顺序。干预措施是在现有的传统SSI监测方法基础上,每周增加应用优化的SPC方法及反馈。在判定SSI发生率升高的SPC信号时,流行病学家对医院身份和随机化状态不知情,但在SSI调查期间无法保持不知情。主要结局是总体SSI患病率(PR = SSI数/100例手术),通过采用泊松回归模型的广义估计方程进行评估。次要结局比较了识别SSI发生率升高的传统和优化SPC信号,包括发起的正式SSI调查数量以及在SSI预防最佳实践中发现的缺陷。本试验已在ClinicalTrials.gov注册,注册号为NCT03075813。

研究结果

在2016年3月1日至2020年2月29日期间,204,233名不同患者接受了237,704例外科手术。148,365例手术仅接受传统SSI监测和反馈,89,339例手术还额外接受了优化SPC监测干预。对参与组内进行的所有手术评估SSI主要结局。在接受对照监测的1171例手术(患病率为每100例手术0.79例)后发生了SSI,相比之下,接受干预的781例手术(患病率为每100例手术0.87例;基于模型的PR比值为1.10,95%CI为0.94 - 1.30,P = 0.25)后发生了SSI。传统监测发起了24次正式SSI调查,识别出120例存在两项或更多围手术期SSI预防最佳实践缺陷的SSI。相比之下,优化SPC监测发起了74次正式调查,识别出458例存在多项最佳实践缺陷的SSI。

解读

在传统的SSI监测方法中增加优化的SPC方法及反馈,能更有效地检测到重要的SSI发生率升高和最佳实践缺陷,但并未降低SSI发生率。需要进一步研究以确定如何最佳利用SPC方法及反馈来提高对SSI质量指标的依从性并预防SSI。

资金来源

医疗保健研究与质量机构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/507f/9583445/ccdd3b74c574/gr1.jpg

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