一项旨在减少中国农村地区抗生素处方的复杂干预措施：一项整群随机对照试验。

A complex intervention to reduce antibiotic prescribing in rural China: a cluster randomised controlled trial.

作者信息

Shen Xingrong, Stuart Beth, Cui Enci, Liu Rong, Zhang Tingting, Chai Jing, Cong Wenjuan, Hu Xiaowen, Oliver Isabel, Yao Guiqing, Little Paul, Lambert Helen, Yardley Lucy, Cabral Christie, Wang Debin

机构信息

School of Health Service Management, Anhui Medical University, Hefei Anhui 230032, China.

Center for Operational Health Service Research, Anhui Medical University, Hefei Anhui 230032, China.

出版信息

Lancet Reg Health West Pac. 2024 Nov 6;53:101236. doi: 10.1016/j.lanwpc.2024.101236. eCollection 2024 Dec.

DOI:10.1016/j.lanwpc.2024.101236

PMID:39559165

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11570860/

Abstract

BACKGROUND

Excessive use of antibiotics is a widespread problem. We aim to evaluate the efficacy of a multifaceted intervention for reducing antibiotic use in patients with respiratory tract infections (RTIs).

METHODS

In this two-arm cluster randomized controlled trial, we enrolled patients aged 18+ with symptomatic RTIs at 40 township health centers (THCs) selected from 10 counties in Anhui, China. The THCs were randomized using an online tool ('Sealed Envelope') to intervention or usual care (1:1 ratio), stratified by baseline antibiotic prescribing and with random block sizes (4 or 6). The intervention had five components: a half-day clinician training, a WeChat-based peer support group, a decision aid, a poster commitment letter and a patient leaflet. The primary outcome was whether antibiotics were prescribed at the index consultation. Secondary measures included defined daily dose (DDD), illness recovery rate, re-visits to other care-givers or retail pharmacies and incremental cost-effectiveness ratio (ICER). These measures were analyzed using generalized linear mixed modeling controlling for clustering. The study was registered as ISRCTN30652037.

FINDINGS

Between December 2021 and September 2022, 1053 patients were recruited (intervention, 21 THCs, n = 552; control, 19 THCs, n = 501), using consecutive sampling. Antibiotic prescribing rate was 55.25% and 66.67% in the intervention and control arms (Odds ratio 0.52, 95% confidence interval [CI]: 0.27, 0.98; p = 0.044). The intervention group also had lower, significant or non-significant, differences for other markers of antibiotic use: DDD (1.57 vs 2.75); prescriptions of two or more types of antibiotics (9.78% vs 11.58%); obtaining antibiotics from retail pharmacies (3.68% vs 5.78) or from other clinics (2.70% vs 4.05%). The intervention resulted in a cost reduction of 9.265 RMB (1.471 USD) per consultation episode and an ICER of -7769.98 RMB or -1233.33 USD/QALYs. The intervention did not encounter any major adverse event.

INTERPRETATION

The intervention package was effective and cost-effective in reducing antibiotics prescribing without adverse effects.

FUNDING

The trial was supported by National Natural Science Foundation of China (No. 81861138049) and United Kingdom Research Innovation (No. MR/S013717/1).

摘要

背景

抗生素的过度使用是一个普遍存在的问题。我们旨在评估一项多方面干预措施对减少呼吸道感染（RTIs）患者抗生素使用的疗效。

方法

在这项双臂整群随机对照试验中，我们在中国安徽省10个县选取的40个乡镇卫生院（THCs）纳入了18岁及以上有症状RTIs的患者。使用在线工具（“密封信封”）将THCs随机分为干预组或常规治疗组（1:1比例），按基线抗生素处方分层并采用随机区组大小（4或6）。干预措施有五个组成部分：为期半天的临床医生培训、基于微信的同伴支持小组、决策辅助工具、海报承诺书和患者宣传册。主要结局是在首次就诊时是否开具了抗生素。次要指标包括限定日剂量（DDD）、疾病康复率、再次就诊于其他医护人员或零售药店以及增量成本效益比（ICER）。使用控制聚类的广义线性混合模型对这些指标进行分析。该研究注册为ISRCTN30652037。

结果

在2021年12月至2022年9月期间，采用连续抽样法招募了1053名患者（干预组，21个THCs，n = 552；对照组，19个THCs，n = 501）。干预组和对照组的抗生素处方率分别为55.25%和66.67%（比值比0.52，95%置信区间[CI]：0.27，0.98；p = 0.044）。干预组在抗生素使用的其他指标方面也有较低的显著或非显著差异：DDD（1.57对2.75）；两种或更多种抗生素的处方（9.78%对11.58%）；从零售药店获取抗生素（3.68%对5.78%）或从其他诊所获取抗生素（2.70%对4.．05%）。干预措施使每次就诊费用降低了9.265元人民币（1.471美元），ICER为-7769.98元人民币或-1233.33美元/质量调整生命年。该干预措施未出现任何重大不良事件。