社会规范反馈减少临床医生抗生素处方行为干预效果meta分析

石林; 曾颖超; 李伟彬; 刘立; 刘雨晨; 黄绮娴; 陈少贤; 刘朝杰; 杨廉平

doi:10.11847/zgggws1137911

社会规范反馈减少临床医生抗生素处方行为干预效果meta分析

doi: 10.11847/zgggws1137911

1.
中山大学公共卫生学院，广东广州 510080
2.
澳大利亚乐卓博大学心理与公共卫生学院

基金项目: 国家自然科学基金（72074234）；美国中华医学基金会基金（CMB – OC19 – 337）；广东省自然科学基金（2022A1515011338）

详细信息

作者简介:
石林（1998 – ），男，安徽亳州人，硕士在读，研究方向：公共卫生管理与政策

通讯作者:
杨廉平，E-mail：yanglp7@mail.sysu.edu.cn

中图分类号: R 969.3
计量
- 文章访问数: 43
- HTML全文浏览量: 20
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2022-01-04
- 网络出版日期: 2022-12-19
- 刊出日期: 2023-01-31

Behavioral intervention effect of social norm feedback on reducing clinicians′ antibiotic prescribing: a meta-analysis

1.
School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong Province 510080, China

摘要

摘要: 目的评价社会规范反馈（SNF）减少临床医生抗生素处方行为的干预效果，为减缓抗菌药物的不合理使用提供参考依据。方法检索中国期刊全文数据库、维普期刊全文数据库、万方数据库、PubMed数据库、Web of Science数据库、Scopus数据库和EMBASE数据库，并辅以文献追溯法收集各数据库从建库至2021年10月31日公开发表的关于SNF减少医生抗生素处方行为的相关文献，应用Stata16.0统计学软件对纳入的文献进行meta分析。结果最终纳入9篇英文文献，累计样本量19528例；meta分析结果显示，SNF干预可使临床医生的抗生素处方率降低4 %（RD = – 0.04，95 % CI = – 0.06～ – 0.03）；亚组分析结果显示，干预间隔 < 3个月和 ≥ 3个月、干预单元为医生和医疗机构、干预方式为信件和邮件/电子弹窗、排名方式以模糊排名的SNF干预均可降低临床医生的抗生素处方率（均P < 0.001）；敏感性分析和发表偏倚检验结果显示，本次meta分析纳入的文献存在的发表偏倚较小，结果相对稳定。结论 SNF干预可减少临床医生的抗生素处方行为。
- 抗生素处方行为 /
- 社会规范反馈（SNF） /
- 干预效果 /
- 临床医生 /
- meta分析
Abstract: Objective To evaluate intervention effect of social norm feedback (SNF) on reducing antibiotic prescribing behavior of clinicians and to provide a reference for decreasing irrational use of antibiotics. Methods Literatures published relevant to intervention effect of SNF on doctors′ antibiotic prescribing behavior were retrieved through searching publications up to October 31, 2021 from China Journal Full-Text Database, VIP Journal Full-Text Database, WanFang Database, PubMed Database, Web of Science Database, Scopus Database, and EMBASE Database; the searching was supplemented using literature retrospective method. Stata 16.0 statistical software was adopted to perform meta-analysis. Results Totally 9 English literatures with 19 528 pooled participants were included in the analysis. The results of meta-analysis showed that SNF intervention can reduce the number of clinicians′ antibiotic prescriptions by 4% (rate difference, [RD] = – 0.04, 95% confidence interval [95% CI]: – 0.06 – – 0.03). Further subgroup analysis indicated that all SNF interventions being carried out through following approaches could significantly reduce antibiotic prescription rate of clinicians: with short interval (< 3 months) or long interval ( ≥ 3 months), targeted at doctors or medical institutions, disseminating intervening information by letters and emails/electronic pop-up windows, and adopting fuzzy ranking evaluation (all P < 0.001). Sensitivity analysis and publication bias test demonstrated that the literatures included in the analysis had less publication bias and the results were relatively stable. Conclusion SNF intervention could restrain clinicians′ antibiotic prescribing behavior.
- antibiotic prescribing behavior /
- social norm feedback /
- intervention effect /
- clinician /
- meta-analysis

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图 1 文献筛选流程图

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图 2 SNF减少临床医生抗生素处方行为干预效果的meta分析

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表 1 纳入文献基本特征

第一作者	发表年份	研究地区	样本量	研究方法	干预时长（月）	干预次数（次）	干预间隔	干预单元	干预方式	排名情况 ^a
Ratajczak M^[18]	2019	英国英格兰	7425	非RCT	6	1	6个月	医生	信件	模糊排名
Hallsworth M^[19]	2016	英国英格兰	1581	RCT	6	2	3个月	医疗机构	信件	精确排名
Chang Y^[20]	2020	中国贵州	163	RCT	6	18	10天	医生	电子弹窗	精确排名
Daneman N^[21]	2021	加拿大安大略	1238	RCT	24	8	3个月	医生	电子邮件	模糊排名
Cummings PL^[22]	2020	美国	28	RCT	6	3	2个月	医生	电子邮件	精确排名
Meeker D^[23]	2016	美国	248	RCT	18	18	1个月	医生	电子邮件/电子弹窗	模糊排名
Schwartz KL^[24]	2021	加拿大	3465	RCT	12	1	12个月	医生	信件	模糊排名
Elouafkaoui P^[25]	2016	英国苏格兰	2566	RCT	12	3	3～6个月	医疗机构	信件	模糊排名
Hemkens LG^[26]	2017	瑞士	2814	RCT	24	8	3个月	医生	电子邮件	模糊排名
注：a 精确排名指将该医疗机构或者该地区所有的同领域、相同时间段的医生按其所开具的抗生素处方量进行排名，参与研究的医生清楚知道自己在该医疗机构或当地同领域内抗生素处方量的排名情况；模糊排名指通过将高抗生素处方医生的处方水平与该医疗机构或当地医疗机构的同领域内、相同时间段的平均抗生素处方水平进行比较，或者是高抗生素处方医生只知道自己抗生素处方水平在同领域、相同时间段内的大致位置（如前25 %、30 %），并不知道自己所处的精确位置。

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表 2 SNF减少临床医生抗生素处方行为干预效果的亚组分析

组别		文献数	异质性检验			效应模型	效应值
组别		文献数	I²值	Q 值	P 值	效应模型	RD 值	95 % CI	P 值
干预间隔	干预间隔 < 3个月	3	82.10 %	11.17	< 0.001	随机	– 0.07	– 0.12～ – 0.02	< 0.001
干预间隔	干预间隔 ≥ 3个月	6	34.01 %	7.58	0.180	固定	– 0.03	– 0.04 ～ – 0.02	< 0.001
干预单元	医生	7	74.48 %	23.51	< 0.001	随机	– 0.04	– 0.06～ – 0.02	< 0.001
干预单元	医疗机构	2	1.92 %	1.02	0.310	固定	– 0.03	– 0.05～ – 0.02	< 0.001
干预方式	信件	4	0.00 %	1.49	0.680	固定	– 0.04	– 0.04～ – 0.03	< 0.001
干预方式	电子邮件/电子弹窗	5	82.79 %	23.25	< 0.001	随机	– 0.05	– 0.08～ – 0.01	< 0.001
排名情况	精确排名	2	90.74 %	10.80	< 0.001	随机	– 0.09	– 0.20～0.01	0.090
排名情况	模糊排名	7	36.75 %	9.49	0.150	固定	– 0.03	– 0.04～ – 0.02	< 0.001

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