Behavioral intervention effect of social norm feedback on reducing clinicians′ antibiotic prescribing: a meta-analysis
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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。 -
关键词:
- 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. -
Key words:
- antibiotic prescribing behavior /
- social norm feedback /
- intervention effect /
- clinician /
- meta-analysis
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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。 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 I2 值 Q 值 P 值 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 ≥ 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 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 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 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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