Effect of a computer network-based feedback program on antibiotic prescription rates of primary care physicians: A cluster randomized crossover-controlled trial

被引:21
作者
Chang, Yue [1 ,2 ]
Sangthong, Rassamee [2 ]
McNeil, Edward B. [2 ]
Tang, Lei [1 ]
Chongsuvivatwong, Virasakdi [2 ]
机构
[1] Guizhou Med Univ, Sch Med & Hlth Management, Guiyang 550025, Guizhou, Peoples R China
[2] Prince Songkla Univ, Epidemiol Unit, Fac Med, Hat Yai 90110, Songkhla, Thailand
基金
中国国家自然科学基金;
关键词
Antibiotic prescription rates; Crossover trial; Feedback intervention; Primary care physicians; Health information system; PROTON PUMP INHIBITORS; TRACT-INFECTIONS; IMPLEMENTATION; CHINA;
D O I
10.1016/j.jiph.2020.05.027
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Objective: Antibiotic overuse is one of the major prescription problems in rural China and a major risk factor for antibiotic resistance. Low antibiotic prescription rates can effectively reduce the risk of antibiotic resistance. We hypothesized that under a paperless, computer-based feedback system the rates of antibiotic prescriptions among primary care physicians can be reduced. Methods: A cluster randomized crossover open controlled trial was conducted in 31 hospitals. These hospitals were randomly allocated to two groups to receive the intervention for three months followed by no intervention for three months in a random sequence. The feedback intervention information, which dis played the physicians' antibiotic prescription rates and ranking, was updated every 10 days. The primary outcome was the 10-day antibiotic prescription rate of the physicians. Results: There were 82 physicians in group 1 (intervention first followed by control) and 81 in group 2 (control first followed by intervention). Baseline comparison showed no significant difference in antibiotic prescription rate between the two groups (30.8% vs 35.2%, P-value = 0.07). At the crossover point, the relative reduction in antibiotic prescription rate was significantly higher among physicians in the intervention group than in the control group (33.1% vs 20.3%, P-value < 0.001). After a further 3 months, the rate of decline in antibiotic prescriptions was also significantly greater in the intervention group compared to the control group (14.2% vs 4.6%, P-value < 0.001). The characteristics of physicians did not significantly determine the change in rate of antibiotic prescriptions. Conclusion: A computer network-based feedback intervention can significantly reduce the antibiotic prescription rates of primary care outpatient physicians and continuously affected their prescription behavior for up to six months. (C) 2020 The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences.
引用
收藏
页码:1297 / 1303
页数:7
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