Lane Isabel, Bryce Ashley, Ingle Suzanne M, Hay Alastair D
National Institute for Health Research School for Primary Care Research, Centre for Academic Primary Care, University of Bristol, Bristol, UK.
The National Institute for Health Research Health Protection Research Unit in Evaluation of Interventions at University of Bristol, Bristol, UK.
Fam Pract. 2018 Sep 18;35(5):542-550. doi: 10.1093/fampra/cmy008.
Antimicrobial resistance is a significant threat to public health. Diagnostic uncertainty is a key driver of antimicrobial prescribing. We sought to determine whether locally relevant, real-time syndromic or microbiological infection epidemiology can improve prescribing by reducing diagnostic uncertainty.
Eligible studies investigated effects on primary care prescribing for common infections in Organisation For Economic Co-Operation And Development countries. We searched Medline, Embase, Cumulative index to nursing and allied health literature, Web of Science, grey literature sources, thesis databases and trial registries.
We identified 9548 reports, of which 17 were eligible, reporting 12 studies, of which 3 reported relevant outcomes. The first (observational) showed antibacterial prescribing for upper respiratory infections reduced from 26.4% to 8.6% (P = 0.01). The second (observational) showed antibacterial prescribing reduced during influenza pandemic compared with seasonal influenza periods [odds ratio (OR) 0.72 (95% CI, 0.68 to 0.77), P < 0.001], while antiviral prescribing increased [OR 6.43 (95% CI, 5.02 to 8.25), P < 0.001]. The likelihood of prescribing also decreased as the number of infection cases a physician saw increased in the previous week [OR 0.57 (95% CI, 0.51 to 0.63), P < 0.001 for ≥12 versus ≤1 patient). The third (randomized-controlled trial) showed an absolute reduction in antibacterial prescribing of 5.1% during a period of moderate influenza activity (P < 0.05). We did not find measures of diagnostic certainty, harms or costs.
There is promising evidence that epidemiological syndromic and microbiological data can reduce primary care antimicrobial prescribing. Future research should use randomized designs of behaviourally informed interventions, investigate costs and harms, and establish mechanisms of behaviour change.
CRD42016038871.
抗菌药物耐药性对公众健康构成重大威胁。诊断不确定性是抗菌药物处方的关键驱动因素。我们试图确定本地相关的实时症状性或微生物感染流行病学是否可以通过减少诊断不确定性来改善处方。
符合条件的研究调查了对经济合作与发展组织国家常见感染的初级保健处方的影响。我们检索了Medline、Embase、护理及相关健康文献累积索引、科学引文索引、灰色文献来源、论文数据库和试验注册库。
我们识别出9548篇报告，其中17篇符合条件，报告了12项研究，其中3项报告了相关结果。第一项（观察性研究）显示，上呼吸道感染的抗菌药物处方率从26.4%降至8.6%（P = 0.01）。第二项（观察性研究）显示，与季节性流感时期相比，流感大流行期间抗菌药物处方减少[比值比（OR）0.72（95%置信区间，0.68至0.77），P < 0.001]，而抗病毒药物处方增加[OR 6.43（95%置信区间，5.02至8.25），P < 0.001]。随着医生前一周看到的感染病例数量增加，处方的可能性也降低[OR 0.57（95%置信区间，0.51至0.63），≥12例患者与≤1例患者相比，P < 0.001]。第三项（随机对照试验）显示，在中度流感活动期间，抗菌药物处方绝对减少了5.1%（P < 0.05）。我们未找到诊断确定性、危害或成本的衡量指标。
有证据表明，症状性和微生物学的流行病学数据可以减少初级保健中的抗菌药物处方。未来的研究应采用行为学知情干预的随机设计，调查成本和危害，并建立行为改变机制。
PROSPERO注册编号：CRD42016038871。
