解释常见感染中抗生素处方的差异：基于英国初级保健数据的三向方差分解
Explaining variation in antibiotic prescribing for common infections: A three-way variance decomposition using UK primary care data.
文献信息
| PMID | 42785570 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Nam Nguyen |
| 作者单位 | Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and AMR at University of Oxford in partnership with the UK Health Security Agency, UK. Electronic address: nam.nguyen@phc.ox.ac.uk. |
| 期刊 | The Journal of infection |
| SCI 分区 | Q1 |
| IF | 9.1 |
| 研究类型 | 临床研究 · 临床 |
| 所属专科 | 耳科 |
中文摘要
目的： 英国全科诊所之间常见感染抗生素处方的差异可能部分由病例组合差异解释。我们旨在量化在考虑病例组合后，诊所间处方规范差异可解释多少这种变异。
方法： 我们使用英国临床实践研究数据链（CPRD）Aurum数据库，识别了11种常见感染的全科医生就诊记录。三向方差分解量化了三个模型（无调整、最小调整（年龄/性别）和完全病例组合调整）中总方差归因于患者病例组合、诊所间变异和残余未解释方差的比例。对于下呼吸道感染和咽痛，使用外部数据插补疾病严重程度，以估计未测量感染严重程度的潜在影响。
结果： 我们识别了2019年的3,820,806次就诊。大多数疾病在全科诊所间存在明显的抗生素处方变异性。在完全调整模型中，诊所间变异解释了总方差的5.8-32.6%，在11种感染中有9种超过病例组合归因的变异。急性中耳炎和上呼吸道感染（URTI）——这两种疾病在诊所间处方差异大，且调整后诊所间差异归因的方差较高（分别为12.6%和10.3%）——是公平处方指标的 promising 候选。与无调整相比，完全病例组合调整降低了诊所间差异对总方差的贡献，而最小年龄-性别调整影响甚微。在完全病例组合调整基础上插补感染严重程度进一步降低了诊所间方差对总方差的贡献。
结论： 诊所层面处方差异超出患者病例组合，突显了在诊所层面提供反馈和抗生素管理的价值。包括插补感染严重程度在内的全面病例组合调整支持更公平的性能比较。
英文摘要
OBJECTIVES: Variation in antibiotic prescribing for common infections between general practices in the UK may be partly explained by differences in case-mix. We aimed to quantify how much of this variation was attributable to differences in prescribing norms between practices after accounting for case-mix.
METHODS: We used the UK Clinical Practice Research Datalink (CPRD) Aurum database to identify general practitioner consultations for 11 common infections. Three-way variance decomposition quantified the proportions of total variance attributable to patient case-mix, between practice variation, and residual unexplained variance across three models (no, minimal (age/sex), and full case mix adjustment). For lower respiratory tract infection and sore throat, external data to impute illness severity were used to estimate the potential effect of unmeasured infection severity.
RESULTS: We identified 3820,806 consultations in 2019. There was clear variability in antibiotic prescribing across practices for most conditions. In fully adjusted models, between-practice variation explained 5.8-32.6% of total variance, exceeding variation attributed to case-mix in 9 out of 11 infections. Acute otitis media and upper respiratory tract infection (URTI), conditions with substantial prescribing variations across practices and high variance attributable to adjusted between-practice differences (12.6% and 10.3%, respectively), are promising candidates for fair prescribing indicators. Compared to no adjustment, full case-mix adjustment lowered the contribution of between-practice differences to total variance, while minimal age-sex adjustment had little impact. Imputing infection severity in addition to full case-mix adjustment further reduced contribution of between-practice variance to the total variance.
CONCLUSIONS: Differences in practice-level prescribing, beyond patient case-mix, highlight the value of providing feedback and antibiotic stewardship at the practice level. Comprehensive case-mix adjustment, including imputed infection severity, supports fairer performance comparisons.