Laboratory of Healthcare Research and Pharmacoepidemiology, Division of Biostatistics, Epidemiology, and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
Division of Pediatric Infectious Diseases, Department of Women's and Children's Health, University of Padua, Padua, Italy.
JAMA Netw Open. 2024 Sep 3;7(9):e2435127. doi: 10.1001/jamanetworkopen.2024.35127.
Point prevalence surveys (PPSs) are used globally to collect data on antibiotic prescriptions. However, the optimal frequency for data collection to ensure comprehensive understanding of antibiotic use and to target and monitor stewardship interventions remains unknown.
To identify the optimal frequency for collecting data on antibiotic use among the pediatric population through PPSs leveraging administrative data.
DESIGN, SETTING, AND PARTICIPANTS: This prognostic study used a cross-sectional validation approach and was conducted in pediatric outpatient and inpatient settings in the Veneto region of Italy. Antibiotics were classified according to the World Health Organization Access, Watch and Reserve criteria. Prescribing rates of access antibiotics were analyzed for pediatric inpatients with records dated between October 1, 2014, and December 31, 2022, and outpatients with records dated between January 1, 2010, and December 31, 2022. The study included children younger than 15 years with an antibiotic prescription who were admitted to the pediatric acute care unit or evaluated by a primary care pediatrician. Data analysis was performed from October 2023 to January 2024.
An algorithm was developed to identify optimal time frames for conducting PPSs. This approach sought to minimize the discrepancy between quarterly and yearly PPS results, aiming to accurately estimate annual antibiotic prescribing rates in both inpatient and outpatient settings (primary outcome). External validity of the optimal PPS time frames derived from outpatient data when applied to the inpatient setting was also investigated. Validation involved assessing the effectiveness of administrative data in identifying strategic PPS periods for capturing inpatient antibiotic use patterns (secondary outcome).
This analysis included 106 309 children: 3124 were inpatients (1773 males [56.8%]) and 103 185 were outpatients (53 651 males [52.0%]). A total of 5099 and 474 867 antibiotic prescriptions from inpatients and outpatients were analyzed, respectively. Outpatients tended to be older than inpatients, with a median age of 3.2 (IQR, 1.3-6.3) years vs 2.6 (IQR, 0.6-6.6) years, respectively, and with a lower burden of clinical comorbidities (≥1 comorbidity: 6618 [6.4%] vs 1141 [36.5%], respectively). The algorithm successfully identified distinct time frames within the calendar year from inpatient and outpatient records optimized for PPS data collection. Rates obtained from the quarterly PPS during these identified periods exhibited greater agreement with annual antibiotic prescribing rates (inpatient: r = 0.17, P < .001; and outpatient: r = 0.42, P < .001) than those derived from the yearly PPS (inpatient: r = 0.04, P = .58; and outpatient: r = 0.05, P = .34), with a Δ reduction of up to 89.8% (where Δ represents the percentage point change in antibiotic prescribing rates). Furthermore, the optimal PPS time frames gleaned from the outpatient data demonstrated robust applicability to the inpatient setting, yielding comparable results in both scenarios.
This study evaluated the potential of administrative data in determining the optimal timing of PPS implementation. The quarterly PPS balanced precision and sustainability, especially when implemented during strategically selected periods across different seasons. Further studies are needed to validate the algorithm used in this study, especially in post-COVID-19 pandemic years and different settings.
点患病率调查(PPS)在全球范围内用于收集抗生素处方数据。然而,为了确保全面了解抗生素的使用情况,并针对和监测管理干预措施,最佳的数据收集频率仍不清楚。
通过利用行政数据,从儿科人群的 PPS 中确定最佳的抗生素使用数据收集频率。
设计、地点和参与者:本预后研究采用了横断面验证方法,在意大利威尼托地区的儿科门诊和住院环境中进行。抗生素根据世界卫生组织的获取、观察和储备标准进行分类。分析了 2014 年 10 月 1 日至 2022 年 12 月 31 日期间住院患者和 2010 年 1 月 1 日至 2022 年 12 月 31 日期间门诊患者的记录中抗生素的处方率。研究纳入了年龄小于 15 岁、有抗生素处方、入住儿科急症病房或由初级保健儿科医生评估的儿童。数据分析于 2023 年 10 月至 2024 年 1 月进行。
开发了一种算法来确定进行 PPS 的最佳时间框架。这种方法旨在最小化季度和年度 PPS 结果之间的差异,旨在准确估计住院和门诊环境中年度抗生素处方率(主要结果)。还研究了从门诊数据中得出的最佳 PPS 时间框架应用于住院环境时的外部有效性,评估行政数据在确定捕获住院抗生素使用模式的战略 PPS 期间的有效性(次要结果)。
本分析包括 106309 名儿童:3124 名住院患者(1773 名男性[56.8%])和 103185 名门诊患者(53651 名男性[52.0%])。分别分析了 5099 和 474867 份来自住院患者和门诊患者的抗生素处方。门诊患者的年龄中位数大于住院患者,分别为 3.2(IQR,1.3-6.3)岁和 2.6(IQR,0.6-6.6)岁,且临床合并症负担较低(≥1 种合并症:6618[6.4%]与 1141[36.5%])。该算法成功地从住院和门诊记录中确定了年内的不同时间框架,这些时间框架优化了 PPS 数据收集。从这些确定的时间段内的季度 PPS 获得的抗生素处方率与年度抗生素处方率(住院患者:r=0.17,P<0.001;门诊患者:r=0.42,P<0.001)的一致性大于从年度 PPS 获得的处方率(住院患者:r=0.04,P=0.58;门诊患者:r=0.05,P=0.34),抗生素处方率的降低幅度高达 89.8%(其中Δ表示抗生素处方率的百分比变化)。此外,从门诊数据中得出的最佳 PPS 时间框架在住院环境中具有强大的适用性,在两种情况下都产生了可比的结果。
本研究评估了行政数据在确定 PPS 实施最佳时机方面的潜力。季度 PPS 平衡了精确性和可持续性,尤其是在不同季节的战略性选择期间实施时。需要进一步研究来验证本研究中使用的算法,特别是在 COVID-19 大流行后和不同环境中。