ArticleJAMA network open2024
Validation of Administrative Data and Timing of Point Prevalence Surveys for Antibiotic Monitoring.
Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pediatric stewardship in Italy: a necessity, not an option - a National Multi-Society Expert Consensus on Antimicrobial and Diagnostic Stewardship (SIP, SITIP, SIMRI, SIAIP, SIMEUP, SIPPS, SICUPP, SIMIT, SIMPE, SIPINF, SIT, SIAATIP, SARNEPI, AIEOP, SIM, SITI, SIF, SIFACT, SITA, SIN).Italian journal of pediatrics · 2025Pooled it
- Interpreting point prevalence survey data on antibiotic use: guidance for facility antimicrobial stewardship teams and national policymakers.JAC-antimicrobial resistance · 2026Review
- Pre-treatment pathogen testing rates before antimicrobial therapy in emergency departments: a four-year retrospective study from two hospital campuses.Frontiers in cellular and infection microbiology · 2026Article
- Antibiotic stewardship and point-of-care testing for children in 25 low-income and lower-middle-income countries: a systematic review and meta-analysis.EClinicalMedicine · 2025Article
- State of the Art of Antimicrobial and Diagnostic Stewardship in Pediatric Setting.Antibiotics (Basel, Switzerland) · 2025Review
- Antimicrobial Stewardship Programs in Pediatric Intensive Care Units: A Systematic Scoping Review.Antibiotics (Basel, Switzerland) · 2025Review
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: 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. Objective: 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. Main Outcomes and Measures: 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). Results: 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. Conclusions and Relevance: 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.
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