ArticleEGEMS (Washington, DC)2019
Comparing Prescribing and Dispensing Data of the PCORnet Common Data Model Within PCORnet Antibiotics and Childhood Growth Study.
Article in EGEMS (Washington, DC), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
12 citing papers in PubMed.
- Partnerships With Health Plans to Link Data From Electronic Health Records to Claims for Research Using PCORnet®.Medical care · 2026Article
- A cross-sectional study of prescribing of antiseizure medication for the treatment of pain in Australia.International journal of clinical pharmacy · 2025Article
- Trends of Antihypertensive Prescription Among US Adults From 2010 to 2019 and Changes Following Treatment Guidelines: Analysis of Multicenter Electronic Health Records.Journal of the American Heart Association · 2024Article
- Avenues for Strengthening PCORnet's Capacity to Advance Patient-Centered Economic Outcomes in Patient-Centered Outcomes Research (PCOR).Medical care · 2023Article
- Global Regulatory and Public Health Initiatives to Advance Pediatric Drug Development for Rare Diseases.Therapeutic innovation & regulatory science · 2022Review
- Effect of Obesity on Risk of Hospitalization, Surgery, and Serious Infection in Biologic-Treated Patients With Inflammatory Bowel Diseases: A CA-IBD Cohort Study.The American journal of gastroenterology · 2022Article
- National Trends in Use of Sodium-Glucose Cotransporter-2 Inhibitors and Glucagon-like Peptide-1 Receptor Agonists by Cardiologists and Other Specialties, 2015 to 2020.Journal of the American Heart Association · 2022Article
- Antibiotics prior to age 2 years have limited association with preschool growth trajectory.International journal of obesity (2005) · 2022Article
- Electronic Health Record Network Research in Infectious Diseases.Clinical therapeutics · 2021Review
- Association of Early Antibiotic Exposure With Childhood Body Mass Index Trajectory Milestones.JAMA network open · 2021Article
- The Patient-Centered Outcomes Research Network Antibiotics and Childhood Growth Study: Implementing Patient Data Linkage.Population health management · 2020Article
- Review of Clinical Research Informatics.Yearbook of medical informatics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Researchers often use prescribing data from electronic health records (EHR) or dispensing data from medication or medical claims to determine medication utilization. However, neither source has complete information on medication use. We compared antibiotic prescribing and dispensing records for 200,395 patients in the National Patient-Centered Clinical Research Network (PCORnet) Antibiotics and Childhood Growth Study. We stratified analyses by delivery system type [closed integrated (cIDS) and non-cIDS]; 90.5 percent and 39.4 percent of prescribing records had matching dispensing records, and 92.7 percent and 64.0 percent of dispensing records had matching prescribing records at cIDS and non-cIDS, respectively. Most of the dispensings without a matching prescription did not have same-day encounters in the EHR, suggesting they were medications given outside the institution providing data, such as those from urgent care or retail clinics. The sensitivity of prescriptions in the EHR, using dispensings as a gold standard, was 99.1 percent and 89.9 percent for cIDS and non-cIDS, respectively. Only 0.7 percent and 6.1 percent of patients at cIDS and non-cIDS, respectively, were classified as false-negative, i.e. entirely unexposed to antibiotics when they in fact had dispensings. These patients were more likely to have a complex chronic condition or asthma. Overall, prescription records worked well to identify exposure to antibiotics. EHR data, such as the data available in PCORnet, is a unique and vital resource for clinical research. Closing data gaps by understanding why prescriptions may not be captured can improve this type of data, making it more robust for observational research.
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Registered trials
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