ArticleBMC infectious diseases2025
Validation of influenza vaccination status using health administrative databases by integrating pharmacy claims and medical billing databases in Ontario, Canada.
Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundDetermining vaccination status among the population is key for vaccine research and surveillance. This study aimed to validate the combined use of Ontario Health Insurance Program (OHIP) physician billing claims and Ontario Drug Benefit program (ODB) pharmacist billing claims against data from the Canadian Community Health Survey (CCHS).
methodsOHIP and ODB billing claims databases were linked to 2013-2014 CCHS data, which contain self-reported seasonal influenza vaccination status of respondents (the reference standard). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), and their associated 95% confidence intervals (CIs) were estimated. Subgroup analyses were performed based on key respondent characteristics, including having a regular medical doctor and the presence of risk factors for influenza complications.
resultsThere were 31,390 eligible CCHS respondents aged ≥ 12 years in Ontario who responded to the influenza vaccination questions and agreed to have their responses linked to health administrative databases. More than half (55%) were female, 29% were aged ≥ 65 years, 93% had a regular medical doctor, and 54% had one or more risk factors for influenza complications. The sensitivity for the combined administrative databases was 60.1% (95% CI, 59.3%-61.0%), specificity was 98.5% (95% CI, 98.3%-98.7%), PPV was 96.7% (95% CI, 96.3%-97.1%), and NPV was 76.9% (95% CI, 76.4%-77.5%). Sensitivity was higher among those aged ≥ 65 years (72.7%; 95% CI, 71.6%-73.7%), with a regular medical doctor (61.1%; 95% CI, 60.3%-62.0%), and those with at least one risk factor for influenza complications (65.8%; 95% CI, 64.9%-66.8%).
conclusionCombining administrative physician and pharmacy claims data in Ontario results in moderate sensitivity but very high specificity and PPV, demonstrating that they can be a valid measure of influenza vaccination status.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.