MétaCan
Menu
Back to cohort
Record W3036027922 · doi:10.1016/j.vaccine.2020.06.003

Assessing the completeness of infant and childhood immunizations within a provincial registry populated by parental reporting: A study using linked databases in Ontario, Canada

2020· article· en· W3036027922 on OpenAlexafffundabout
Sarah E. Wilson, Andrew S. Wilton, Jacqueline Young, Elisa Candido, Andrean Bunko, Sarah A. Buchan, Natasha S. Crowcroft, Shelley L. Deeks, Astrid Guttmann, Scott A. Halperin, Jeffrey C. Kwong, Kumanan Wilson, Karen Tu

Bibliographic record

VenueVaccine · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsNorth York General HospitalOttawa HospitalIzaak Walton Killam Health CentreUniversity Health NetworkUniversity of TorontoDalhousie UniversityPublic Health OntarioHospital for Sick ChildrenInstitute for Clinical Evaluative Sciences
FundersPublic Health OntarioOntario Ministry of Health and Long-Term CareCanadian Institutes of Health ResearchPublic Health Institute
KeywordsMedicinePediatricsFamily medicineDatabaseEnvironmental healthComputer science

Abstract

fetched live from OpenAlex

INTRODUCTION: In Ontario, Canada, parents have the responsibility to report their child's routine infant and childhood vaccines to the provincial immunization registry (the Digital Health Immunization Repository; DHIR) without healthcare provider validation. Despite its use in routine immunization coverage monitoring, no study has previously examined the completeness of immunization data within the DHIR. METHODS: We assessed the completeness of DHIR immunizations, as compared to immunizations within the Electronic Medical Records-Primary Care (EMRPC) database, also known as EMRALD, a network of family physician electronic medical records (EMRs). We linked client records from the DHIR and EMRPC to a centralized population file. To create the study cohort, we examined children born during 2005-2008 and further defined the cohort based on those rostered to an EMRPC physician, visit criteria to ensure ongoing care by an EMRPC provider, and school attendance in Ontario at age 7. We calculated up-to-date (UTD) immunization coverage at age 7 for individual vaccines and overall using data from the DHIR and EMRPC separately, and compared the estimates. RESULTS: The analytic cohort to assess DHIR data completeness included 2,657 children. Overall UTD coverage (all vaccines assessed) was 82.0% in the DHIR and 67.6% in EMRPC. UTD coverage was higher in the DHIR for all vaccines assessed individually, with the exception of meningococcal C conjugate vaccine (difference = 0.3%). After excluding two EMRPC sites with irregularities in immunization data, the difference in overall UTD coverage between systems decreased from 14.4% to 6.6% INTERPRETATION: These results validate the use of DHIR for coverage assessment but also suggest that bidirectional exchange of immunization information has the potential to increase immunization data completeness in both systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.019
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.325
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueVaccineSame topicVaccine Coverage and HesitancyFrench-language works237,207