Improving accountability for children's health: Immunization registries and public reporting of coverage in Canada
Bibliographic record
Abstract
Routine childhood immunizations remain one of the most cost-effective preventive health interventions. As such, immunization coverage is a well-established performance measure of the primary care (1) and public health (2) systems. We have called for reporting on the performance of the Canadian public health system, including childhood immunization coverage (3), but this has not yet become universally routine or public. Canada ranks last among reporting Organisation for Economic Co-operation and Development countries for up-to-date pertussis coverage at two years of age (4), and we continue to have outbreaks of vaccine-preventable diseases. The most recent publicly available results are from the 2004 National Immunization Coverage Survey, a telephone household survey conducted by the Public Health Agency of Canada (5). Complete up-to-date coverage is very low: 61% among two-year-old children and 41% among seven-year-old children. Assigning accountability for this poor health system performance and improving coverage is complex. Provision of childhood immunizations across Canada varies both across and within provinces and territories. For example, for routine childhood immunizations, over 90% are given by physicians in Ontario, whereas close to 100% are administered by public health nurses in Alberta, Nunavut, Prince Edward Island and the Northwest Territories. However, even within one jurisdiction, a child might receive immunizations from multiple providers across a number of settings (primary series from a primary care physician, hepatitis B from a public health nurse in school or influenza from a nurse in a public health clinic). The national data, although helpful in drawing a broad picture of overall coverage, cannot be reported at the level responsible for providing immunizations (ie, public health unit or primary care practice) or identify communities of underimmunized populations. Province/territory (P/T) immunization registries, on the other hand, have the potential to serve a number of important functions, including timely reporting of coverage, identifying populations with low coverage, monitoring programs designed to achieve target rates, and generating reminders and recalls, which is shown to be one of the most effective strategies for improving coverage irrespective of the provider (6). A number of countries have achieved population-based immunization registries. The Australian Childhood Immunisation Register (7), operational since 1996, was the first complete national immunization registry. More recently, Great Britain, New Zealand and Denmark have developed registries and have achieved high rates of immunization coverage (8). In the United States, even with its challenges surrounding universal health coverage, 56% of children younger than six years of age are enrolled in a city or state registry (9).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".