Does a clinical guideline change chlamydia testing? Report from the Waikato Chlamydia Project
Bibliographic record
Abstract
BACKGROUND AND CONTEXT: Waikato District Health Board was one of three districts chosen to implement a national chlamydia management guideline, with the aim of optimising testing and treatment. Previous New Zealand studies suggest any test increases associated with such an intervention may be short-lived. ASSESSMENT OF PROBLEM: District-wide chlamydia test volumes were compared for three periods, before (June-Nov 2008), during (June-Nov 2009) and after (June-Nov 2010) guideline implementation by age, gender and ethnicity. Crude estimates of population test uptake were calculated. Azithromycin pharmacy claim volumes were assessed as a measure of treatment. RESULTS: Chlamydia test uptake for women was already high, with 23% of 15- to 24-year-old women tested during the period from June to November 2008. Although tests from under-25-year-olds increased during implementation in 2009, the change was not significant and was not sustained in 2010, p=0.06. Similarly, there were no significant sustained changes by gender or ethnicity following implementation. STRATEGIES FOR IMPROVEMENT: This includes a continued emphasis on optimal chlamydia case finding and treatment by focusing on those at greater risk of infection. Efforts to improve partner notification should be instigated which may in turn better engage men around sexual health. LESSONS: Local data should be used to identify local issues. There is a need to determine whether <25 years is the optimal age threshold for targeted chlamydia testing in New Zealand and to ensure appropriate resources, training and support are in place for primary care nurses who play a pivotal role in sexual health care delivery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".