An express sexual health service: in and out in a jiffy
Bibliographic record
Abstract
Objectives The aims of the present study were to assess client satisfaction with existing services, gauge the interest in an express service option and to compare waiting times before and after the introduction of an express service. Methods A survey evaluating satisfaction with existing services, waiting times and interest in an express service was offered to all clients attending the Western Sydney Sexual Health Centre in May 2013. A pilot of the express service ran from May to December 2013, and a follow-up survey was conducted in December 2013. Results There was a high level of interest in the express service. Median waiting times and satisfaction with waiting times improved following introduction of the express clinic. A high level of satisfaction was reported in those who had used the express service. Conclusions The express service was well received by clients and has the potential to improve client waiting times, increase clinic capacity and improve the overall client journey through the clinic. What is known about the topic? Express service options for testing for sexually transmitted infections (STIs) are being introduced both in Australia and overseas. Express services have been shown to increase clinic capacity and can create cost savings. They appear to be acceptable to clients. What does this paper add? This paper demonstrates that an express service option can be successfully introduced in an at-risk multicultural population. What are the implications for practitioners? The present study helps show that new models can be successfully introduced into long-standing traditional service models. Such models can help improve efficiency, clinic capacity and may produce cost savings. An express clinic is an option for screening asymptomatic clients for STIs. Clients complete a self-collected history and take self-collected specimens, and clinician-collected blood tests and throat swabs are advised accordingly.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".