P040 How COVID reduced inequities of sexual health in a rural health board
Bibliographic record
Abstract
Introduction When the Covid pandemic arrived, the Sexual Health service in Hywel Dda had to adapt and change dramatically and rapidly. Prior to Covid the service ran walk in clinics, whereby patients would arrive and wait to be seen for their sexual health needs. During Covid, the service used technology to change the way patients accessed the service. The use of video and telephone consultations increased, and were used as the first point of contact, after the patient had phoned the central phone line. Medications were posted out using registered postal services, and this included abortion medications. Only patients that required to be examined were seen face to face. Methods Data was collected from the year preceding Covid [2019] and compared with data from 2021. This looked at how patients accessed services and the numbers of patients that accessed the service in those periods of time. Results In 2019 96% of patients were seen face to face in walk in clinics, and the service had 23 000 attendances In 2021, 46% of patients were seen face to face and 54% of patients either had a telephone or video consultation. The service had 25 000 attendances in 2021 Approx 3 000 packages of medications were also posted out during 2021, whilst none was sent in 2019. These included approx 900–1000 abortion medication packs. Discussion Hywel Dda University Health Board covers 3 counties of rural South West Wales: Pembrokeshire, Carmarthenshire and Ceredigion. These 3 counties cover a quarter of the land area of Wales and has a population of 384 000. To access clinics patients would have to travel large distances to access sexual health services. When the Covid pandemic arrived and the use of technology increased, meant that patients could access services remotely and this has reduced inequities in access to residents of Hywel Dda
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 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".