Assessing DNA rates for new referrals in older adults
Bibliographic record
Abstract
Aims To assess DNA rates for initial assessment medical appointments offered for new referrals within an Older Adults CMHT. To establish any correlation between waiting time and DNA rates. To establish if the initial appointments offered were in keeping with the National guidelines (18 weeks) and our local Trust policy (1-4 weeks). Background In the Uk 15% of adults 60 and above suffer from a mental disorder. Despite the increasing mental health burden, analysis indicate that a quarter of mental health trust received less investment from 2017 to 2018. Financial pressures have also increased appointment waiting time. The NHS has stated that by 2023 there will be a 4-week waiting time for older adult mental health services. Current national guidelines state that initial referrals should be seen within 18 weeks. Method This is a retrospective audit looking at all first time referrals to an Older Adult CMHT in East Birmingham. 110 patients were included in this audit. Factors recorded included age, gender, reason for referral, waiting time for appointment, and whether this complies with guidelines. Electronic patients' notes (RIO) were used for data collection. Result Out of 110 new referrals 11 were not offered any appointments. Out of the remaining 99, 13 cancelled and 8 did not attend. In total, 78 attended the initial appointment offered, out of which 77 were seen within 18 weeks as per national guidelines. 43 patients were seen within the 4-week period (trust policy). 1 patient was offered an appointment at 19 weeks and 3 days from the referral date. The patients who did not attend their appointments were followed up except for one, to find out the reasons of the DNA. This included 2 (physically unwell), 1 (unaware of appointment), 1 (refused), 1 (forgot), 1 (couldn't get to clinic), 1 (asthma attack). Another appointment was offered to those who could attend. Conclusion There was no significant correlation between a longer waiting time and an increased DNA rate for first appointments. Even though the time for an initial appointment was within the NHS guidelines, only 56% of the appointments met our Trust's policy of a 4 week wait. When discussing the results with the relevant team it was clear that a number of factors affected the waiting time including: number of available clinicians and a large catchment area.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".