Nurse-led implementation of the single assessment process in primary care: a descriptive feasibility study
Bibliographic record
Abstract
OBJECTIVE: to determine the resources required to carry out the single assessment process in primary care. DESIGN: prospective descriptive study. SETTING: one urban primary care practice, Southampton. PARTICIPANTS: nine hundred and forty-four people aged 70+ years, registered with the practice, not living in a residential/nursing home, or terminally ill. INTERVENTION: participants were sent the six-item Sherbrooke questionnaire (case-finding tool). Non-responders were re-mailed after 4 weeks. All those scoring 4, 5 or 6 and a randomly selected half of those scoring 2 or 3 were offered overview assessment and comprehensive assessment as indicated by the Minimum Data Set for Home Care protocol. The nurse assessor identified unmet needs and agreed an action plan with participants. Another researcher conducted semi-structured interviews with a purposive sample of 26 participants to elicit their views of the process. MAIN OUTCOME MEASURES: response rates/scores of Sherbrooke questionnaire; numbers/characteristics of people requiring overview and comprehensive assessments; nature of resulting recommendations/referrals and impact on other agencies; resources required; views of service users. RESULTS: eight hundred and sixty-three (91%) participants replied. Five hundred and seven (54%) scored 2+, triggering an overview assessment, which was offered to 307. One hundred and twenty-four participants (40%) accepted; 64 (52%) had unmet needs (median 8 each, range 2-18), resulting in 34 referrals within the practice including four case conferences, and 21 to community/secondary health services. Few participants with a Sherbrooke score of 2 required comprehensive assessment. Users perceived the process as acceptable and useful, but not always relevant to their current needs. CONCLUSION: targeting those scoring 3+ on the Sherbrooke questionnaire (28% of sample) may improve the identification of patients who would benefit from further assessment. A contact approach rather than a case-finding one may improve the relevance of this process to older people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".