After-hours services in capitation-funded primary care practice: use and satisfaction.
Bibliographic record
Abstract
OBJECTIVE: To examine patients' use of and satisfaction with the nurse-staffed Telephone Health Advisory Service (THAS) and physician after-hours care in a rostered Family Health Organization, as well as physicians' satisfaction with both types of services. DESIGN: Cross-sectional telephone survey. SETTING: A Family Health Organization in Hamilton, Ont. PARTICIPANTS: Nineteen family physicians and their patients who used an after-hours service during 9 selected weeks between March and December of 2007. MAIN OUTCOME MEASURES: Distribution of encounters directed to the on-call physician or to the THAS; types of health problems; and patient and physician satisfaction. RESULTS: A total of 817 calls were recorded from 774 patients. Of these patients, 606 were contacted and 94.4% (572/606) completed encounter-specific surveys: 358 completed the on-call physician survey and 214 completed the THAS survey. Mean age of respondents was 40.8 years; most were women, and approximately one-third called on behalf of children. Most calls (66.8%, 546/817) were made directly to the on-call physicians. The most common problems were respiratory (34.3%, 271/789), gastrointestinal (10.1%, 80/789), and genitourinary (9.3%, 73/789). Most patients reported being very satisfied with the after-hours care provided by the THAS (62.5%, 125/200) or the on-call physicians (70.9%, 249/351). Almost all callers who bypassed the THAS knew about it (89.8%, 316/352), but either felt their problems were too serious or wished to talk to a physician. Most physicians agreed or strongly agreed that they were satisfied with their colleagues' on-call care (81.0%, 17/21); 47.6% (10/21) agreed that the THAS was helpful in managing on-call duty. CONCLUSION: When direct after-hours physician contact is available, a minority of patients uses a nurse-staffed triage. Physicians find the arrangements onerous and would prefer to see after-hours care managed and remunerated differently.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".