Time on wait lists for coronary bypass surgery in British Columbia, Canada, 1991 – 2000
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In British Columbia, Canada, all necessary medical services are funded publicly. Concerned with growing wait lists in the mid-1990s, the provincial government started providing extra funding for coronary artery bypass grafting (CABG) operations annually. Although aimed at improving access, it is not known whether supplementary funding changed the time that patients spent on wait lists for CABG. We sought to determine whether the period of registration on wait lists had an effect on time to isolated CABG and whether the period effect was similar across priority groups. METHODS: Using records from a population-based registry, we studied the wait-list time before and after supplementary funding became available. We compared the number of weeks from registration to surgery for equal proportions of patients in synthetic cohorts defined by five registration periods in the 1990s. RESULTS: Overall, 9,231 patients spent a total of 137,126 person-weeks on the wait lists. The time to surgery increased by the middle of the decade, and decreased toward the end of the decade. Relative to the 1991-92 registration period, the conditional weekly probabilities of undergoing surgery were 30% lower among patients registered on the wait lists in 1995-96, hazard ratio (HR) = 0.70 (0.65-0.76), and 23% lower in 1997-98 patients, HR = 0.77 (0.71-0.83), while there were no differences with 1999-2000 patients, HR = 0.94 (0.88-1.02), after adjusting for priority group at registration, comorbidity, age and sex. We found that the effect of registration period was different across priority groups. CONCLUSION: Our results provide evidence that time to CABG shortened after supplementary funding was provided on an annual basis to tertiary care hospitals within a single publicly funded health system. One plausible explanation is that these hospitals had capacity to increase the number of operations. At the same time, the effect was not uniform across priority groups indicating that changes in clinical practice should be considered when adding extra funding to reduce wait lists.
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.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it