Change in appropriate referrals to nephrologists after the introduction of automatic reporting of the estimated glomerular filtration rate
Bibliographic record
Abstract
BACKGROUND: Use of the serum creatinine concentration, the most widely used marker of kidney function, has been associated with under-reporting of chronic kidney disease and late referral to nephrologists, especially among women and elderly people. To improve appropriateness of referrals, automatic reporting of the estimated glomerular filtration rate (eGFR) by laboratories was introduced in the province of Ontario, Canada, in March 2006. We hypothesized that such reporting, along with an ad hoc educational component for primary care physicians, would increase the number of appropriate referrals. METHODS: We conducted a population-based before-after study with interrupted time-series analysis at a tertiary care centre. All referrals to nephrologists received at the centre during the year before and the year after automatic reporting of the eGFR was introduced were eligible for inclusion. We used regression analysis with autoregressive errors to evaluate whether such reporting by laboratories, along with ad hoc educational activities for primary care physicians, had an impact on the number and appropriateness of referrals to nephrologists. RESULTS: A total of 2672 patients were included in the study. In the year after automatic reporting began, the number of referrals from primary care physicians increased by 80.6% (95% confidence interval [CI] 74.8% to 86.9%). The number of appropriate referrals increased by 43.2% (95% CI 38.0% to 48.2%). There was no significant change in the proportion of appropriate referrals between the two periods (-2.8%, 95% CI -26.4% to 43.4%). The proportion of elderly and female patients who were referred increased after reporting was introduced. INTERPRETATION: The total number of referrals increased after automatic reporting of the eGFR began, especially among women and elderly people. The number of appropriate referrals also increased, but the proportion of appropriate referrals did not change significantly. Future research should be directed to understanding the reasons for inappropriate referral and to develop novel interventions for improving the referral process.
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".