Monitoring the evolutionary process of quality: Risk-adjusted charting to track outcomes in intensive care
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To present graphical procedures for prospectively monitoring outcomes in the intensive care unit. DESIGN: Observational study: risk-adjusted control chart analysis of a case series. SETTING: Tertiary referral adult intensive care unit: Princess Alexandra Hospital, Brisbane, Australia. PATIENTS: A total of 3398 intensive care unit admissions from January 1, 1995, to January 1, 1998. CONCLUSIONS: Risk-adjusted process control charting procedures for continuous monitoring of intensive care unit outcomes are proposed as quality management tools. A modified Shewhart p chart and cumulative sum process control chart, using the Acute Physiology and Chronic Health Evaluation III model mortality prediction for risk adjustment, are presented. The risk-adjusted p chart summarizes performance at arbitrary intervals and plots observed against predicted mortality rate to detect large changes in risk-adjusted mortality. The risk-adjusted cumulative sum procedure is a likelihood-based scoring method that adjusts for estimated risk of death, accumulating evidence from outcomes of all previous patients. It formally tests the hypothesis of a change in the odds of death. In this application, we detected a decrease from above to predicted risk-adjusted mortality. This was temporally related to increased senior staffing levels and enhanced ongoing multidisciplinary review of practice, quality improvement, and educational activities. Formulas and analyses are provided as appendices.
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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 | 0.001 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it