Laboratory medicine: The exemplar for value-based healthcare
Bibliographic record
Abstract
Value-Based Healthcare (VBHC) aims to improve the overall quality, safety, and sustainability of healthcare while reducing delivery costs of more effective care. Despite advantages associated with VBHC transformation, the road to its adoption has been lengthy. Laboratory Medicine (LM) is in a prime position to lead the transition to VBHC because of its key role in diagnosis and treatment of patients. Laboratory medicine results inform/influence 50% to 70% of all clinical decisions. This article summarizes some issues associated with adoption of VBHC and related healthcare innovations and suggests potential approaches using LM-specific examples to help accelerate adoption. Laboratory medicine is both a useful model for VBHC implementation and facilitator for related innovation adoption by helping to target patient populations that would benefit most from specific interventions. The critical value of rapidly adopted diagnostic technologies used during the COVID-19 pandemic and economic recovery provide important insights about the need to embrace and accelerate VBHC implementation.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".