Association of Cardiology Billing Amounts With Health Care Utilization and Clinical Outcomes in Patients With Atrial Fibrillation
Bibliographic record
Abstract
Background The relationship between health care utilization and outcomes in patients with atrial fibrillation is unknown. The objective of this study was to investigate whether cardiologists' billing amounts in a fee-for-service environment are associated with better patient-level clinical outcomes. Methods and Results A retrospective cohort study was conducted using administrative claims data of cardiologists in Ontario, Canada between April 1, 2011 and March 31, 2016. The cardiologists were stratified into quintiles based on their median billing patterns per patient over the observation period. The primary outcomes were patient-level receipt of repeat visits, cardiac diagnostic tests, and medications ≤1 year of index date. The secondary clinical outcomes were death, emergency department visits, and all-cause hospitalization 1-year post-index visit. The patient cohort comprised 182 572 patients with atrial fibrillation (median age 74 years, 58% male) from 467 cardiologists. Patients with atrial fibrillation seen by higher-billing cardiologists were 26% more likely to have an echocardiogram (adjusted odds ratio [aOR], 1.26 [95% CI, 1.10-1.43] for quintile 5 versus 2), 28% a stress test (aOR, 1.28 [1.12-1.46] for quintile 5 versus 2), 25% continuous electrocardiographic monitoring (aOR, 1.25 [1.08-1.46] for quintile 4 versus 2), and 79% more likely to get a stress echocardiogram (aOR, 1.79 [1.32-2.42] for quintile 5 versus 2). They also had a higher rate of all-cause hospitalization (aOR, 1.13 [1.07-1.20]). Mortality rates were similar across cardiologists billing quintiles (eg, aOR, 0.98 [0.87-1.11] for quintile 4 versus 2). Conclusions Higher-billing cardiologists ordered more diagnostic tests per patient with atrial fibrillation but these are not associated with improvements in outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".