Cardiologist Participation in Accountable Care Organizations and Changes in Spending and Quality for Medicare Patients With Cardiovascular Disease
Bibliographic record
Abstract
Background: Despite widespread adoption of Medicare accountable care organizations (ACOs), healthcare spending reductions have been modest. This may relate to variable participation in ACOs by specialist physicians, who disproportionately drive spending. To examine whether specialist participation in Medicare ACOs was associated with changes in healthcare spending and clinical quality, we analyzed national Medicare data. Methods and Results: Working with a 20% random sample of Medicare beneficiaries (2008 to 2015), we identified those with cardiovascular disease. We estimated linear regression models at the beneficiary-quarter level to evaluate changes in healthcare spending and clinical quality after the start of the Shared Savings Program in 2012. We then examined whether changes in spending and quality across ACOs were conditional on cardiologist participation. Our study included ≈1.6 million beneficiaries per year. Although the number of ACOs increased over the study period (from 114 in 2012 to 392 in 2015), the proportion with any cardiologist participation remained stable (from 80% in 2012 to 83% in 2015). Compared with unaligned beneficiaries, those cared for by ACOs without cardiologist participation were associated with a spending reduction (per quarter) of −$75 (95% CI, −$105 to −$46; P <0.001). Care receipt in an ACO with cardiologist participation was associated with an additional difference in spending of −$56 (95% CI, −$87 to −$25; P <0.001), driven by lower spending for skilled nursing facilities, evaluation and management services, procedural care, and testing. While heart failure admission rates were similar among aligned and unaligned beneficiaries, ACO care was associated with fewer all-cause readmissions ( P <0.001) and emergency department visits ( P <0.001). Rates of these outcomes did not vary by cardiologist participation. Conclusions: Annual spending for beneficiaries with cardiovascular disease was ≈$200 lower when cared for by ACOs with cardiologist participation (compared with those without). These spending reductions did not come at the expense of clinical quality.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".