Offsetting Patient-Centered Medical Homes Investment Costs Through Per-Member-Per-Month or Medicare Merit-based Incentive Payment System Incentive Payments
Bibliographic record
Abstract
Primary care practices become patient-centered medical homes (PCMHs) to improve care. However, investment costs and opportunities to offset those costs are critical to the decision. We examined potential offsets through commercial payer per-member-per-month (PMPM) payments and the Medicare Merit-based Incentive Payment System (MIPS) for a network that spent $4 818 260 over 4 years obtaining and renewing PCMH recognition for 57 practices. With PMPM payments of $3.37 to $8.98, "breakeven" requires that 2.4% to 6.4% of the network's 1645 commercially insured patients per physician be covered, while applying MIPS incentive payments of half the maximum available each year to the network's average 2016 Medicare reimbursement of $196 812 per physician showed they would exceed PCMH costs by 2022.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".