Patient-centered Medical Homes and Access to Services for New Primary Care Patients
Bibliographic record
Abstract
BACKGROUND: Recent efforts to revitalize primary care have centered on the patient-centered medical home (PCMH). Although enhanced access is an integral component of the PCMH model, the effect of PCMHs on access to primary care services is understudied. OBJECTIVE: To determine whether PCMH practices are associated with better access to new appointments for nonelderly adults by direct measurement. RESEARCH DESIGN: We estimated the relationship between practice PCMH status and access to care in multivariate regression models, adjusting for a robust set of patient, practice, and geographic characteristics; using data on 11,347 simulated patient calls to 7266 primary care practices across 10 US states merged with data on PCMH practices. PARTICIPANTS: Trained field staff posing as patients (age younger than 65 y) seeking a new primary care appointment with varying insurance status (private, Medicaid, or self-pay). MEASURES: Our primary predictor was practice PCMH status and our primary outcome was the ability of simulated patients to schedule a new appointment. Secondary outcomes included the number of days to that appointment; availability of after-hour appointments; and an appointment with an ongoing primary care provider. RESULTS: Of the 7266 practices contacted for an appointment, 397 (5.5%) were National Committee for Quality Assurance-recognized PCMHs. In adjusted analyses, callers to PCMH practices compared with non-PCMH practices were more likely to schedule a new appointment (adjusted odds ratio=1.26 (95% CI, 1.01-1.58); P=0.04] and be offered after-hour appointments [adjusted odds ratio=1.36 (95% CI, 1.04-1.75); P=0.02]. DISCUSSION: PCMH practices maybe associated with better access to new primary care appointments for nonelderly adults, those most likely to gain insurance under the Affordable Care Act.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".