Partial and Incremental PCMH Practice Transformation: Implications for Quality and Costs
Bibliographic record
Abstract
OBJECTIVE: To examine the associations between partial and incremental implementation of the Patient Centered Medical Home (PCMH) model and measures of cost and quality of care. DATA SOURCE: We combined validated, self-reported PCMH capabilities data with administrative claims data for a diverse statewide population of 2,432 primary care practices in Michigan. These data were supplemented with contextual data from the Area Resource File. STUDY DESIGN: We measured medical home capabilities in place as of June 2009 and change in medical home capabilities implemented between July 2009 and June 2010. Generalized estimating equations were used to estimate the mean effect of these PCMH measures on total medical costs and quality of care delivered in physician practices between July 2009 and June 2010, while controlling for potential practice, patient cohort, physician organization, and practice environment confounders. PRINCIPAL FINDINGS: Based on the observed relationships for partial implementation, full implementation of the PCMH model is associated with a 3.5 percent higher quality composite score, a 5.1 percent higher preventive composite score, and $26.37 lower per member per month medical costs for adults. Full PCMH implementation is also associated with a 12.2 percent higher preventive composite score, but no reductions in costs for pediatric populations. Incremental improvements in PCMH model implementation yielded similar positive effects on quality of care for both adult and pediatric populations but were not associated with cost savings for either population. CONCLUSIONS: Estimated effects of the PCMH model on quality and cost of care appear to improve with the degree of PCMH implementation achieved and with incremental improvements in implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.036 | 0.163 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".