Practice Environments and Job Satisfaction in Patient-Centered Medical Homes
Bibliographic record
Abstract
PURPOSE: We undertook a study to evaluate the effects of medical home transformation on job satisfaction in the primary care setting. METHODS: We collected primary data from 20 primary care practices participating in medical home pilot projects in Rhode Island and Colorado from 2009 to 2011. We surveyed clinicians and staff about the quality of their practice environments (eg, office chaos, communication, difficulties in providing safe, high-quality care) and job satisfaction at baseline and 30 months, and about stress, burnout, and intention to leave at 30 months. We interviewed practice leaders about the impact of pilot project participation. We assessed longitudinal changes in the practice environment and job satisfaction and, in the final pilot year, examined cross-sectional associations between the practice environment and job satisfaction, stress, burnout, and intention to leave. RESULTS: Between baseline and 30 months, job satisfaction improved in Rhode Island (P=.03) but not in Colorado. For both pilot projects, reported difficulties in providing safe, high-quality care decreased (P<.001), but emphasis on quality and the level of office chaos did not change significantly. In cross-sectional analyses, fewer difficulties in providing safe, high-quality care and more open communication were associated with greater job satisfaction. Greater office chaos and an emphasis on electronic information were associated with greater stress and burnout. CONCLUSIONS: Medical home transformations that emphasize quality and open communication while minimizing office chaos may offer the best chances of improving job satisfaction.
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 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 | 0.003 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".