Primary care satellite clinics and improved access to general and mental health services.
Bibliographic record
Abstract
OBJECTIVES: To evaluate the relationship between the implementation of community-based primary care clinics and improved access to general health care and/or mental health care, in both the general population and among people with disabling mental illness. STUDY SETTING: The 69 new community-based primary care clinics in underserved areas, established by the Department of Veterans Affairs (VA) between the last quarter of FY 1995 and the second quarter of FY 1998, including the 21 new clinics with a specialty mental health care component. DATA SOURCES: VA inpatient and outpatient workload files, 1990 U.S. Census data, and VA Compensation and Pension files were used to determine the proportion of all veterans, and the proportion of disabled veterans, living in each U.S. county who used VA general health care services and VA mental health services before and after these clinics began operation. DESIGN: Analysis of covariance was used to compare changes, from late FY 1995 through early FY 1998, in access to VA services in counties in which new primary care clinics were located, in counties in which clinics that included specialized mental health components were located, and for comparison, in other U.S. counties, adjusting for potentially confounding factors. KEY FINDINGS: Counties in which new clinics were located showed a significant increase from the FY 1995-FY 1998 study dates in the proportion of veterans who used general VA health care services. This increase was almost twice as large as that observed in comparison counties (4.2% vs. 2.5%: F = 12.6, df = 1,3118, p = .0004). However, the introduction of these clinics was not associated with a greater use of specialty VA mental health services in the general veteran population, or of either general health care services or mental health services among veterans who received VA compensation for psychiatric disorders. In contrast, in counties with new clinics that included a mental health component the proportion of veterans who used VA mental health services increased to almost three times the proportion in comparison counties (0.87% vs. 0.31%: F = 8.3, df = 1,3091, p = .004). CONCLUSIONS: Community-based primary care clinics can improve access to general health care services, but a specialty mental health care component appears to be needed to improve access to mental health services.
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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".