A population-based study comparing patterns of care delivery on the quality of care for persons living with HIV in Ontario
Bibliographic record
Abstract
OBJECTIVES: Physician specialty is often positively associated with disease-specific outcomes and negatively associated with primary care outcomes for people with chronic conditions. People with HIV have increasing comorbidity arising from antiretroviral therapy (ART) related longevity, making HIV a useful condition to examine shared care models. We used a previously described, theoretically developed shared care framework to assess the impact of care delivery on the quality of care provided. DESIGN: Retrospective population-based observational study from 1 April 2009 to 31 March 2012. PARTICIPANTS: 13 480 patients with HIV and receiving publicly funded healthcare in Ontario were assigned to one of five patterns of care. OUTCOME MEASURES: Cancer screening, ART prescribing and healthcare utilisation across models using adjusted multivariable hierarchical logistic regression analyses. RESULTS: Models in which patients had an assigned family physician had higher odds of cancer screening than those in exclusively specialist care (colorectal cancer screening, exclusively primary care adjusted OR (AOR)=3.12, 95% CI (1.90 to 5.13), family physician-dominant co-management AOR=3.39, 95% CI (1.94 to 5.93), specialist-dominant co-management AOR=2.01, 95% CI (1.23 to 3.26)). The odds of having one emergency department visit did not differ among models, although the odds of hospitalisation and HIV-specific hospitalisation were lower among patients who saw exclusively family physicians (AOR=0.23, 95% CI (0.14 to 0.35) and AOR=0.15, 95% CI (0.12 to 0.21)). The odds of antiretroviral prescriptions were lower among models in which patients' HIV care was provided predominantly by family physicians (exclusively primary care AOR=0.15, 95% CI (0.12 to 0.21), family physician-dominant co-management AOR=0.45, 95% CI (0.32 to 0.64)). CONCLUSIONS: How care is provided had a potentially important influence on the quality of care delivered. Our key limitation is potential confounding due to the absence of HIV stage measures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".