Health care utilization in medically complex people living with HIV before and after admission to an HIV-specific community facility: a pre–post comparison study
Bibliographic record
Abstract
Background: People living with HIV and multiple comorbidities have high rates of health service use. This study evaluates system usage before and after admission to a community facility focused on HIV care. Methods: We used Ontario administrative health databases to conduct a pre–post comparison of rates and costs of hospital admissions, emergency department visits, and family physician and home care visits among medically complex people with HIV in the year before and after admission to Casey House, an HIV-specific hospital in Toronto, for all individuals admitted between April 2009 and March 2015. Negative binomial regression was used to compare rates of health care utilization. We used Wilcoxon rank sum tests to compare associated health care costs, standardized to 2015 Canadian dollars. To contextualize our findings, we present rates and costs of health service use among Ontario residents living with HIV. Results: During the study period, 268 people living with HIV were admitted to Casey House. Emergency department use declined from 4.6 to 2.5 visits per person-year (p = 0.02) after discharge from Casey House, and hospitalization rates declined from 1.4 to 1.1 admissions per person-year (p = 0.05). Conversely, home care visits increased from 24.3 to 35.6 visits per person-year (p = 0.01) and family physician visits increased from 18.3 to 22.6 visits per person-year (p < 0.001) in the year after discharge. These changes were associated with reduced overall costs to the health care system. The reduction in overall costs was not significant (p = 0.2); however, costs of emergency department visits (p < 0.001) and physician visits (p < 0.001) were significantly less. Interpretation: Health care utilization by people with HIV was significantly different before and after admission to a community hospital focused on HIV care. This has implications for health care in other complex patient populations.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".