Health care services utilization stratified by virological and immunological markers of HIV: evidence from a universal health care setting
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to determine rates of utilization of in-patient, out-patient and laboratory services stratified by virological and immunological markers of HIV disease among patients on antiretroviral treatment in British Columbia, Canada. METHODS: We estimated resource utilization for in-patient visits, out-patient visits, and laboratory tests among patients initiating antiretroviral treatment between 1 April 1994 and 31 December 2000, with follow-up to 31 March 2001. Resource use was stratified by CD4 cell count and plasma HIV viral load (pVL) at the time of utilization and rates per 100 patient-years were calculated for each health care resource. RESULTS: A total of 2718 patients were included in our analyses. The overall rates of in-patient visits, out-patient visits, and laboratory tests were 902, 3001 and 840 per 100 patient-years, respectively. Utilization was higher for patients with low CD4 cell counts and high pVLs when compared with patients with high CD4 cell counts and low pVLs. CONCLUSIONS: Patients with low CD4 cell counts and high pVLs had the highest use of health care services. Regular follow-up with health care providers in an out-patient setting, allowing for proper monitoring and maintenance of HIV care, is important in minimizing unnecessary and potentially costly in-patient care.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".