Bibliographic record
Abstract
We aimed to identify “high-cost” patients with HIV (PWH) and determine drivers behind higher costs. All PWH at the Southern Alberta HIV Clinic, Canada, and active in 2017 were included. Sociodemographic, clinical, and healthcare utilization data were collected. The direct care costs from the payers’ perspective including antiretroviral drugs (ARV), outpatient visits, and hospital admissions were determined for 2017. Patients’ annual total costs were grouped into top 5% (i.e., high-cost), top 20%, middle 60%, and bottom 20%. High-cost patients were older, Caucasian or indigenous Canadian, and more likely acquired HIV from intravenous drug use (all p < 0.05). High-cost patients had lower nadir CD4, more comorbidities, missed more clinic appointments, had more ARV interruptions, and developed more ARV resistance ( p < 0.01). The overall median cost of HIV care was US$14,064 [IQR US$13,121–US$17,883] (2017 Cdn$). High-cost patients had a median cost of US$29,902 [IQR US$27,229–US$37,891] and accounted for 14% of total costs and 84% of all inpatient costs. Hospitalizations constituted 58% of costs for high-cost patients. Although heterogeneous, high-cost patients have distinct sociodemographic and clinical characteristics driving their healthcare utilization. Addressing these social determinants of health and using novel ARV administration approaches may preserve health and save costs.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".