Patients' Costs and Cost-Effectiveness of Tuberculosis Treatment in DOTS and Non-DOTS Facilities in Rio de Janeiro, Brazil
Bibliographic record
Abstract
BACKGROUND: Costs of tuberculosis diagnosis and treatment may represent a significant burden for the poor and for the health system in resource-poor countries. OBJECTIVES: The aim of this study was to analyze patients' costs of tuberculosis care and to estimate the incremental cost-effectiveness ratio (ICER) of the directly observed treatment (DOT) strategy per completed treatment in Rio de Janeiro, Brazil. METHODS: We interviewed 218 adult patients with bacteriologically confirmed pulmonary tuberculosis. Information on direct (out-of-pocket expenses) and indirect (hours lost) costs, loss in income and costs with extra help were gathered through a questionnaire. Healthcare system additional costs due to supervision of pill-intake were calculated considering staff salaries. Effectiveness was measured by treatment completion rate. The ICER of DOT compared to self-administered therapy (SAT) was calculated. PRINCIPAL FINDINGS: DOT increased costs during the treatment phase, while SAT increased costs in the pre-diagnostic phase, for both the patient and the health system. Treatment completion rates were 71% in SAT facilities and 79% in DOT facilities. Costs per completed treatment were US$ 194 for patients and U$ 189 for the health system in SAT facilities, compared to US$ 336 and US$ 726 in DOT facilities. The ICER was US$ 6,616 per completed DOT treatment compared to SAT. CONCLUSIONS: Costs incurred by TB patients are high in Rio de Janeiro, especially for those under DOT. The DOT strategy doubles patients' costs and increases by fourfold the health system costs per completed treatment. The additional costs for DOT may be one of the contributing factors to the completion rates below the targeted 85% recommended by WHO.
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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 | 0.001 | 0.001 |
| 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".