Cost-effectiveness of educational outreach to primary care nurses to increase tuberculosis case detection and improve respiratory care: economic evaluation alongside a randomised trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the cost-effectiveness of an educational outreach intervention to improve primary respiratory care by South African nurses. METHODS: Cost-effectiveness analysis alongside a pragmatic cluster randomised controlled trial, with individual patient data. The intervention, the Practical Approach to Lung Health in South Africa (PALSA), comprised educational outreach based on syndromic clinical practice guidelines for tuberculosis, asthma, chronic obstructive pulmonary disease, pneumonia and other respiratory diseases. The study included 1999 patients aged 15 or over with cough or difficult breathing, attending 40 primary care clinics staffed by nurses in the Free State province. They were interviewed at first presentation, and 1856 (93%) were interviewed 3 months later. RESULTS: The intervention increased the tuberculosis case detection rate by 2.2% and increased the proportion of patients appropriately managed (that is, diagnosed with tuberculosis or prescribed an inhaled corticosteroid for asthma or referred with indicators of severe disease) by 10%. It costs the health service $68 more for each extra patient diagnosed with tuberculosis and $15 more for every extra patient appropriately managed. Analyses were most sensitive to assumptions about how long training was effective for and to inclusion of household and tuberculosis treatment costs. CONCLUSION: This educational outreach method was more effective and more costly than usual training in improving tuberculosis, asthma and urgent respiratory care. The extra cost of increasing tuberculosis case detection was comparable to current costs of passive case detection. The syndromic approach increased cost-effectiveness by also improving care of other conditions. This educational intervention was sustainable, reaching thousands of health workers and hundreds of clinics since the trial.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".