Evaluating the impact of the nationwide public–private mix (PPM) program for tuberculosis under National Health Insurance in South Korea: A difference in differences analysis
Bibliographic record
Abstract
Public-private mix (PPM) programs on tuberculosis (TB) have a critical role in engaging and integrating the private sector into the national TB control efforts in order to meet the End TB Strategy targets. South Korea's PPM program can provide important insights on the long-term impact and policy gaps in the development and expansion of PPM as a nationwide program.Healthcare is privatized in South Korea, and a majority (80.3% in 2009) of TB patients sought care in the private sector. Since 2009, South Korea has rapidly expanded its PPM program coverage under the National Health Insurance (NHI) scheme as a formal national program with dedicated PPM nurses managing TB patients in both the private and public sectors. Using the difference in differences (DID) analytic framework, we compared relative changes in TB treatment outcomes-treatment success (TS) and loss to follow-up (LTFU)-in the private and public sector between the 2009 and 2014 TB patient cohorts. Propensity score matching (PSM) using the kernel method was done to adjust for imbalances in the covariates between the 2 population cohorts. The 2009 cohort included 6,195 (63.0% male, 37.0% female; mean age: 42.1) and 27,396 (56.1% male, 43.9% female; mean age: 45.7) TB patients in the public and private sectors, respectively. The 2014 cohort included 2,803 (63.2% male, 36.8% female; mean age: 50.1) and 29,988 (56.5% male, 43.5% female; mean age: 54.7) patients. In both the private and public sectors, the proportion of patients with transfer history decreased (public: 23.8% to 21.7% and private: 20.8% to 17.6%), and bacteriological confirmed disease increased (public: 48.9% to 62.3% and private: 48.8% to 58.1%) in 2014 compared to 2009. After expanding nationwide PPM, absolute TS rates improved by 9.10% (87.5% to 93.4%) and by 13.6% (from 70.3% to 83.9%) in the public and private sectors. Relative to the public, the private saw 4.1% (95% confidence interval [CI] 2.9% to 5.3%, p-value < 0.001) and -8.7% (95% CI -9.7% to -7.7%, p-value <0.001) higher rates of improvement in TS and reduction in LTFU. Treatment outcomes did not improve in patients who experienced at least 1 transfer during their TB treatment. Study limitations include non-longitudinal nature of our original dataset, inability to assess the regional disparities, and verify PPM program's impact on TB mortality.We found that the nationwide scale-up of the PPM program was associated with improvements in TB treatment outcomes in the private sector in South Korea. Centralized financial governance and regulatory mechanisms were integral in facilitating the integration of highly diverse South Korean private sector into the national TB control program and scaling up of the PPM intervention nationwide. However, TB care gaps continued to exist for patients who transferred at least once during their treatment. These programmatic gaps may be improved through reducing administrative hurdles and making programmatic amendments that can help facilitate management TB patients between institutions and healthcare sectors, as well as across administrative regions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".