Monetary Valuation of Congenital Heart Disease in Indonesia: Economic Modeling Study
Bibliographic record
Abstract
BACKGROUND: Congenital heart disease (CHD) constitutes a significant health and economic burden in low- and middle-income countries, including Indonesia. However, its macroeconomic impact across provinces remains poorly quantified. OBJECTIVE: This study aims to estimate the economic burden associated with premature death and disability due to CHD in Indonesia, with a focus on regional and gender disparities. METHODS: Using data from the Global Burden of Disease 2019 study, we assessed the value of lost welfare (VLW) attributable to CHD across all 34 Indonesian provinces. Economic valuation was conducted using 3 approaches: the US Department of Transportation model, a method based on the Organisation for Economic Co-operation and Development, and a national wage-based estimate. Analyses were stratified by sex and derived from both disability-adjusted life years (DALYs) and years of life lost. We examined disparities using two approaches: (1) gender disparity was measured as the relative difference in VLW between males and females, and (2) geographical disparity was quantified using both location quotients (for raw VLW) and a disparity index (for VLW-to-gross domestic product ratios). RESULTS: The national CHD-related VLW derived from DALYs was estimated at US $16.83 billion (US Department of Transportation), US $11.41 billion (Organisation for Economic Co-operation and Development), and US $9.03 billion (wage-based). West Java recorded the highest provincial VLW (US $1.60 billion), followed by East Java (US $0.83 billion), North Sumatra (US $0.80 billion), and Central Java (US $0.79 billion), indicating a concentration of burden in populous provinces. In contrast, Yogyakarta (US $0.04 billion), North Kalimantan (US $0.04 billion), and West Papua (US $0.06 billion) had the lowest estimates. In several provinces, male-attributed VLW was more than 150% higher than female VLW, with extreme gaps observed in Riau Islands (281.25%), Aceh (166.10%), and Banten (145.86%). These patterns were consistent across both DALY- and years-of-life-lost-based estimates. Based on the location quotients, provinces such as Papua (2.42), West Sulawesi (2.37), Maluku (1.78), East Nusa Tenggara (1.75), and Central Sulawesi (1.66) bore VLW burdens far greater than their population share. The burden was disproportionately high in several eastern provinces, including East Nusa Tenggara (3.35%), Maluku (2.61%), and West Sulawesi (2.66%). CONCLUSIONS: CHD is a macroeconomically manageable burden across most of Indonesia. However, the presence of deep gender disparities and geographically concentrated burdens in eastern and underserved provinces calls for targeted pediatric cardiac health investments.
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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 | 0.000 |
| 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) | 0.000 | 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".