Health policies can be more effective if we know who benefits the most. A new method called causal machine learning helps us understand this better. In Indonesia, mothers with contributory health insurance use healthcare more and have lower infant mortality rates. Subsidised insurance, however, doesn't show significant benefits. The contributory scheme helps disadvantaged mothers the most, while the subsidised scheme doesn't show any specific benefits for vulnerable populations. This new method helps policymakers design better health programmes.