Health system financing is the process by which revenues are generated and pooled to pay for health services. Revenue generation determines where money comes from — taxes, insurance premiums, out-of-pocket payments, or external aid. Risk pooling determines how those funds are aggregated so that the financial risk of healthcare costs is shared across a population rather than borne by individuals at the moment of illness. The choice of financing mechanism fundamentally shapes who has access to care, how much financial protection people receive, and what incentives providers face.
Found that higher cost-sharing significantly reduced overall healthcare utilization (Efficiency) but had little to no significant impact on objective Health Status for the average adult, demonstrating the price elasticity of health behavior.
Singapore achieved low health expenditure (3–4% of GDP) with strong health outcomes, but the system depends critically on complementary catastrophic insurance (MediShield) and a government safety net (Medifund). MSAs alone cannot handle rare catastrophic events. The system also benefits from heavy government involvement in hospital supply and pricing — MSAs operate within a tightly regulated environment, not a free market.
The consensus price elasticity of cigarette demand is approximately -0.4 in high-income countries and -0.4 to -0.8 in low- and middle-income countries. A 10% price increase reduces consumption by 4–8%. Youth and low-income populations are most price-responsive. Industry documents confirmed that companies viewed tax increases as the greatest threat to consumption.
Demonstrated that a single-payer model could achieve universal coverage (Access) and high Financial Risk Protection while maintaining remarkably low administrative costs (Efficiency) below 2% of total health expenditures.
Catastrophic payment rates varied widely across countries. Three preconditions were identified: (1) availability of health services requiring payment, (2) low capacity to pay, and (3) absence of prepayment or insurance mechanisms. Countries relying on out-of-pocket financing had the highest incidence.
Children in treatment households experienced approximately a 23% reduction in the incidence of illness, an 18% reduction in anemia, and a 1–4% increase in height. Preventive health care visits increased by more than half.
CBHI schemes modestly reduced out-of-pocket spending and increased utilization of health services among members, but enrollment remained low (typically under 10% of target populations) and schemes suffered from adverse selection. Financial sustainability was fragile — most schemes required external subsidies to remain solvent. Evidence of impact on health outcomes was minimal.
Intention-to-treat estimates showed a 23% reduction in catastrophic expenditures (1.9 percentage points). Effects were stronger among poor households (3.0 pp reduction) and experimental compliers (6.5 pp reduction, a 59% decrease). No significant effects on health outcomes or utilization over the short follow-up period.
SHI adoption was associated with increased health expenditure but no significant improvement in health outcomes. Out-of-pocket spending as a share of total health expenditure did not decline, and in some specifications increased. SHI did not achieve the anticipated improvements in financial protection or equity.
Each dollar of DAH displaced approximately $0.43-$1.14 of domestic government health spending in Sub-Saharan Africa, depending on the specification. Governments reduced their own health allocations when external aid increased, partially offsetting the intended funding boost. The fungibility of aid was highest in countries with weak governance.
Winning the lottery completely eliminated catastrophic out-of-pocket medical expenditures (Risk Protection) and increased healthcare utilization (Access), but did not generate statistically significant improvements in measured physical Health Status over the first two years.
Under-5 mortality showed a dose-response relationship with BFP coverage: approximately 17%, 32%, and 53% reductions at intermediate, high, and consolidated coverage levels respectively. Effects were strongest for poverty-related causes (malnutrition and diarrhea).
Improved risk adjustment reduced favorable selection into MA plans by 15–20%. However, plans responded to the new formula by intensifying diagnostic coding — upcoding increased, with MA enrollees showing 6–16% higher risk scores than comparable fee-for-service beneficiaries, representing billions in excess payments.