Public Policy Health Impact Evaluator

Policy & Method Configuration

Public Policy Domain

Causal Identification Strategy

Demographic Stratification

Policy Implementation Intensity

75%

Intervention Duration (Months)

36 mo

Baseline Target Population

NIH Policy Research Grant Level Surveillance Tracker

Grant Funding & Evaluation Support

100%

Full Research Surveillance Active: High statistical power (95% CI standard error ±1.2%). Longitudinal outcome cohorts tracked without bias.

Primary Health Delta

-14.2%

Maternal Mortality Avoided

Preventable Hospitalizations

-3,840

Cumulative Annual Admissions

QALYs Gained

+8,420

Quality Adjusted Life Years

Disparity Index Attenuation

-18.6%

Gini Equity Gap Narrowed

Causal Longitudinal Health Trajectory

Observed Treated vs Synthetic Counterfactual Baseline (95% CI)

Model: DiD Fixed Effects

Cohort Strata	Sub-Population	Baseline Rate (per 100k)	Post-Policy Rate	Relative Effect	Net Events Averted

Parameter	Coefficient (β)	Std. Error	95% Confidence Interval	p-value

Context: As documented by Nature, federal research funding curtailments for health effects of public policy reduce causal surveillance rigor, prolong policy error detection, and leave vulnerable population harms unobserved.

Evidentiary Metric	Current Grant Capacity	Impairment Status	Scientific Consequence

Canonical Evaluation Brief: Paid Family Leave under DiD causal model (N=1,500,000) achieves -14.2% primary morbidity reduction with 100% research funding surveillance.