Rigorous policy measurement: causal inference challenges and opportunities

Area of Science:

• Public Health
• Epidemiology
• Health Policy

Background:

• Epidemiologists increasingly evaluate policy impacts on health and disparities using quasi-experimental methods.
• Methodological advancements address inference challenges in observational policy evaluations.
• Measurement and operationalization of policy exposures remain under-addressed in epidemiology.

Purpose of the Study:

• Introduce legal epidemiology methods to epidemiologists for measuring policy exposures.
• Highlight how policy measurement challenges compromise causal inference.
• Emphasize the importance of accurate policy characterization for health and equity research.

Main Methods:

• Describe legal epidemiology's formalized approaches to policy measurement.
• Explain how measurement issues, including information bias and consistency, affect causal inference.
• Utilize epidemiologist-familiar terminology to bridge disciplinary divides.

Main Results:

• Challenges in measuring policy exposures can significantly undermine causal inference in epidemiologic studies.
• Legal epidemiology provides tools to rigorously characterize and measure policy interventions.
• Improved policy measurement can enhance the validity of research on health and equity outcomes.

Conclusions:

• Integrating legal epidemiology can strengthen the rigor of policy evaluation in public health.
• Addressing measurement challenges in policy is crucial for advancing causal inference in epidemiology.
• Accurate measurement of laws and regulations is essential for understanding their impact on population health and structural inequities.