Peter Muennig, MD, MPH

I embarked on my career with a mission to evaluate and optimize non-medical social policies to improve health. The cornerstone of my work was cost-effectiveness analysis, a tool that aids policymakers in making strategic decisions to maximize health benefits within a fixed budget. However, I found a gap in our understanding: despite a profusion of correlational studies establishing links between poverty and poor health outcomes, there was a dearth of causal data directly connecting social policies to health outcomes. This was an issue for two reasons: one, correlational studies can be fraught with confounding factors; and two, welfare policies typically offer assistance later in life, while poverty's impacts on health can start in utero, leading to uncertainty about the effectiveness of interventions initiated in adulthood.

Consequently, I pivoted my research focus towards the experimental analysis of welfare policies. While numerous social policy experiments existed, they predominantly examined the policies' impact on economic wellbeing, often overlooking health data. I made it my mission to connect these older experiments with death records. Institutional Review Board (IRB) rules mandating the destruction of identifiers posed a challenge, but I was able to unearth a few datasets with identifiers. In the process, I also managed to connect a prominent social science dataset—The General Social Survey—to mortality records. To my surprise, I found that a wealth of health outcome data from older experiments had been neglected. Collaborating with Emilie Courtin, I performed a systematic meta-analysis of these studies. When the well of these old studies ran dry, I switched gears to focus on ongoing randomized controlled trials, working in close collaboration with MDRC and Mathematica, two entities responsible for evaluating government policies.

This journey revealed some unexpected truths. While I discovered that effective welfare programs do indeed have a positive impact on health, the ironic reality is that only a small number of these programs actually provide effective welfare. They tend to be mired in bureaucracy, creating barriers for the most vulnerable individuals, such as those with large families, those lacking transportation or stable housing, or those with cognitive limitations.

Given these challenges, I've developed a keen interest in enhancing access to these programs. One promising avenue is the adoption of digital identities, which could link individuals to their data and eliminate the need for extensive paperwork or income verification. A case in point is India, a country that, despite its size and level of poverty, has successfully harnessed technology to reach many of its poorest citizens.

I have been published around 200 times, mostly in leading journals in my field (e.g., New England Journal of Medicine, Jama, Health Affairs, The Milbank Quarterly, and The American Journal of Public Health). My work has appeared in virtually every major global newspaper and on a number of television and radio outlets (these include the New York Times, NPR, and CNN).