{"id":34353,"date":"2026-03-10T12:53:01","date_gmt":"2026-03-10T19:53:01","guid":{"rendered":"https:\/\/sop.washington.edu\/?p=34353"},"modified":"2026-03-10T15:30:20","modified_gmt":"2026-03-10T22:30:20","slug":"evidence%e2%80%91informed-policy-for-better-population-health-outcomes","status":"publish","type":"post","link":"https:\/\/staff.washington.edu\/twentzel\/wordpress\/evidence%e2%80%91informed-policy-for-better-population-health-outcomes\/","title":{"rendered":"Evidence\u2011Informed Policy for Better Population Health Outcomes"},"content":{"rendered":"

CHOICE Institute Assistant Professor, Dr. No\u00e9mi Kreif<\/a> was invited to deliver a keynote lecture in December 2025 at Corvinus University of Budapest<\/a> – her alma mater – at a conference marking the 30th anniversary of the prestigious John von Neumann Award in economics. Funded by the Rajk College for Advanced Studies, a student organization of which No\u00e9mi was also a member, the prize celebrates outstanding contributions to economic thought. Drawing on the work of past awardees including Kenneth Arrow and John Harsanyi, her talk introduced an economics and business audience to health economics and highlighted how it can inform the design of more efficient and equitable health care systems.<\/p>\n

\"A
Dr. Kreif presenting at Corvinus University in December 2025 <\/figcaption><\/figure>\n

What Modern Health Economics Brings to Public Health<\/strong><\/h4>\n

Kreif introduced the audience to health economics as a practical decision science, not an abstract field. She highlighted the realities that make healthcare uniquely challenging: outcomes are uncertain, patients and providers have very different information, and society demands much higher ethical standards in healthcare than in typical markets. These conditions mean that health systems must rely on carefully designed public policies\u2014not just market forces\u2014to deliver fair and effective care.<\/p>\n

Importantly, Kreif emphasized that health economics provides tools to answer real\u2011world questions, such as which treatments to fund, how to measure their impact, and how to ensure that the benefits reach those most in need.<\/p>\n

Four Evidence\u2011Based Principles for Better Health Policy<\/strong><\/h4>\n
1. Measure what actually matters for people\u2019s lives.<\/em><\/h5>\n

Good policy requires accounting for both survival and quality of life, especially when evaluating expensive treatments like new cancer therapies. Without measuring wellbeing alongside longevity, health systems risk paying a lot for small gains.<\/p>\n

2. Look beyond averages\u2014equity depends on it.<\/em><\/h5>\n

The same intervention can have very different effects across communities. Life expectancy gaps of 15 years in the U.S. and 12 years within Hungary demonstrate that average results hide urgent needs. Policies must be assessed for who benefits and who is left out.<\/p>\n

3. Remove small barriers that have big consequences.<\/em><\/h5>\n

Seemingly minor obstacles\u2014like travel time, bus fare, or a small co\u2011pay\u2014can prevent people from getting preventive care or vaccinations. Evidence from India shows that even simple in\u2011kind incentives can dramatically increase participation, while minimal fees reduce it. These findings underscore that access is shaped by friction, not just availability.<\/p>\n

4. Use analytics to target what works, for whom.<\/em><\/h5>\n

Machine learning and modern causal methods can help identify which policies are most effective for which groups, enabling smarter resource allocation. Instead of \u201cone\u2011size\u2011fits\u2011all,\u201d health systems can tailor policies to maximize impact and close gaps.<\/p>\n

Why This Matters Now<\/strong><\/h4>\n

Corvinus University\u2019s conference summary highlighted a key theme: the growing need for truly data\u2011driven decisions in public policy, especially as health systems confront rising costs, demographic shifts, and inequities. Kreif\u2019s work provides a roadmap for how to do this responsibly and effectively.<\/p>\n

Her message is that evidence is only powerful if we design systems that act on it. And acting on it means:<\/p>\n