A couple weeks ago I took a great 2-day stats course on evaluating treatment effects using observational data that was offered by Statistical Horizons and taught by Dr. Stephen Vaisey, Professor of Sociology at Duke. Terrific stuff. Learned key concepts about new and better ways to do such analyses. One gem that my colleague, Tim Hediger, recommended and which resonated with the theme of the course was this YouTube video by Dr. Gary King at Harvard click here. It clearly lays out why, despite its buzz … propensity score matching is NOT the best way to match observational data prior to analyzing treatment effects.
Fellow geeks, enjoy!
A close 5-4 Supreme Court decision has upheld the constitutionality of the Patient Protection and Affordable Care Act, America’s sweeping health reform law. Some vow to continue to work toward its repeal. For now, however, it seems that a tenuous stability as far as federal health policy is concerned may be emerging. If so, such stability could help our country get on with the hard and complicated work of the R&D on system improvement we need in health care.
Regardless of one’s political orientation, challenging facts about the U.S. health care system remain; it simultaneously develops the most advanced, innovative, treatments in the world, fails to provide all of its citizens with basic health services, is phenomenally expensive, fragmented, and poorly designed to address the needs of an aging, chronically ill population (the latter being an attribute we share with health systems worldwide). There are no easy fixes for our system, but there is great potential in undertaking serious, sustained, well-supported and thoughtfully conducted experiments to learn how we can improve – at the level of system design.
Yet to conduct these kinds of large-scale, long term trials requires a fundamental commitment for doing so; a constancy to purpose born from a widely shared belief that our best chance for improvement is through knowledge. On this Independence Day, may we all agree to undertake the hard work needed to be free, strong, vibrant, and healthy.