On The Record (with daily recap)

  • IOM: The Healthcare Imperative: Lowering Costs and Improving Outcomes
  • IOM: The Learning Health System and its Innovation Collaboratives
  • IOM: Geographic Adjustment in Medicare Payment, Phase 1
  • CBO: Some Context for Thinking About Deficit Reduction: Implications for Future Budget Policy


Today in TIE: Reflex, Austin on if you aren’t worried now, think about 2030, and the weekly reading list, Kevin on ACOs as a way around Sherman Anti-Trust and Boston Globe does good job covering proposals to raise the Medicare age, Don on hospital-insurer integration.

Podcast: How health services research is funded.

About Don Taylor
Professor of Public Policy at Duke University (with appointments in Business, Nursing, Community and Family Medicine, and the Duke Clinical Research Institute). I am one of the founding faculty of the Margolis Center for Health Policy, and currently serve as Chair of Duke's University Priorities Committee (UPC). My research focuses on improving care for persons who are dying, and I am co-PI of a CMMI award in Community Based Palliative Care. I teach both undergrads and grad students at Duke. On twitter @donaldhtaylorjr

One Response to On The Record (with daily recap)

  1. JayB says:

    Message for the IOM and fellow travelers, courtesy of Arnold Kling:

    “When a remote authority sets incentives, people respond by manipulating the system. This fact is poorly understood by education reformers who are fond of pay-for-performance and national standards, by health care reformers who are fond of paying for quality, and by financial regulators.”

    The entire report is predicated on the notion that variations in numerical associations between high-level statistical aggregates gathered in region A and region B represent inefficiencies that can be eliminated by centralized bureaucratic processes.

    Are there any examples of cases where administrators and clinicians have actually used these data sets to simultaneously eliminate a regional cost variation and improve an outcome?

    Presumably insurers that cover a broad geographic area have both the means and the motive to identify the places where the cost of care is high and the outcomes are no better. If this is the sort of low hanging fruit that Orzag et al claim it to be, why haven’t the likes of UHC used this statistical arsenal to enhance their profits, undercut their competitors, or both?

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