Decision-based Evidence Making Mark D. Smith, MD MBA National Health Policy Conference Washington, DC February 7 th, 2006.

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Presentation transcript:

Decision-based Evidence Making Mark D. Smith, MD MBA National Health Policy Conference Washington, DC February 7 th, 2006

Translating Research Into Practice Conference Washington, DC July 24 th, 2003 Mark Smith, MD, MBA The California HealthCare Foundation TRIP Funding Priorities, or: An odd analogy from the provinces

2004 Annual Budget, in Millions Translating Research Into Practice Conference Federal funding of basic and clinical science swamps HSR

An odd analogy ` 2003 payroll: $50 million 2003 payroll: $150 million Dollars spent per win, A’s: $446,000 Yankees: $1,396,000 ratio: 1 / 3.13 Sources: MLB.com and USA Today baseball salary database Translating Research Into Practice Conference

The secrets of the As’ success Fast Cheap Fanatically devoted to practical R & D Cunning Translating Research Into Practice Conference

The A’s v. HSR Fast Cheap Practical R&D Cunning Sloooowwwwww Expensive Uncontaminated experiments Field of Dreams A’s successIncentives to HS Researchers Translating Research Into Practice Conference

Ford makes … Cars

The health care system makes … Visits

Tenure Health Services Research makes …

What do we need more of ? Meaningful definitions when framing research questions Quick turnaround Research questions driven more by operational stakeholders’ priorities Expertise in the management sciences as applied to health care Permanent research infrastructure Translating Research Into Practice Conference

What drives selection of research topics and methods? Money Researcher interest and skills Researcher incentives Data availability Potential for publication of findings.

Problematic Researcher Attitudes Modeled on biochemical research – researchers’ muse Observational Arrogance towards delivery system –town/gown ; “LMD” –“only 65% of patients got …”

Typical Research Incentives Big Long Expensive Dedicated staff –Neutron bomb – nothing left of value to the clinical enterprise Are for projects to be:

What data on patients are available? Age Sex “Race” Income proxies (e.g. zipcode) Co-morbid conditions … Etc.

What patient attributes are meaningful? Risk aversion Where on diffusion curve Assertiveness

What clinician attributes are meaningful? Risk aversion Where on diffusion curve Income elasticity

Research topics: ask the users Medical Directors Chiefs of staff Department Chairs Benefits purchasers State/local legislators and regulators Clinicians

The Role of Health care IT IT: the new silver bullet?

The current state of health care IT Fast, cheap machines Connected by Slow, expensive people

The greatest contribution of modern IT in health care: The ability to measure and report quality and the outcomes of policy decisions in speedily and economically

What do we need? Relevance Speed “good enough” precision Analytical attributes and skills unfamiliar to many epidemiologists, health services and policy researchers Integrated care/research IT platforms

Decision-based Evidence Making Mark D. Smith, MD MBA National Health Policy Conference Washington, DC February 7 th, 2006