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Does X Really Cause Y?

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Does X Really Cause Y?
Chan ges in

Does X Really
Cause Y?
By Bryan Dowd and Robert Town
September 2002

AcademyHealth is the national program office for HCFO, an initiative of
The Robert Wood Johnson Foundation.

Foreword
Health policy issues often dominate state and federal policymakers’ agendas. In the most recent session of the United States
Congress alone, the House and Senate addressed legislation concerning a patients’ bill of rights, prescription drugs for seniors, and generic drug substitution. While politics and legislative realities seem to have starring roles in the process, in most cases, research results and other information can be solid supporting players. Those responsible for the recommendations, if not also the decisions, strive to increase their knowledge of the problem at hand, as well as the likely impact of the regulation or legislation under consideration. However, they frequently express frustration that they do not have objective evidence-based and timely information on which to base their recommendations and decisions.
Health services researchers, meanwhile, generate information about many of the same pressing health policy issues. Each year millions of dollars are spent by private foundations and the federal government to support health services research designed to produce useful, policy relevant results. A plethora of monthly journals are filled with articles highlighting findings from studies of health care costs, quality, and access, as well as interventions designed to improve health and health care. Many universities and research institutions publish reports with findings of interest to decision-makers.
The challenge for the field, in general, and shared by us at The Robert Wood Johnson
Foundation’s Changes in Health Care
Financing and Organization (HCFO) initiative, is to develop effective mechanisms for researchers to make their findings accessible to policymakers seeking information. Typically,



References: of Nonexperimental Data, Tucson, Arizona, April 8-10, 1987 90-3454 (May 1990). Heise, D. Causal Analysis. Wiley and Sons: New York (1975). Oaks, CA (2001). Two-Part Models,” Journal of Econometrics 35 (1987) pp Prentice-Hall, Inc.: Upper Saddle River, NJ (2000). Medical Association 272:11 (September 21, 1994) pp Cambridge, MA (September 1999). Edition. MIT Press: Cambridge, MA (1998). Company: New York (1988). Press: (March 2000). Oxford University Press: New York (1998). G. C. Merriam Company: Springfield, MA (1977).

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