A Look at the Data

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Science  17 May 2013:
Vol. 340, Issue 6134, pp. 788
DOI: 10.1126/science.340.6134.788-b

A lot of people in the United States do not have health insurance, and one aim of the Patient Protection and Affordable Care Act is to expand the coverage of low-income individuals. In 2008, Oregon enrolled about 6000 new applicants, chosen via lottery, in its Medicaid plan. Baicker et al. now describe the 2-year outcomes for these individuals in comparison to a control group of 6000 people who had applied but were not chosen. In terms of finances, the enrollees had fared better: They had lower medical expenses and had incurred less debt. In terms of health care access, the enrollees had made more office visits and taken more advantage of preventive screenings. Neither of these outcomes is particularly surprising given the function of health insurance. What was surprising, and disappointing to some, was the lack of effect of coverage on the health of these individuals. This was assessed via many measures, but the most critical were three pre-specified indicators of high blood pressure (mm Hg), high cholesterol (mg/dl), and high blood sugar (glycated Hb); these parameters reflect underlying conditions that predict mortality due to chronic noncommunicable diseases. Changes in these measures might reasonably have been expected to be detectable within the time frame of 2 years, but none were seen. A final take-home message, much less actively debated in the blogosphere, is the importance of performing impact evaluations.

N. Engl. J. Med. 368, 1713 (2013).

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