"Targeting screening to higher-risk groups could be more effective than general age-based recommendations, which we find attract mostly healthy women," adds Tamar Oostrom PhD '20, an assistant professor of economics at Ohio State University and another co-author of the study.

The paper, "Screening and Selection: The Case of Mammograms," appears in the December issue of the American Economic Review. The co-authors are Finkelstein, who is the John and Jennie S. MacDonald Professor of Economics in the MIT Department of Economics; Liran Einav, a professor of economics at Stanford University; Oostrom; Ostriker; and Heidi Williams, the Charles R. Schwab Professor of Economics at Stanford University.

Data show "compliers" are healthier

Overall, health insurance data show, about 90 percent of mammograms for middle-aged women are negative, another 9.7 percent are false positives, and just 0.7 percent are authentically positive. Previous studies have found particularly limited mammogram benefits for women ages 40 to 49. But the American Cancer Society has still advocated that women start annual screening at age 40, and the Affordable Care Act of 2010 mandates that insurers reimburse mammograms for women starting at age 40. Therefore the percentage of women having mammograms jumps sharply from 10 percent before age 40, to 35 percent at age 40.

However, as the scholars point out in the paper, this entire debate has "primarily focused on the average impacts of mammograms," rather than considering the possibility that those who comply with screening recommendations may make up a lower-risk group than those who do not.

To investigate this issue, the scholars drew upon multiple information sources, including the Health Care Cost Institute (HCCI), which has data about screenings and diagnoses from three insurance companies (Aetna, Humana, and United Healthcare) involving 3.7 million women who got mammograms from 2009 through 2011.

The researchers also used a database from the National Cancer Institute (NCI) called Surveillance, Epidemiology, and End Results (SEER), which provides detailed data on over 200,000 breast cancer diagnoses between 2000 and 2014 for women in 13 U.S. states, as well as demographic data about the patients. To study the impact of detection at different points in time, the researchers used a clinical model of breast cancer disease progression in the absence of treatment, which had been developed by medical researchers. That clinical model also helped the researchers approximate the overall incidence of breast cancer in the entire population, including those who are not screened.

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