Screening and Selection: The Case of Mammograms

65 Pages Posted: 20 Aug 2019

See all articles by Liran Einav

Liran Einav

Stanford University - Department of Economics; National Bureau of Economic Research (NBER)

Amy Finkelstein

Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER)

Tamar Oostrom

Massachusetts Institute of Technology (MIT)

Abigail Ostriker

Massachusetts Institute of Technology (MIT)

Heidi Williams

Stanford University

Date Written: August 2019

Abstract

Debates over whether and when to recommend screening for a potential disease focus on the causal impact of screening for a typical individual covered by the recommendation, who may differ from the typical individual who responds to the recommendation. We explore this distinction in the context of recommendations that breast cancer screening start at age 40. The raw data suggest that responders to the age 40 recommendation have less cancer than do women who self-select into screening at earlier ages. Combining these patterns with a clinical oncology model allows us to infer that responders to the age 40 recommendation also have less cancer than women who never screen, suggesting that the benefits of recommending early screening are smaller than if responders were representative of covered individuals. For example, we estimate that shifting the recommendation from age 40 to age 45 results in over three times as many deaths if responders were randomly drawn from the population than under the estimated patterns of selection. These results highlight the importance of considering the characteristics of responders when making and designing recommendations.

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Suggested Citation

Einav, Liran and Finkelstein, Amy and Oostrom, Tamar and Ostriker, Abigail and Williams, Heidi, Screening and Selection: The Case of Mammograms (August 2019). NBER Working Paper No. w26162. Available at SSRN: https://ssrn.com/abstract=3439172

Liran Einav (Contact Author)

Stanford University - Department of Economics ( email )

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Amy Finkelstein

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Tamar Oostrom

Massachusetts Institute of Technology (MIT) ( email )

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Abigail Ostriker

Massachusetts Institute of Technology (MIT) ( email )

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Heidi Williams

Stanford University ( email )

Stanford, CA 94305
United States

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