Screening and Selection: The Case of Mammograms

Working Paper: NBER ID: w26162

Authors: Liran Einav; Amy Finkelstein; Tamar Oostrom; Abigail J. Ostriker; Heidi L. Williams

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.

Keywords: No keywords provided

JEL Codes: I11; I18


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Age 40 mammogram recommendation (J14)Lower rates of cancer among responders (I12)
Shifting recommendation from age 40 to age 45 (J26)More than three times as many deaths (J17)
Selection patterns (C52)Overall effectiveness of screening policy (J78)

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