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Screening and Selection: The Case of Mammograms

Author

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  • Liran Einav
  • Amy Finkelstein
  • Tamar Oostrom
  • Abigail Ostriker
  • Heidi Williams

Abstract

We analyze selection into screening in the context of recommendations that breast cancer screening start at age 40. Combining medical claims with a clinical oncology model, we document that compliers with the recommendation are less likely to have cancer than younger women who select into screening or women who never screen. We show this selection is quantitatively important: shifting the recommendation from age 40 to 45 results in three times as many deaths if compliers were randomly selected than under the estimated patterns of selection. The results highlight the importance of considering characteristics of compliers when making and designing recommendations.

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  • Liran Einav & Amy Finkelstein & Tamar Oostrom & Abigail Ostriker & Heidi Williams, 2020. "Screening and Selection: The Case of Mammograms," American Economic Review, American Economic Association, vol. 110(12), pages 3836-3870, December.
  • Handle: RePEc:aea:aecrev:v:110:y:2020:i:12:p:3836-70
    DOI: 10.1257/aer.20191191
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    3. Marianne P. Bitler & Christopher S. Carpenter & Danea Horn, 2021. "Effects of the Colorectal Cancer Control Program," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2667-2685, November.
    4. Francetic, Igor & Meacock, Rachel & Sutton, Matt, 2022. "Understanding Concordance in Health Behaviours among Couples: Evidence from the Bowel Cancer Screening Programme in England," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 310-345.
    5. Emily Oster, 2020. "Health Recommendations and Selection in Health Behaviors," American Economic Review: Insights, American Economic Association, vol. 2(2), pages 143-160, June.
    6. ZHAO Meng (KONISHI Moe), 2023. "Does Free Cancer Screening Make a Difference? Evidence from the effects of a free-coupon program in Japan," Discussion papers 23067, Research Institute of Economy, Trade and Industry (RIETI).
    7. Abbasi, Ali & DiTraglia, Francis J. & Gazze, Ludovica & Pals, Bridget, 2023. "Hidden hazards and screening policy: Predicting undetected lead exposure in Illinois," Journal of Health Economics, Elsevier, vol. 90(C).
    8. Jason Abaluck & Leila Agha & David C. Chan Jr & Daniel Singer & Diana Zhu, 2020. "Fixing Misallocation with Guidelines: Awareness vs. Adherence," NBER Working Papers 27467, National Bureau of Economic Research, Inc.
    9. Eleanor Corkum & Tiffanie Perrault & Erin C. Strumpf, 2023. "Improving Breast Cancer Diagnosis Pathways in Quebec," CIRANO Project Reports 2023rp-22, CIRANO.
    10. Hwang, Jisoo & Hwang, Seung-sik & Kim, Hyuncheol Bryant & Lee, Jungmin & Lee, Junseok, 2023. "Risk Compensation after COVID-19 Vaccination," IZA Discussion Papers 16053, Institute of Labor Economics (IZA).
    11. Abbasi, Ali & Gazze, Ludovica & Pals, Bridget, 2022. "Hidden hazards and Screening Policy : Predicting Undetected Lead Exposure in Illinois Using Machine Learning," The Warwick Economics Research Paper Series (TWERPS) 1398, University of Warwick, Department of Economics.
    12. Abbasi, A & DiTraglia, F & Gazze, L & Pals, B, 2022. "Hidden hazards and Screening Policy: Predicting Undetected Lead Exposure in Illinois Using Machine Learning," CAGE Online Working Paper Series 612, Competitive Advantage in the Global Economy (CAGE).
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    More about this item

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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