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IFS-STICERD Public Economics Seminar

Diagnosis and Unnecessary Procedure Use: Evidence from C-Section

Janet Currie (Princeton University)

Wednesday 29 May 2013 12:30 - 13:45

Due to the onging coronavirus outbreak, many of our seminars and public events this year will continue as online seminars. Please check our website listings and Twitter feed @STICERD_LSE for updates.


About this event

This paper provides a model of diagnostic skill as an element of provider quality that is separate from a doctor's skill in performing procedures. Unlike higher surgical skill, which leads to higher use of surgical procedures across the board, better diagnostic skill results in fewer procedures for the low risk, but more procedures for the high risk. That is, better diagnostic skill improves the matching between patients and procedures leading to better health outcomes. Taking the model to data on C-sections, the most common surgical procedure performed in the U.S., we show that improving diagnostic skills from the 25th to the 75th percentile of the observed distribution would reduce C-section rates by 11.7% among the low risk, and increase them by 4.6% among the high risk. Since there are many more low risk than high risk women, improving diagnosis would reduce overall C-section rates. Moreover, such an improvement in diagnostic skill would improve health outcomes for both high risk and low risk women, while improvements in surgical skill have the greatest impact on high risk women. These results are consistent with the hypothesis that efforts to improve diagnosis through methods such as checklists, computer assisted diagnosis, and collaborative decision making may improve patient outcomes.

This seminar series is jointly organized by the IFS and STICERD.

IFS-STICERD Public Economics seminars are held on Wednesdays in term time at 16:30-17:30, ONLINE, unless specified otherwise.

Seminar organisers: Stuart Adam (IFS), Monica Costa Dias (IFS), Xavier Jaravel (LSE), Camille Landais (LSE), Attila Lindner (UCL), Joana Naritomi (LSE), and Johannes Spinnewijn (LSE).

For further information please contact Lubala Chibwe, either by email: l.chibwe@lse.ac.uk.

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