Hosted by Professor: Christopher Flinn- firstname.lastname@example.org
I study the physician-patient interaction in medical treatment decisions. For many illnesses, patients seek advice from physicians, who signal the relative value of various treatment options. Patients then incorporate this information into their treatment decision, aware that it may reflect not just their own interests but the physicians' as well. I characterize this interaction formally using a Dayesian persuasion framework and test the model's main implications, using health insurance claims data for a large district in China. Using a Difference-in-Differences approach, I find that, for a diagnosis for which surgical treatment is somewhat discretionary, a 1 percent increase in physicians' reimbursement for surgery leads to an 8 percent increase in the likelihood of surgery, with no change in health outcomes. The effect is 1.5 times larger for more insured patients. I then estimate a parameterized version of the model to calculate the value of fully informing patients about the relative value of treatments. While only 8 percent of the patients choose surgery, 57 percent of them would not have done so were they fully informed, whereby total welfare rises by 13 percent.