UC Berkeley

This dissertation is comprised of three chapters, each of which contributes to the fields of health economics and psychology & economics. Two of the chapters investigate how choice architecture affects patients health care decisions. The third investigates the role of beliefs in the demand for health information. The underlying motivation for these studies stems from the observations that the proportion of HIV-infected persons in the United States who are undiagnosed has remained constant for over a decade, and those who are diagnosed are often diagnosed late in the course of their disease. Deeper understanding of how HIV test acceptance by patients depends on how the test is offered has the potential to decrease the frequency of missed opportunities for identifying infected persons.

Choice architecture has the potential to influence patients' health and health care deci- sions. In particular, decisions with significant but delayed consequences can be very sensitive to small, immediate costs and benefits. I investigate how small monetary incentives and de- fault test policies affect patient decision making with regard to HIV testing. I conduct and analyze the results of a field experiment that takes place in an urban emergency depart- ment (ED). In parallel with routine care, patients are approached by research assistants and offered HIV tests and questionnaires according to treatment assignments. In a factorial design, patients are randomly assigned to be offered HIV tests according to default scripts; they are also offered small monetary incentives and a questionnaire eliciting HIV-related risk behaviors. Patients are offered the questionnaire either before or after the test offer. Among those assigned to an early questionnaire, half are assigned to an additional question asking whether they would hypothetically accept an HIV test, a `foot-in-the-door' question (FITD).

In Chapter 1, "HIV Screening: To Test or Not to Test? It Depends on the Question," I examine three test defaults: traditional opt-in (test only those patients who request test- ing), opt-out (routine testing unless patients decline), and active-choice testing (patients are required to state whether they want to be tested). I find a test acceptance rate of 51.2% in the opt-in treatment. Active-choice and opt-out test schemes increased the proportion of patients who accepted HIV testing by clinically significant levels. Patients assigned to an active-choice test offer are 9.5 percentage points more likely to accept an HIV test; those assigned to an opt-out offer are 18.2 percentage points more likely than opt-in patients.

I take up the issue of monetary incentives in "Conditional Cash Incentives for HIV Test- ing." Patients are offered monetary incentives ($0, $1, $5, $10), which vary by ED zone (four zones) by day. I find that cash incentives of $5 and $10 increase test acceptance rates by 11.7 and 12.8 percentage points, respectively, from a baseline of 57.9% with no incentive. The $1 treatment assignment has no significant effect on overall test rates. It does, however, have a differential effect on high- and low-risk patients: patients reporting HIV risk factors are 4.3 percentage points more likely to test when offered $1 than when offered no incentive, and patients denying any risk factors are 9.6 percentage points less likely to accept testing when offered $1 than when offered no incentive. I find no difference in test rates between patients assigned to the FITD treatment and those in the early questionnaire treatment who were not asked the hypothetical question. Across defaults and monetary incentives, I observe an effect of being offered a questionnaire: patients assigned to either of Early or FITD questionnaires are 10.8 percentage points less likely to accept testing than those who are offered the test prior to being offered the questionnaire.

In "Perceptions and Misperceptions of HIV Transmission, Testing, and Treatment" I examine the relationship between beliefs regarding HIV transmission, testing, and treatment on subjects' testing behavior. I find that subjects grossly overestimate the probability of transmission for both real (e.g., injection drug use) and false (e.g., sharing a beverage) risk behaviors. Subjects also overestimate the prevalence of HIV. Despite these overestimates and self-reported risk behaviors, most consider themselves to be at no or very low risk of HIV infection, and few have ever tested for HIV. While these findings support both classical and behavioral interpretations (including psychological expected utility), these findings suggest that people's beliefs regarding HIV risk are biased and suggest that educating the public might be counterproductive, leading to more risky behaviors and lower testing rates.