Our Research
As a public benefit company, Waymark is committed to learning from our research, sharing our findings, and moving community-based care forward.
Bounds on the Conditional and Average Treatment Effect with Unobserved Confounding Factors
For observational studies, we study the sensitivity of causal inference when treatment assignments may depend on unobserved confounders and develop a loss minimization approach. Our approach is scalable and allows flexible use of model classes in estimation, including nonparametric and black-box machine learning methods. Based on these bounds for the conditional average treatment effect, we propose a sensitivity analysis for the average treatment effect.
How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study
We studied the gender wage gap between male and female physicians using a large national practice survey. We observed that the gap varied by whether physicians were compensated by fee-for-service or value-based capitated payments. Additionally, we found that other future models might better align with primary care effort and outcomes.
Catastrophic Spending On Insulin In The United States, 2017–18
Insulin is considered an essential medicine for people with diabetes, but its price has doubled during the past decade, posing substantial financial barriers to patients in the US. We studied out-of-pocket spending on insulin, considering possible risk factors impacting the likelihood of someone experiencing catastrophic spending (spending more than 40 percent of post-subsistence family income on insulin).
