Clinician treatment preferences affect the ability to perform randomized clinical trials and the ability to analyze observational data for treatment effects. In clinical trials, clinician preferences that are based on a subjective analysis of the patient can make it difficult to define eligibility criteria for which clinicians would agree to randomize all patients who satisfy the criteria. In addition, since each clinician typically has some preference for the choice of treatment for a given patient, there are concerns about how strong that preference needs to be before it is inappropriate for him to randomize the choice of treatment. In observational studies, the fact that clinician preferences affect the choice of treatment is a major source of selection bias when estimating treatment effects. In this paper we review alternative designs that have been proposed in the literature for randomized clinical trials that utilize clinician preferences differently than the standard randomized trial design. We also examine the effects of clinician preferences on the ability to estimate causal treatment differences from observational data, and propose an alternative method of analysis for observational data that uses clinician preferences explicitly. We report on our experience to date in using our alternative randomized clinical trial design and our new method of observational analysis to compare two treatments at the orthodontic clinics at the University of California San Francisco and the University of the Pacific, San Francisco.
"Clinician preferences and the estimation of causal treatment differences." Statist. Sci. 13 (3) 209 - 235, August 1998. https://doi.org/10.1214/ss/1028905885