Practice Variation, Bias, and Experiential Learning in Cesarean Delivery: A Data-Based System Dynamics Approach

Decision making regarding cesarean delivery (CD) versus vaginal delivery (VD) in the United States is suboptimal. First, there has been a bias toward more CD. Experts contend that CD is overperformed in the United States. In 2010, 32 percent of birth cases in United States were CDs (Hamilton, Martin, and Ventura 2011), whereas the World Health Organization's standard for developed countries is 10–15 percent (World Health Organization 1985). Second, there has been considerable practice variation in delivery mode decisions, after controlling for patients' health status and risk. Epstein and Nicholson (2009) found substantial variation across both regions and physicians within regions, suggesting that physicians make different decisions for medically similar patients. Overperforming CD is undesirable for many reasons, including long-term side effects and increased costs (Hall and Bewley 1999; Wagner 2000; Villar et al. 2006). There are many potential determinants of practice variation. Regional factors include culture, norms, standards, regulations, and the organization of health services (Fisher, Bynum, and Skinner 2009). Physicians' characteristics, such as age and training (Grytten and Sorensen 2003; Rebitzer, Rege, and Shepard 2007; Epstein and Nicholson 2009) and financial incentives also influence decisions (Bodenheimer and Grumbach 2005). Patients' characteristics such as health status, preferences, race, and socioeconomic status may influence physicians' decision making (Institute Of Medicine 2003). However, these factors cannot completely account for all practice variation and bias (Fisher, Bynum, and Skinner 2009). Accordingly, other relevant factors need to be considered. Although the existing candidate explanations for practice variation come from a static “snapshot in time” framework, dynamic decision-making processes may be important. Delivery mode decisions are not one-time events. One obstetrician might perform thousands of deliveries in her career. One might expect that the repetitive nature of making decisions and observing outcomes (experiential learning) could influence practice style and lead to learning and correcting decisions. For example, obstetricians with similar training, background, and patient pools may by random chance perform different numbers of CD versus VD early in their careers. Those early initial experiences (including poor experiences such as emergency CD after initial labor) might change their tendencies to conduct CD versus VD, in turn affecting their skills and future performance of CD versus VD. This process of feedback and learning may lead to practice divergence despite identical initial states and patient populations. Such possible effects of experiential learning on practice styles are underexplored in the literature. This study aims at this direction and examines the contribution of experiential learning to practice variation. We develop a system dynamics model of delivery mode decision making (scheduled and unscheduled CD and VD) and explore dynamic changes in physicians' decisions as they accumulate experience. By imposing theory-based structures, a system dynamics simulation can use real-world data to test explanations that manifest endogenously, such as experiential learning. We calibrate our model with empirical data from deliveries performed by obstetricians in Florida and examine the extent to which simulation results replicate the data. We then analyze the simulation results and discuss policy implications.