Edmonds, Brownsyne TuckerMcKenzie, FatimaFadel, William F.Matthias, Marianne S.Salyers, Michelle P.Barnato, Amber E.Frankel, Richard M.2015-08-182015-08-182014-12Edmonds, B. T., McKenzie, F., Fadel, W. F., Matthias, M. S., Salyers, M. P., Barnato, A. E., & Frankel, R. M. (2014). Using Simulation to Assess the Influence of Race and Insurer on Shared Decision Making in Periviable Counseling. Simulation in Healthcare, 9(6), 353-359. http://dx.doi.org/10.1097/SIH.0000000000000049https://hdl.handle.net/1805/6650Introduction: Sociodemographic differences have been observed in the treatment of extremely premature (periviable) neonates, but the source of this variation is not well understood. We assessed the feasibility of using simulation to test the effect of maternal race and insurance status on shared decision making (SDM) in periviable counseling. Methods: We conducted a 2 × 2 factorial simulation experiment in which obstetricians and neonatologists counseled 2 consecutive standardized patients diagnosed with ruptured membranes at 23 weeks, counterbalancing race (black/white) and insurance status using random permutation. We assessed verisimilitude of the simulation in semistructured debriefing interviews. We coded physician communication related to resuscitation, mode of delivery, and steroid decisions using a 9-point SDM coding framework and then compared communication scores by standardized patient race and insurer using analysis of variance. Results: Sixteen obstetricians and 15 neonatologists participated; 71% were women, 84% were married, and 75% were parents; 91% of the physicians rated the simulation as highly realistic. Overall, SDM scores were relatively high, with means ranging from 6.4 to 7.9 (of 9). There was a statistically significant interaction between race and insurer for SDM related to steroid use and mode of delivery (P < 0.01 and P = 0.01, respectively). Between-group comparison revealed nonsignificant differences (P = <0.10) between the SDM scores for privately insured black patients versus privately insured white patients, Medicaid-insured white patients versus Medicaid-insured black patients, and privately insured black patients versus Medicaid-insured black patients. Conclusions: This study confirms that simulation is a feasible method for studying sociodemographic effects on periviable counseling. Shared decision making may occur differentially based on patients’ sociodemographic characteristics and deserves further study.en-USPublisher Policyshared decision makingracehealth insuranceArticle