Hardeman, Rachel R.

AbstractBackgroundOne in nine US infants is born before 37 weeks' gestation, incurring medical costs 10 times higher than full‐term infants. One in three infants is born by cesarean; cesarean births cost twice as much as vaginal births. We compared rates of preterm and cesarean birth among Medicaid recipients with prenatal access to doula care (nonmedical maternal support) with similar women regionally. We used data on this association to mathematically model the potential cost‐effectiveness of Medicaid coverage of doula services.MethodsData came from two sources: all Medicaid‐funded, singleton births at hospitals in the West North Central and East North Central US (n = 65,147) in the 2012 Nationwide Inpatient Sample, and all Medicaid‐funded singleton births (n = 1,935) supported by a community‐based doula organization in the Upper Midwest from 2010 to 2014. We analyzed routinely collected, de‐identified administrative data. Multivariable regression analysis was used to estimate associations between doula care and outcomes. A probabilistic decision‐analytic model was used for cost‐effectiveness estimates.ResultsWomen who received doula support had lower preterm and cesarean birth rates than Medicaid beneficiaries regionally (4.7 vs 6.3%, and 20.4 vs 34.2%). After adjustment for covariates, women with doula care had 22 percent lower odds of preterm birth (AOR 0.77 [95% CI 0.61–0.96]). Cost‐effectiveness analyses indicate potential savings associated with doula support reimbursed at an average of $986 (ranging from $929 to $1,047 across states).ConclusionsBased on associations between doula care and preterm and cesarean birth, coverage reimbursement for doula services would likely be cost saving or cost‐effective for state Medicaid programs.

Context Health care trainees demonstrate implicit (automatic, unconscious) and explicit (conscious) bias against people from stigmatised and marginalised social groups, which can negatively influence communication and decision making. Medical schools are well positioned to intervene and reduce bias in new physicians. Objectives This study was designed to assess medical school factors that influence change in implicit and explicit bias against individuals from one stigmatised group: people with obesity. Methods This was a prospective cohort study of medical students enrolled at 49 US medical schools randomly selected from all US medical schools within the strata of public and private schools and region. Participants were 1795 medical students surveyed at the beginning of their first year and end of their fourth year. Web‐based surveys included measures of weight bias, and medical school experiences and climate. Bias change was compared with changes in bias in the general public over the same period. Linear mixed models were used to assess the impact of curriculum, contact with people with obesity, and faculty role modelling on weight bias change. Results Increased implicit and explicit biases were associated with less positive contact with patients with obesity and more exposure to faculty role modelling of discriminatory behaviour or negative comments about patients with obesity. Increased implicit bias was associated with training in how to deal with difficult patients. On average, implicit weight bias decreased and explicit bias increased during medical school, over a period of time in which implicit weight bias in the general public increased and explicit bias remained stable. Conclusions Medical schools may reduce students’ weight biases by increasing positive contact between students and patients with obesity, eliminating unprofessional role modelling by faculty members and residents, and altering curricula focused on treating difficult patients.

ObjectiveTo examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students.MethodsA web‐based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti‐fat attitudes test.ResultsA majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non‐Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice.ConclusionsImplicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact.