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Despite individual and institutional awareness of the inequity in retention, promotion and leadership of racially and ethnically underrepresented minority faculty in academic medicine, the number of such faculty remains unacceptably low. The authors explored challenges to the recruitment, retention and promotion of underrepresented faculty among a sample of leaders at academic medical centers. Semi-structured interviews were conducted from 2011 to 2012 with 44 senior faculty leaders, predominantly members of the Group on Diversity and Inclusion (GDI) and/or the Group on Women in Medical Sciences (GWIMS), at the 24 randomly selected medical schools of the National Faculty Survey of 1995. All institutions were in the continental United States and balanced across public/private status and geographic region. Interviews were audio-taped, transcribed, and organized into content areas before conducting inductive thematic analysis. Themes expressed by multiple informants were studied for patterns of association. The climate for underrepresented minority faculty was described as neutral to positive. Three consistent themes were identified regarding the challenges to recruitment, retention and promotion of underrepresented faculty: 1) the continued lack of a critical mass of minority faculty; 2) the need for coordinated programmatic efforts and resources necessary to address retention and promotion; and 3) the need for a senior leader champion. Despite a generally positive climate, the lack of a critical mass remains a barrier to recruitment of racially and ethnically underrepresented faculty in medicine. Programs and resources committed to retention and promotion of minority faculty and institutional leadership are critical to building a diverse faculty.

The transition from medical school to residency is a critical step in the careers of physicians. Because of the standardized application process-wherein schools submit summative Medical Student Performance Evaluations (MSPE's)-it also represents a unique opportunity to assess the possible prevalence of racial and gender disparities, as shown elsewhere in medicine. The authors conducted textual analysis of MSPE's from 6,000 US students applying to 16 residency programs at a single institution in 2014-15. They used custom software to extract demographic data and keyword frequency from each MSPE. The main outcome measure was the proportion of applicants described using 24 pre-determined words from four thematic categories (\"standout traits\", \"ability\", \"grindstone habits\", and \"compassion\"). The data showed significant differences based on race and gender. White applicants were more likely to be described using \"standout\" or \"ability\" keywords (including \"exceptional\", \"best\", and \"outstanding\") while Black applicants were more likely to be described as \"competent\". These differences remained significant after controlling for United States Medical Licensing Examination Step 1 scores. Female applicants were more frequently described as \"caring\", \"compassionate\", and \"empathic\" or \"empathetic\". Women were also more frequently described as \"bright\" and \"organized\". While the MSPE is intended to reflect an objective, summative assessment of students' qualifications, these data demonstrate for the first time systematic differences in how candidates are described based on racial/ethnic and gender group membership. Recognizing possible implicit biases and their potential impact is important for faculty who strive to create a more egalitarian medical community.

\"This book provides an outline with methodological steps of how to use statistics to analyze your research data. The book begins with a general introduction, which discusses what you should be trying to achieve with your statistical analysis. This involves describing the subjects you investigated and their outcomes, determining whether there is statistically significant evidence of differences in outcomes between groups of subjects, quantitatively describing effect sizes, and also determining whether any changes are large enough to be of clinical significance. Next, the authors cover data types and choosing statistical tests. This includes identifying the factor and outcome, and also identifying the type of data used to record the outcome. Readers are then introduced to multiple testing, the Chi-square test, and independent samples and the two-sample t-test. The Man-Whitney test is discussed, as well as the One-way ANOVA. Readers are taught how to Carrying out the Kruskal-Wallis test and the McNemar's test. The Paired t-test is covered, as well as how to carry out the Wilcoxon paired samples test. Readers are shown how to carry out the repeated measures ANOVA and the Friedman test. This includes discussion of merits of change in median, change in proportions in categories, and changes in high/low categories. The book concludes with a discussion on correlation and regression methods, and a detailed analysis on Cronbach's alpha\"-- Provided by publisher.

Challenges at the interface of medical statistics and AI are population inference vs. prediction, generalizability, reproducibility and interpretation of evidence, and stability and statistical guarantees.

This study provides an updated description of diversity along the academic surgical pipeline to determine what progress has been made. Data was extracted from a variety of publically available data sources to determine proportions of minorities in medical school, general surgery training, and academic surgery leadership. In 2014–2015, Blacks represented 12.4% of the U.S. population, but only 5.7% graduating medical students, 6.2% general surgery trainees, 3.8% assistant professors, 2.5% associate professors and 2.0% full professors. From 2005-2015, representation among Black associate professors has gotten worse (−0.07%/year, p < 0.01). Similarly, in 2014–2015, Hispanics represented 17.4% of the U.S. population but only 4.5% graduating medical students, 8.5% general surgery trainees, 5.0% assistant professors, 5.0% associate professors and 4.0% full professors. There has been modest improvement in Hispanic representation among general surgery trainees (0.2%/year, p < 0.01), associate (0.12%/year, p < 0.01) and full professors (0.13%/year, p < 0.01). Despite efforts to promote diversity in surgery, Blacks and Hispanics remain underrepresented. A multi-level national focus is imperative to elucidate effective mechanisms to make academic surgery more reflective of the US population.

The increasing importance of sickness and disability data across health-related disciplines is the focus of this concise but comprehensive resource. It reviews the basics of morbidity at the population level by defining core concepts, analyzing why morbidity has overtaken mortality as central to demographic study, and surveying ways these data are generated, accessed, and measured.

AbstractObjectiveTo investigate whether the US News & World Report (USNWR) ranking of the medical school a physician attended is associated with patient outcomes and healthcare spending.DesignObservational study.SettingMedicare, 2011-15.Participants20% random sample of Medicare fee-for-service beneficiaries aged 65 years or older (n=996 212), who were admitted as an emergency to hospital with a medical condition and treated by general internists.Main outcome measuresAssociation between the USNWR ranking of the medical school a physician attended and the physician’s patient outcomes (30 day mortality and 30 day readmission rates) and Medicare Part B spending, adjusted for patient and physician characteristics and hospital fixed effects (which effectively compared physicians practicing within the same hospital). A sensitivity analysis employed a natural experiment by focusing on patients treated by hospitalists, because patients are plausibly randomly assigned to hospitalists based on their specific work schedules. Alternative rankings of medical schools based on social mission score or National Institute of Health (NIH) funding were also investigated.Results996 212 admissions treated by 30 322 physicians were examined for the analysis of mortality. When using USNWR primary care rankings, physicians who graduated from higher ranked schools had slightly lower 30 day readmission rates (adjusted rate 15.7% for top 10 schools v 16.1% for schools ranked ≥50; adjusted risk difference 0.4%, 95% confidence interval 0.1% to 0.8%; P for trend=0.005) and lower spending (adjusted Part B spending $1029 (£790; €881) v $1066; adjusted difference $36, 95% confidence interval $20 to $52; P for trend <0.001) compared with graduates of lower ranked schools, but no difference in 30 day mortality. When using USNWR research rankings, physicians graduating from higher ranked schools had slightly lower healthcare spending than graduates from lower ranked schools, but no differences in patient mortality or readmissions. A sensitivity analysis restricted to patients treated by hospitalists yielded similar findings. Little or no relation was found between alternative rankings (based on social mission score or NIH funding) and patient outcomes or costs of care.ConclusionsOverall, little or no relation was found between the USNWR ranking of the medical school from which a physician graduated and subsequent patient mortality or readmission rates. Physicians who graduated from highly ranked medical schools had slightly lower spending than graduates of lower ranked schools.