Assessing minimal medical statistical literacy using the Quick Risk Test: a prospective observational study in Germany

OBJECTIVES: To assess minimal medical statistical literacy in medical students and senior educators using the 10-item Quick Risk Test; to assess whether deficits in statistical literacy are stable or can be reduced by training. DESIGN: Prospective observational study on the students, observational study on the university lecturers. SETTING: Charité University Medicine medical curriculum for students and a continuing medical education (CME) course at a German University for senior educators. PARTICIPANTS: 169 students taking part in compulsory final-year curricular training in medical statistical literacy (63% female, median age 25 years). Sixteen professors of medicine and other senior educators attending a CME course on medical statistical literacy (44% female, age range=30-65 years). INTERVENTIONS: Students completed a 90 min training session in medical statistical literacy. No intervention for the senior educators. OUTCOME MEASURES: Primary outcome measure was the number of correct answers out of four multiple-choice alternatives per item on the Quick Risk Test. RESULTS: Final-year students answered on average half (median=50%) of the questions correctly while senior educators answered three-quarters correctly (median=75%). For comparison, chance performance is 25%. A 90 min training session for students increased the median percentage correct from 50% to 90%. 82% of participants improved their performance. CONCLUSIONS: Medical students and educators do not master all basic concepts in medical statistics. This can be quickly assessed with the Quick Risk Test. The fact that a 90 min training session on medical statistical literacy improves students' understanding from 50% to 90% indicates that the problem is not a hard-wired inability to understand statistical concepts. This gap in physicians' education has long-lasting effects; even senior medical educators could answer only 75% of the questions correctly on average. Hence, medical students and professionals should receive enhanced training in how to interpret risk-related medical statistics.