Principal Consultant
John Robinson received a B.A. in Biochemistry from the University of California, Berkeley, an M.D. from the University of California, Los Angeles, and two Ph.D.s in Biostatistics and Health Services Research from Johns Hopkins University, Bloomberg School of Public Health. He was formerly Corporate Medical Director of CMG Health, a managed care organization, taught clinical trials and comparative effectiveness research methods to faculty and fellows at the Johns Hopkins University School of Medicine, conducted health plan surveys for the National Committee for Quality Assurance (NCQA), and practiced psychiatry in academic, public, and private settings.
He has published research on Bayesian statistical methods, multilevel (hierarchical) modeling, machine learning, predictive modeling, healthcare cost analysis, healthcare provider performance assessment, and primary care practice. Additional areas of statistical expertise include survival analysis, longitudinal analysis, propensity score methods, Monte Carlo statistical methods, generalized estimating equations, sample design, and data envelopment analysis.
He has consulted to healthcare organizations and researchers on a wide range of aspects of healthcare and epidemiology, including clinical research design, statistical methods, population health, appropriateness of care, guideline development, cost analysis and prediction, risk adjustment, corporate analytics strategy, and big data applications involving healthcare claims and electronic health records, and he has provided expert testimony in the areas of statistical methods, analysis of healthcare claims, and epidemiologic study design and interpretation.
