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 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.
He has consulted to healthcare organizations and researchers on cost analysis and prediction, quality and appropriateness of care, clinical trials design, comparative effectiveness research, evidence-based guideline development, corporate analytics strategy, health informatics, and big data applications involving healthcare claims and electronic health records.
Additional areas of expertise include survival analysis, longitudinal analysis, propensity score methods, Monte Carlo statistical methods, statistical boosting, generalized estimating equations, data envelopment analysis, risk adjustment, case management, population health, healthcare coding systems (e.g., ICD, CPT, LOINC), and database design.