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    (877)-792-1060

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Emmanuel Erskine, M.A.

Senior Researcher, Statistician, Programmer, Analyst, is an applied mathematician. He has a wide-ranging background in advanced mathematical, statistical, computational modeling techniques and methodologies, including knowledge and experience with sampling, weighting, non-response analysis/adjustments, bench-marking, imputation, and assessing/minimizing survey bias, variance and error, and analysis of data from complex sample surveys. He is proficient in SAS, R, Python, among other statistical/mathematical software packages, and has the ability to utilize large scale information systems. As a researcher he has: 1) Worked with clients conducting and performing surveys by applying sampling techniques and counting responses; 2) Evaluated reliability of source information by weighting raw data and organized results for analysis; 3) Presented data by computer readouts, graphs, charts, tables and written reports; 4) Prepared and created conclusions and forecasts by analyzing and interpreting data summaries; 5) Maintained historical data records by organizing and filing statistical reports; and 6) Familiarized himself with current research studies on complex survey data by organizations like Westat with a focus on variance estimation, replication-based methods, and issues of data disclosure.

Mr. Erskine is the lead expert in performance metrics analytics for KCI and in 2012/2013 led a team that used Agency for Healthcare Research and Quality (AHRQ) Quality Indicators and New York University Emergency Department (NYU ED) Algorithms in evaluating metrics for the State of Maryland Health Services Cost Review Commission. He worked as the data manager and Hospital Consumers Assessment of Healthcare Providers and Systems (HCAHPS) data analyst for the Maryland Department of Health (MDH) Quality Measure Data Center (QMDC) project. Mr. Erskine has experience working on updating the NYU ED Algorithm software with the correct ICD-9/10 codes and identifying strategies for pay-for-performance in public health insurance. He works with clients to provide statistical support for protocol development including sample size calculations, statistical analysis plan preparation, statistical analysis of research study data, and presentation in study reports and publications.