HEALTH ANALYTICS

COMARTS/LIS 705

Introduces key stages in the processes of gathering and analyzing data for decision making, including tasks, methods, and tools used at each stage. Topics include developing the research question from organizational goals, choosing appropriate data collection methods, sampling, basics of measurement and question design, managing and visualizing data, descriptive statistics and basic inferential statistics such as correlations, regressions, and ANOVA.

MEDICINE 914

The main concepts and challenges in medical data gathering and analysis. Identification of aspects of data gathering and measurement, including emerging data sources. Informatics concepts used in population health. Use of a self-reporting tools in an electronic health record to answer population health questions, including those surrounding health equity. Formulation of a population medicine-based clinical question, and development of a reporting strategy to answer the question. Communication of a population medicine issue, including a potential path for improvement and a description of the measurement of any impact of proposed change.

BMI/POPHLTH 551

Designed for population health researcher. Topics include descriptive statistics, elementary probability, probability distributions, one- and two-sample normal inference (point estimation, hypothesis testing, confidence intervals), power and sample size calculations, one- and two-sample binomial inference, underlying assumptions and diagnostic work.

PUBAFFR 242

We have entered a new era of "big data." It is now possible to collect and analyze genetic information, digital health records, and many other types of data quickly, cheaply, and non-invasively from large numbers of people. This new wealth of information creates exciting opportunities for more targeted, individualized approaches to health care and better management of public health risks such as age-related diseases or pandemics. However, it also creates policy challenges such as privacy, discrimination, equality, and fairness. Covers what types of health-relevant data exist, how such data is typically analyzed and used, and discuss what types of applications this enables, what type of policy challenges this brings about, and which options policy makers have to deal with these challenges. Analytic methods will include regression, principal component and cluster analysis, statistical approaches for prediction, how to interpret the results of such analyses and their limitations.

POPHLTH 784

Learn applied techniques for community health assessment and surveillance. Population health data (including census, natality, mortality, hospital discharge, behavioral risk factor) are retrieved for analysis and interpretation.