Advances in technology, the availability of large amounts of data and the rapid growth of electronic health data and analysis tools have led to an ever-increasing need for specific skills in data analytics. The online Healthcare Analytics certificate program provides learners with the knowledge and skills to contribute to data analytics and become a vital part of their healthcare informatics team.
|MHA 500||Introduction to Healthcare Analytics||3 Credits|
|MHA 501||Programming Tools and Techniques in Data Management||3 Credits|
|MHA 504||Predictive Data Analytics||3 Credits|
|MHA 502||Research Methods||3 Credits|
Introduction to Healthcare Analytics (3 credits)
The course introduces basic concepts in healthcare analytics. Students will develop data analysis skills with an emphasis on statistical reasoning. The course is designed to teach students how to use data to make informed decisions. This process includes reviewing the data, exploring all the underlying assumptions, summarizing and analyzing the data and finally translating the results. Discussions and assignments will focus on honing data interpretation and the ability to strategically apply analysis results to improve health outcomes.
Programming Tools and Techniques in Data Management (3 credits)
This course is designed to train students in basic and advanced statistical programming languages (such as SAS or R) together with techniques and tools necessary for data management and data mining. Students will develop skills in the data management process for analytics including data acquisition, cleansing and debugging. Students will be able to relate and aggregate these data in analytic databases, data marts and data warehouses, and will be able to explore different analytical decision tools through case studies and projects.
Predictive Data Analytics (3 credits)
This course focuses on statistical inference and hypothesis testing methods in predictive analytics. Students will learn the application of statistical methods for analyzing both continuous and discrete data for knowledge discovery. Analytic continuous and discrete data concepts and methods are developed with practical skills in exploratory data analysis. Descriptive statistics, goodness-of-fit tests, correlation measures, single and multiple linear regression, analysis of variance and covariance (ANOVA and ANCOVA), contingency tables, logistic regression, multinomial and multivariate models will be covered. Application of various statistical methods using case studies and real-world data will leverage statistical assessment and interpretation.
Research Methods (3 credits)
This course introduces research methods in a healthcare setting. Students will be able to learn about development of research questionnaire and design, methodology, data collection and sampling techniques, sample size and power analysis, research ethics and validation and effective dissemination of research. Students will be able to explore and evaluate different types of research procedures and outcomes in the healthcare sector.
Classes are taught online (asynchronous) and are offered in a 16-week format, ideal for participants who have professional and family responsibilities.
Federal financial aid may be available for any term in which a student is enrolled at least half-time, subject to timely completion of the Free Application for Federal Student Aid (FAFSA). Private education loans may be available for less than half-time study.
Tuition costs for the Healthcare Analytics graduate certificate is based upon the number of credit hours taken per term. Tuition is due at the beginning of each term of your enrollment. For more information, please contact EVMS Financial Aid at email@example.com for more information.
Gainful employment information applies to the Graduate Program in Healthcare Analytics certificate programs at EVMS, where students may receive Title IV aid. See the gainful employment disclosure for more information.