Hospitals and Healthcare
In an industry where the health, and even lives, of patients are on the line, there’s simply no room for error when it comes to hiring and developing staff. Within such a fast-paced and high-pressure environment, having the right knowledge and training is crucial for all staff.
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Project Management: Healthcare Projects
Released 10/24/2016 Healthcare projects have their own unique set of needs and challenges, including privacy concerns and regulatory constraints. Learn how to effectively manage these challenges on healthcare projects large and small in this course with project management expert Bob McGannon. Bob goes over specific approaches to setting project goals, scheduling tasks, managing stakeholders, and mitigating the risks and challenges that are common to the medical field. Then he proposes some specific challenges to bring the concepts to life and offers solutions so you can compare your approach with his recommendations. Topics include: Managing healthcare project stakeholders Dealing with regulatory constraints Establishing milestones Assessing project risks Executing your healthcare project
Descriptive Healthcare Analytics in R
Released 12/12/2016 Analyze behavior and risk using R, the open-source statistical computing software. R provides an environment and a language you can use to analyze data, including the publicly available Behavioral Risk Factor Surveillance Survey (BRFSS) dataset. This course teaches core healthcare data science skills, including epidemiology, as well as how to perform a cross-sectional analysis, set up a data dictionary, develop metadata, determine confounders, apply exclusions, create diagrams, generate continuous and categorical outcome variables, and more. Join biotech expert and epidemiologist Monika Wahi as she first discusses design and ethical considerations, and then takes you through the steps of conducting a descriptive analysis.This detailed, practical course is designed to help those in the field of public health, medicine, and data science to edit, analyze, and interpret data. Learn how to code new variables, use the forward-stepwise modeling process, and document your decisions. Find out how to visualize results by generating charts and graphics, and how to add tables and figures to your documentation. This course helps equip you to independently design, develop, and execute a full BRFSS analysis, and even publish your results in scientific publications or journals. Topics include: Reviewing survey data and documentation Conducting a BRFSS analysis Understanding naming conventions Editing variables Reviewing distributions Generating an analytic dataset Developing descriptive statistics to answer prespecified hypotheses Preparing publication-worthy tables and plots
Healthcare Analytics: Regression in R
Released 1/19/2017 Linear and logistic regression models can be created using R, the open-source statistical computing software. In this course, biotech expert and epidemiologist Monika Wahi uses the publicly available Behavioral Risk Factor Surveillance Survey (BRFSS) dataset to show you how to perform a forward stepwise modeling process. Monika shows you how to design your research by considering scientific plausibility selecting a hypothesis. Then, she takes you through the steps of preparing, developing, and finalizing both a linear regression model and a logistic regression model. She also shares techniques for how to interpret diagnostic plots, improve model fit, compare models, and more. Topics include: Dealing with scientific plausibility Selecting a hypothesis Interpreting diagnostic plots Working with indexes and model metadata Working with quartiles and ranking Making a working model Improving model fit Performing linear regression modeling Performing logistic regression modeling Performing forward stepwise regression Estimating parameters Interpreting an odds ratio Adding odds ratios to models Comparing nested models Presenting and interpreting the final model
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