GATEWAY CONSULTING SINGAPORE
All course participants are required to work on the Course Project Work which will account for nearly 42% of the Course contact time (7.5 hours out of a total of 18 hours for the 3-day Course).
2. Project Work Details
The Project Work component will be a major feature of the Data Analytics in Healthcare Course. In all, there will be 5 labs in which participants will be trained on the use of the R statistical package to acquire the necessary basic skills to undertake data analytics in healthcare. The Course Project Work will comprise 5 labs each of 1.5 hour duration. Details of the labs are as follows:
Lab 1. Introduction to R and R-Commander and derivation of basic statistical indices for KPIs
(Course participants will be taught how to download, install and run the open-source R statistical software and implement the R-Commander, which is the gui for R. No coding is needed.)
Lab 2. Statistical and Visual analytics using R (1)
(Course participants will be get the opportunity to work with a real clinical dataset to derive statistical indicators that are useful for KPIs and to display data and results in statistical charts and graphs)
Lab 3. Statistical and Visual analytics using R (2)
(Course participants will be get the opportunity to work with a real clinical dataset to perform commonly used statistical tests such as chi-square tests, Fisher’s exact test, t-tests, analysis of variance as well as their non-parametric equivalents)
Lab 4. Predictive analytics using R
(Course participants will get the opportunity to learn the use of linear and multiple regression analysis, multiple logistic regression analysis and Cox’s proportional hazards regression analysis to predict healthcare outcomes based on a large health dataset)
Lab 5. Plenary session: Group presentation and discussion of lab results
(Course participants working in groups will reconvene after the 4 lab exercises to present their lab findings, share experiences and discuss results)
For the labs, participants will mostly work with a real clinical dataset comprising data taken from 1000 randomly-selected individual in a large scale, population-based health survey.
3. Project Work Grading
The Project Work will account for 50% of the final marks for Course Assessment. The other 50% will be given for written Assessment comprising Multiple Choice Questions to be taken by participants at the end of the Course.