LECTURE: Introduction to research 

Why research is necessary 
How to conduct data search 
Research networks 
Research governance
Basic principles of GCP 

LECTURE: Data science. 

Types of data 
Data management 
Data analysis 
Basics of statistics 
Information Governance. 
Patient identifiable data and Data protection 

LECTURE: How to start a research study.

LECTURE: How to disseminate good practice/research.

Guidance on how to publish abstracts / papers /  

LECTURE: Translation of research into clinical practice.

Sources of information: Clinical trials, stratified medicine, genomics, informatics, qualitative techniques, systematic review, meta-analysis, health services research, conference attendance 
Assimilating Information in one place 

Peer discussion 

Course (on the day) 

Group session

00:00 to 01:00 Hrs: QA session on above lectures: (Delegates questions and answers on lectures) 

Workshops: Face to face sessions or delivered virtually. 

01:00 to 02:30 Hrs – Workshop 1: Critical appraisal of a paper   
Paper will be provided one week before the course to delegates 
Two students will get one paper  
The session would include appraisal of following elements of paper:  
Relevance or Quality of research question / Methodology / Results / Discussion /Conclusion 
Most importantly limitations of abstract. 

02:30 to 03:00 Hrs – Lunch 

03:00 to 04:30 Hrs – Workshop: How to design a study based on a research question? 

Critical appraisal of a paper (5 groups of 8 students running simultaneously),  
Two students will get one paper, 2- 4 topics will be given for discussion and the group will explore through research question, ethics, methodology, power, results, feasibility and a good  research question? 

e.g Do patients undergoing hip surgery have a higher incidence of PE in postoperative period?  

Group thought provocation would be around inclusion criterion, exclusion criterion, incidence of PE in general population/surgical patients, when would they be tested for PE, how many times and for how long, diagnosis of PE, costs, no of patient needed, type of data, statistics etc.