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'Observational research: an introduction to epidemiology, real-world data, prognostic models, machine learning, and health economics' is provided by NDORMS for MSD postgraduate researchers wanting to learn about the methods and practice of observational research in basic and advanced real world epidemiology, with a key focus on musculoskeletal diseases and interventions.

This four week module covers basic and advanced real world epidemiology, sources of real-world data in the UK, development and validation of prognostic models, machine learning, foundations of health economics, and economic analyses of MSK diseases and interventions. It provides an opportunity to learn about the foundations of a series of key related topics in observational research. No prior knowledge is required.

One of the key principles of evidence-based medicine is that there exists a hierarchy of evidence, often represented by a pyramid with study types ordered according to their comparative level of validity. Systematic reviews and meta-analyses sit at the top, followed by randomised controlled trials (RCTs) and then various observational study designs. The high costs and limitations of RCTs, together with the ever-growing availability of observational or routinely collected data and data science tools make routinely collected data increasingly relevant in evidence-based medicine and healthcare decision-making. 

The Centre for Statistics in Medicine at NDORMS is home to interdisciplinary teams conducting observational research with the aim to advance healthcare practice and policy focusing on improving safety, vigilance, equity, effectiveness and cost-effectiveness. Topics of interest include clinical prognosis, supervised and unsupervised machine learning, analysis of routinely-collected health data, and health economics and outcomes research. This 8-session module will provide you with an introduction to the methods and practice of observational research which can help support your research and will enhance your skills in your future research career.

The course is spread over approximately 4 weeks between 20 April and 23 May 2022, with occasional work to be done between sessions to help prepare and enrich the level of discussion in subsequent sessions. 

For further detailed course information and registration, please contact

Learning outcomes

In this series of eight sessions, this module will:

  • Familiarise you with key methods and data sources of observational research
  • Help you consider the strengths, limits and applications of observational research
  • Apply this understanding to observational research in musculoskeletal diseases and interventions.