Advances in technology now allow huge amounts of data to be handled simultaneously. Katherine takes a look at how this can be used in healthcare and how it can be exploited.
Key message: Evidence Based Medicine is useful for informing healthcare professionals what works, what doesn’t, and helping to determine if the benefits outweigh the harms, but it’s far from perfect. There are valuable lessons learned about research that we can share across disciplines. What is the Evidence Based Medicine problem? In 2005, Dr. John Ioannidis, a […]
The Systematic Review is the highest level of research design and brings available evidence to find an answer to a research question. Read Danny’s blog.
Danny takes us on a tour of the Evidence-Based Medicine Pyramid and the wonders within.
Observational research is an important method in evidence-based medicine, especially when it is performed to support or assess effectiveness results from randomized controlled trials. An unwanted (but not always observable) confounder in observational research is confounding by indication and should be eliminated from the research design when possible for the results to be meaningful. Let’s find out what this confounder is!
Anna reminds us of the value of observational evidence in low income countries.
Systematic reviews aren’t cheap or quick – Alice looks at some suggestions from the blogs of Jon Brassey from TRIP and Mona Nasser from Cochrane.
Reporting and discussing clinical trials clearly and accurately can be challenging, both for journalists, and also for students. Ruth Francis has compiled 11 top tips to make it easier.
Revealing the truth behind rates, ratios and risk with QMP statistics tutorials. This is one of a series that helps with understanding of statistics and study design.
David takes a look at the evidence behind health news in the media. 20th June.
A meta-epidemiological study published in the BMJ last month has found that smaller trials consistently report larger effect sizes.
Beginners often get confused with odds ratio and relative risk, which are almost used in same sense.
A simple way to understand both.