Been awhile since your last statistics class? It can be difficult to judge the quality of studies, the significance of data, or the importance of new findings when you don't know the basics. Download our cheat sheets to get a quick, one-page refresher on some of the foundational components of evidence-based medicine.
- Evidence-based practice
- Observational studies
- Randomized control trials
- Systematic reviews
- Statistical significance
Evidence-based practice (EBP) is the explicit use of the best available medical evidence in making clinical decisions. Needing to improve cost efficiency and boost care quality, providers are investing significant time and resources into the creation and adoption of EBPs. These practices guide clinicians in providing patients with the right care, at the right level, at the right time.
In an observational study, researchers observe a population of individuals and measure their outcomes. Unlike in randomized control trials, researchers do not intervene in selecting which participants get a given intervention.
Observational studies are the most common study type, although their takeaways are often limited because they cannot prove causality (something which is often misunderstood).
In a randomized control trial, participants are randomly divided into separate groups where one group is the experimental group (given a treatment or intervention) and the other group is the control group (not given the treatment or intervention). Then, researchers compare the two groups on a particular outcome.
Randomized control trials, especially when analyzed together in a systematic review or meta-analysis, are the basis for evidence-based medicine and forming new clinical guidelines.
A systematic review is a summary of existing research on a given topic. It answers a particular research question by collecting and summarizing all empirical evidence that meets a certain pre-specified eligibility criteria.
Systematic reviews are the strongest way to understand the 'scientific consensus' on a given issue and evaluate new clinical research.
A meta-analysis is a statistical analysis that combines the data of multiple studies into a single estimate of an effect size.
Meta-analyses, particularly of randomized control trails, are one of the strongest types of evidence, and are often used to justify new clinical guidelines or medical approaches.
The result of a study is considered statistically significant when it is highly unlikely to have occurred by chance or due to sampling error (the sample being different from the general population).
Statistical significance is often the basis for deciding whether a new health intervention or treatment is effective.
Ready to apply these concepts?
Read our Daily Briefing coverage to understand why these concepts matter.
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