Really want to make a difference in the world? Well, read on to find out about how some scientists are literally saving lives, just by analyzing data.

A systematic review (aka meta-analysis) on existing, published data, can reveal truths (or falsehoods) that may contain the key to making better decisions. This can be particularly true in the field of healthcare. Because so many people use healthcare, a better decision, even one with a small effect, can have an enormous impact on a large population.

One organization that is famous for conducting such systematic review is UK-based Cochrane. We share some of their work here as an example of the potential power of data to solve real world problems.

What’s the problem they solve?

Huge numbers of medical drug trials take place every year, trying to find out whether treatments help or harm, whether they have side-effects, and so on. This creates a huge amount of data, which is increasing all the time.

Unfortunately, the quality of this data can vary (to put it mildly). Trials can:

1. be inconclusive, due to small numbers of participants.

2. be methodologically flawed, biasing the results.

3. be subject to intentional manipulation, such as failing to publish negative results. This is especially a problem where large amounts of money stand to be made or lost on e.g. the success of a new drug.

Systematic review pools the data from many different trials, (thus addressing point 1) and combines them in a way that weights the results according to quality, to reduce the effect of biases from point 2 and 3.

To avoid introducing bias (even unconscious) each review is performed in a transparent, systematic way with clear rules on how researchers will go about finding the published trial data (like what searches they will perform) and how their analysis will be performed - BEFORE performing the actual work.

Cochrane reviews are noted for using such methods and have been called the gold standard for trial data analysis. See their video here explaining their methods.

How does this save lives? Check out the logo

See the Cochrane logo above? Those lines and the diamond are an example of a forest plot, taken from a real life systematic review of the effects of corticosteroids given to women who are about to give birth prematurely (an idea taken from observations of success with this treatment in sheep!).

Each horizontal line represents the mean results and confidence in that mean for one study. To the left means a “beneficial” effect, and to the right means a “harmful” effect. Longer lines show lower certainty in the mean result. The vertical line represents “no effect” - if the horizontal line for a study touches that vertical line, it means the confidence interval for the result overlaps “no effect” and it was concluded that the trial was inconclusive.

You can see that many are inconclusive studies, as the horizontal line touches the central vertical line. This meant that adoption of the corticosteroid treatment was slow. Doctors might just have seen the results of one trial in whatever publication they happened to read.

However, the diamond shows the overall result when the data for  all the trials were combined. It sits clearly to the left, telling us that based on all the data, we are reasonably confident that this simple treatment can save the life of a premature baby.

This systematic review - originally published by Crowley et al. and since updated - gave doctors the clear information they needed to start adopting this simple treatment, which has saved thousands of lives.

DataClassroom is a tool designed to impart insights about the statistical process, while doing data visualization and analysis.

We’ve previously written about why collecting enough evidence is important, and how the tool can help show this.

If this sounds like what you’ve been waiting for, register for a free trial of DataClassroom or check out the website, have a browse through the searchable User Guide, watch one of our videos or get in touch and see how we can help!

Note: DataClassroom is not endorsed by, or in any way affiliated with Cochrane. We’re just big fans! Logo used by permission.