MIDAS: The importance of data for health policy

Guest post by Paul Carlin of Open University / South Eastern Health and Social Care Trust

At times, when participating in healthcare research, one cannot help but feel slightly divorced from the realities and practicalities of direct clinical care, even when delivering clinical trials. The notion that the evaluation must remain dispassionate and divorced from the emotions and pressures of patient care, particularly within Randomised Controlled Trials (RCT), is evident in the design and reporting of studies, even when psychological impacts are evaluated. Measurement is the goal, measurement that indicates appropriately whether an intervention for example does or does not make a difference.

With MIDAS this gap between theory, i.e. linking data with decision making for public health could feel somewhat remote, an exercise in governance and technological development albeit with support from healthcare practitioners and policy makers that could perhaps prove useful in some future iteration.

How quickly things change!

Corona Virus Disease 19 (COVID-19) has shown how data at population level not only helps track the disease, bringing data from multiple sources (primarily healthcare in nature) to understand the spread, but can also be used to model potential growth, incidence and intervention for effect.

One need only look at the following: https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/news–wuhan-coronavirus/ which impacted significantly on the government response to COVID – 19 in the UK, or to https://medium.com/@tomaspueyo/coronavirus-the-hammer-and-the-dance-be9337092b56 that argues for rapid scaling of controls at national levels.

MIDAS has also used some of its developed technology to track the disease trajectory, research, public interest and media reporting, see a previous Blog: http://www.midasproject.eu/2020/03/13/a-midas-contribution-to-the-global-covid-19-strategy/. This is presented in a user-friendly form:

Figure 1: Articles

As more data from multiple sources is incorporated into models, the tracking of the disease becomes ever more accurate, and gains much more significance when reflected in evaluation of intervention against potential effect, becoming more and more important as the struggle against this tiny RNA virus continues.

The tools to amalgamate, structure, clean and analyse data will gain a standing that will have real effect on us all in relatively short periods of time, as policy makers try and understand how best to meet the challenges of this menace head on.