A health data divide between clinicians and data scientists is wasting precious medical research and healthcare resources, hampering innovation and resulting in poorer outcomes than would otherwise be achievable.
That’s the conclusion of researchers from the Massachusetts Institute of Technology’s Critical Data group, an affiliation of research labs at MIT focused specifically on data that has a critical impact on human health.
As the use of IT and data grows within healthcare, the researchers suggest that data science should be included in the core curriculum during medical school and residency training.
Despite the digitization of healthcare and abundance of health data from disparate sources including EHRs, mobile devices and wearables, they say the fundamental quality, safety and cost challenges of providing care have not been resolved and that better use of clinical data has the potential to address these issues.
According to Leo Anthony Celi, MD, head of the MIT Critical Data group, the problem is that a lot of the data exists in silos and is not integrated. In particular, he believes that the idea of data sharing is still foreign in healthcare because of stubborn cultural barriers that continue to stand in the way of science and progress.
“If we are to learn as a healthcare system, there has to be more data integration and harmonization,” contends Celi, who specifically calls out the health data divide between clinicians, the domain experts and the technical experts, such as data scientists.
“There is a persistent gap between the clinicians required to understand the clinical relevance of the data and the data scientists who are critical to extracting useable information from the increasing amount of healthcare data that are being generated,” wrote Celi and his MIT colleagues in a recent viewpoint article published in the Journal of Medical Internet Research.
However, the MIT researchers contend that the health data divide can be narrowed by creating a culture of collaboration between clinicians and data scientists, exemplified by events such as datathons, as well as reforming medical education, rethinking academic incentives and providing funding opportunities.