Following a year marked by one challenging headline after another in 2020, news in the fight against COVID-19 will likely turn better in 2021 thanks to improved treatments and the arrival of effective vaccines. From a Health IT standpoint, however, both the good news and the bad are together fueling a steady growth in data volumes and complexity that will require new levels of IT coordination and data management.
The reason for this is that medical professionals now have a year’s worth of health metrics on the spread of COVID-19 and reams of structured, unstructured, and behavioral data on treatment regimens and patient outcomes. At the same time, a similar avalanche of data is growing around the administration and efficacy of newly-approved vaccines. Taken together, these factors present challenges of both complexity and scale.
Let’s take a look at three resulting trends we’ll likely see in 2021 as data-driven professionals seek to address these challenges through better ways to leverage information for insight and action against the global pandemic.
Trend 1: Enhanced adoption of common health IT data standards – Whether it’s through the ANSI-accredited Fast Healthcare Interoperability Resources (FHIR) schema or similar frameworks, we’ll see a push to standardize health-related data across mobile phone apps, cloud communications, EHR-based data sharing, server communication in large institutional healthcare providers, and more. The goal is to break down silos between these disparate data sources and platforms. And there’s a cultural component to the silo-busting as well, in that common standards and definitions for data can also help technologists and business users collaborate more efficiently. That can be a challenge in any domain area; but in the case of COVID-19, success around seamless, secure, and proactive analysis of data can literally save lives.
Trend 2: Increased focus on reproducible research – As the volume of health data grows with the number of cases and populations affected, and treated, we’ll see more emphasis on reproducible research that’s repeatable and scalable even when large data sets, AI, and ML are involved. Reproducible research is the key to cutting through the complexity that comes from huge volumes of COVID-19 data of a diverse nature from diverse sources, often with strict privacy limitations. It’s also a way to reap the most value in analyzing and scaling insights from clinical trials, since the principles of reproducible research in data science dovetail nicely with the scientific method of clinical trials. When we standardize how we categorize, cleanse, and analyze clinical trial data, that builds a data lineage to ensure even the most advanced algorithms, AI analysis, and related methodologies are reproducible at the scale required to fight a global pandemic.
Trend 3: More cross-industry collaboration to harmonize disparate data sets – In order to deal with the varied inputs necessary for COVID-19 analysis, a premium will be increasingly be placed on examining core data entities and relevant context of datasets, regardless of origin. Doing so may require new levels of coordination among organizations that manage data, in some cases putting competitive instincts aside temporarily – not unlike how FedEX and UPS did so to coordinate distribution of COVID-19 vaccines. The collaboration is also needed to help navigate the regulatory realities, such as HIPAA restrictions on health data, or ATOs for anything that interacts with government data or systems.
These three trends toward better data management, collaboration, and insight are good ideas in any IT context. But, in a version of the old saying about necessity being the mother of invention, these best practices should get top priority in 2021 as Health IT professionals continue to face the outsized challenge of battling a dangerous global pandemic.