All or Nothing: Why a Population-Wide View of Health Data Is Critical for Patient-Centric Insights
Mass personalization is the holy grail of the big data revolution. Whether it’s in healthcare, product marketing or financial services, the idea of being able to deliver highly personalized solutions at scale has been an elusive promise that many have tried and failed to deliver.
The reason: it’s hard to assemble data sets that are both broad enough to be truly representative of patient populations and deep enough to deliver the precise, accurate, timely insights that are meaningful enough for individual patients. The challenge is particularly pronounced in healthcare where a labyrinth of individual data silos, strict privacy rules, and antiquated systems have created roadblocks to progress.
The Challenge is Real
Consider the example recently shared by a prominent healthcare industry investor, who explained in a FierceHealthcare op-ed how “necessity has driven hard-to-believe work-arounds” including one amazing story about a small healthcare analytics company that resorted to FedExing a 1 terabyte removable hard drive back and forth in order to share data with a multi-billion dollar health plan client.
More recently, we’ve seen the fax machine ‒ yes, the same archaic device that Michael Jordan used to announce his return to the NBA in 1995 ‒ become a bottleneck to the nation’s COVID-19 response as labs and public health departments continue to rely on the old-fashioned means of communication for sharing data.
These are not old examples from some bygone era; it is how many healthcare organizations are still trying to wrap their heads around data sharing.
Leveraging the Cloud
Contrast this approach with some of the groundbreaking work we’ve been doing recently with Kantar Health, a leading healthcare data, analytics, and research provider. Using our cloud-based Sentinel platform, Kantar Health is able to seamlessly link their patient-reported outcomes databases with our Healthcare Map of more than 320 million real-world patient journeys and start analyzing trends immediately.
This is an important development for a few reasons. First, and most obviously, it’s fast. Instead of spending weeks or months uploading (or FedExing) data into a data warehouse, manually encrypting and aligning key data fields and engineering analytics based on the newly combined data set, Kantar Health was able to plug into our database and start performing trend analysis in the cloud in a matter of days.
More importantly, though, is the ability to seamlessly connect disparate data sets – all while maintaining strict adherence to data privacy and encryption requirements – which opens up the ability to go broad and deep, achieving truly patient-centric levels of micro-segmentation within a nationally-representative dataset. Because Komodo’s Healthcare Map captures such a wide swath of the U.S. healthcare experience, Kantar Health is able to identify precise patient cohorts with a clear perspective of where they sit relative to the larger U.S. population.
Unearthing Important Trends
That’s a game-changer when it comes to understanding important trends in healthcare. Take the adoption of telehealth during the COVID-19 pandemic as an example. We’ve all seen the headlines citing the explosive growth of telehealth as the ideal solution for socially distanced healthcare, but that trend also raises lots of questions. Notably, what effect might the “digital divide” have on access to telehealth among older patients, or those without access to reliable internet connections and devices?
Answering these important questions about the social determinants of telehealth should be straightforward, but it’s not. To get the data needed to really understand this issue, researchers need timely access to near-real-time data that cuts across all age, gender, socioeconomic, and geographic factors at a national level while also delivering micro-segmentation down to the individual patient cohort level.
That’s exactly what Kantar Health was able to do by pairing their patient-reported outcomes data with ours to analyze the Social Determinants of Telehealth in the U.S. using our Healthcare Map to find that the 3,000% surge in telehealth utilization during the pandemic was driven in large part by younger, wealthier patients. They also found an interesting trend toward widespread adoption of telehealth among the Hispanic population, which was inconsistent with previous literature.
The Way Forward
These insights, of course, are just the beginning. Kantar Health is digging deeper into the telehealth trends to examine how the use of the technology is impacting utilization and adherence to various therapies and other issues.
Moreover, we continue to work with Kantar Health and several other partners across the healthcare and technology industries to improve access to timely, comprehensive data that will help us better understand individual healthcare encounters at scale.