As we near HIMSS next week, it seems every day brings a new announcement or press release on the latest and greatest healthcare analytics platform or data integration tools. Claims are made that these newly sourced tools will solve all of your patient matching, interoperability, pop health and data security challenges. Healthcare companies are making big investments into these new platforms, but have these organizations made the same investment into fueling that platform with the best data?
Healthcare organizations should be demanding an increase in both depth and breadth of data, which will undoubtedly drive more meaningful insights that will benefit the business and ultimately the consumer.
Healthcare Analytics Are Only As Smart As the Data Behind Them
Last week, KLAS released its list of the most disruptive companies in healthcare. There were some familiar names on the list, but also some new startups with emerging technology from cybersecurity to telehealth. The companies that sparked interest are using AI, machine learning and healthcare analytics to improve efforts in population health, business intelligence and process automation. But imagine a patient matching platform without great data. What happens when there’s still a percentage of patient records you cannot reconcile?
The question remains how will these tech companies grow to scale for the large amounts of data that still needs to be housed and analyzed. That’s why we believe it’s key to have an experienced, industry leading data partner to help you.
2020 Will Be the Year of Collaboration
Here’s an example. This week, we announced a collaboration with Clarify Health, a leading healthcare analytics company that provides AI-driven market intelligence and predictive analytics business applications to health systems, health plans, and life sciences companies. The collaboration will enable Clarify Health to use LexisNexis Risk Solutions Health Care to obtain socioeconomic data to better understand patient populations.
The goal is to use our clinically validated social and behavioral determinants of health data, often referred to as “SDOH” attributes, within predictive models that currently utilize clinical data to improve health outcomes, reduce costs and prevent readmissions.
Everyone is trying to get to the same goal: solve one of the healthcare industry’s biggest challenges, and we’ll see many of them on display at HIMSS next week among the city-block sized booths. We don’t claim to have all of the answers but we do know that we lead the healthcare industry with best in class patient and provider data sets. And remember, if you are willing to make the investment into that shiny new platform, it is imperative you make an equal investment into the data. Sometimes the platform is only as good as the data that feeds it.
