Name that Tune…Probably Not

Like all of you, I’ve personally experienced how the right data can make a difference in healthcare. Did the healthcare provider spell my name right? Do they know that my older parent lives alone? Interactions related to identity make a world of difference for patient care and customer service.

Professionally, I’ve spent much of my career on identity within the healthcare industry. I’ve worked with Verato for 4.5 years and spent 11 years previously with Initiate later purchased by IBM.

Early days—the need for algorithm tuning

In my Initiate days, it was obvious that we’d start tackling medical data management with the patient/person domain, since the patient is at the center of most issues, whether clinical, operational, or safety-related.

Rationalizing person data in healthcare has always been a tough job, given the number of systems, processes, technologies, partners, and individuals involved in sourcing the person data. The technology to unify this person/patient data was complex, requiring data and algorithm specialists to analyze the data and craft the right algorithmic process and components for the best results.

Healthcare organizations needed to hire skilled professional services teams to tweak and tune the algorithm, looking for the highest match rates possible. As each new IT system was onboarded, the team would spend 2-3 months re-tuning the delicate matching algorithm, testing it, and then moving changes into production. This situation persists for healthcare organizations with legacy enterprise master person indexes (EMPIs) like IBM Initiate.

Today—no time for tuning

Fast forward to 2020. The volume of IT systems in play has exploded, the demand for information sharing is greater, and legacy solutions like IBM Initiate require even more custom crafting and algorithm tuning.

Tuning and retuning is like guessing what song will play next on a jukebox. Sitting in a diner booth, you could observe how often each gets played, then make a guess about the next song. Tuning is time consuming, labor intensive, and unfortunately error-fraught.

Tuning and re-tuning legacy EMPI solutions is not only costly, it’s ineffective. You can’t name that tune.

Automatically tuned to the entire U.S. population

It’s time to move to a modern person data management infrastructure that requires less time to implement and maintain, while delivering a much better match rate.

This is why I joined Verato. Our cloud-based, API-accessible universal master person index (UMPI) uniquely relies on reference data that we curate specifically for healthcare. Our embedded and continually updated national reference database spans the entire U.S. population. Each Verato reference identity contains a complete profile of demographic data spanning a 30-year history. It’s essentially a pre-built answer key for all patient demographic data.

We deliver a reliable UMPI that outperforms the bespoke algorithms that I and my fellow Verato employees (former Initiate artisans) used to configure, tune, and retune. With Verato Universal MPI, our customers are avoiding the entire cycle of retuning and related services.

Leading organizations like Texas Health Resources, Intermountain Healthcare, and Advocate Aurora Health have already made the move to Verato. They’re reaping the benefits of uniquely identifying each person using modern customer-oriented web services that are nimble to deploy, accurate at scale, and easy to maintain. Join us in making the leap to Verato!