Radisson co-presented with Verato to share the story of how Verato’s customer matching solutions helped them overcome data integrity and legacy IT issues.
Tag: Data Quality
Webinar Recap: Patient matching is an often-overlooked piece of a patient-centered approach to care delivery
Read our recap of Intermountain Healthcare’s webinar on patient-centered approaches to care delivery and learn more about an often-overlooked approach: patient matching.
Don’t reinvent the wheel: Why your developers are wasting their time building master patient index technology for your health tech platform.
You’re a healthcare technology startup building the next-generation platform in care management, revenue cycle automation, electronic health records, population health, natural language processing. Don’t waste your developers’ time by having them build your master patient index patient matching technology.
The complex nature and navigation of clinical details, billing information, and ultimately insurance data requires herculean efforts on behalf of hospital administrators.
Population Health vendors are experts in predictive data models, risk stratification, data warehousing, reporting and a long list of other sophisticated technologies; patient matching isn’t one of them.
Read this blog post to learn what patient matching is and why it is important, as well as what Referential Matching technology is and how it can help solve our nation’s interoperability challenges.
IBM Initiate is a state-of-the-art master patient index (MPI) solution with best-of-breed patient matching capabilities. But it requires thousands or millions of potential matches to be manually reviewed. Learn how you can automatically match those potential matches, saving the time and effort of manual review.
It’s time for organizations to stop performing MPI cleanups. Verato offers a Referential Matching plug-in that works continuously to find and remediate duplicates an EHR or EMPI has missed, and that prevents duplicates from being created in the first place.
AHIMA16 – Stop Cleaning Your Identity Data! Achieve Interoperability of Patient Information Despite Dirty and Out-of-Date Data
Healthcare organizations perform large data quality exercises and enforce strict data governance standards in order to better match patient identities and improve interoperability. But there is a new way to match patient identities despite low quality data.
Traditional patient matching engines use patients’ names, addresses, and other identity data to link patient records together. But this data is constantly changing, making matching a challenge. This blog examines how you can accurately match patient records even if they contain out-of-date data.
A recent study published in the AHIMA journal “Perspectives in Health Information Management” analyzed what data errors cause duplicate patient records. But duplicates can be found and prevented without the need for data governance.
If you’ve ever renovated a house or bought a “fixer-upper,” you know all about sweat equity—it’s the painstaking investment of time and labor that goes into the project. What you might not know is when you buy a modern identity matching solution—whether a Master Data Management (MDM) or Master Patient Index (MPI) tool—you are signing up for more sweat equity than you realize.