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.
Tag: Data Quality
It’s time for organizations to stop performing MPI cleanups. Verato offers a subscription service that lets organizations prevent 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 Achieve Interoperability of Patient Information Despite Dirty and Out-of-Date Data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 This blog examines how you can accurately match patient records even if they contain out-of-date data.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 Data Quality (DQ), Master Data Management (MDM), or Master Patient Index (MPI) tool—you are signing up for more sweat equity than you realize.