Improve Your MPI Search
Save time and money by finding the right medical records faster with intelligent name matching
11.4 seconds saved per search*
An individual record lookup may not seem to take long, but each second spent searching for patients adds up. Fuzzy name matching mitigates the three most common errors that lead to missed searches for patient records:
- Misspelling/phonetic misunderstanding
- Nicknames, non-English names
- Incomplete/inaccurate records
*Average observed in customer proof-of-concept. Customer experience varies depending upon their database.
Intelligent Name Matching
Rosette finds potential matches in the database regardless common record errors like nicknames, misspellings, names split inconsistently across database fields, solving thirteen name phenomena across fifteen languages.
Rosette names search presents all likely matches for each search query based on a predetermined match score threshold. Possible matches are ranked from most to least likely, allowing hospital staff to review the results and ask the appropriate follow-up questions to find the right patient record faster.
A hybrid solution, Rosette’s trusted blend of machine learning and traditional name matching techniques has improved name search for the world’s thorniest name matching challenges for over 15 years.
- Increase productivity: Tracking down and merging records wastes time. With Rosette, you can find the right patient’s record even if it contains incomplete or inaccurate data.
- Reduce duplicate records: Rosette’s fuzzy matching decreases the likelihood that human errors like misspellings, linguistic and cultural differences, and inverted name fields will lead staff to create duplicate records.
- Protect patient data: Maintain HIPPA compliance and go beyond, protecting patients’ privacy and retaining their trust.
- Decrease costs: Resolving duplicate records costs more than you think.
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Frequently Asked Questions
How does Rosette improve patient identification?
Rosette makes the most common challenges of accurate patient identification (missing data, misspellings, and non-Latin names, etc.) irrelevant by returning results that are semantically or phonetically similar to the search terms instead of only exact matches.
What are Rosette’s patient identifiers?
Rosette's fuzzy matching identifies related names including culture-unique variations, nicknames, misspellings, names with missing or out of order components, semantically or phonetically similar names, and translations of multilingual names. It can also be used in conjunction with other search fields, such as date of birth, address, or social security number.
What are the risks of failed patient identification?
Failing to properly identify and connect patient records can result in the creation of costly duplicate records, failure to accommodate patients' known allergies or medication, or the wrongful disclosure of patients' protected health information.
How does name matching prevent HIPAA violations?
HIPPA violations are extremely costly for healthcare providers both in terms of monetary fines and reputation damage. Intelligent name matching ensures that staff finds the correct patient record on the first try, preventing the accidental disclosure of PHI to the wrong party.