What to consider before investing in a data normalization engine
Integrating a healthcare data normalization engine into any health IT workflow is a big commitment. Check out our checklist of factors to help guide your decision.
IMO Precision Normalize is built on domain-specific NLP to extract, standardize, and enrich free text and structured clinical data.
Clinical patient data is a powerful resource in healthcare. But, as the healthcare IT ecosystem grows in complexity, data is more plentiful and problematic.
As patient data moves across various health information systems, it can become highly variable and lose key components. This leads to a drain on IT, analytics, and clinical resources, as staff must spend more time manually filling in the gaps.
Identifies and understands the presence, absence, or possibility of the clinical concept.
Uncovers connections between clinical concepts throughout the text.
Extracts time-related details associated with the identified clinical concepts.
Identifies sections within clinical narrative to add context and organization to extracted entities.
Comprehensively maps clinical concepts to IMO terms and all relevant standard codes.
(AWS, Azure, GCP)
ICD-10-CM (default), ICD-9-CM, SNOMED CT®
CPT® (default), HCPCS, ICD-10-PCS, SNOMED CT, LOINC
RxNorm® (default), NDC, CVX
LOINC (default), CPT, HCPCS, ICD-10-PCS, SNOMED CT
SNOMED and SNOMED CT® are registered trademarks of SNOMED International. CPT is a registered trademark of the American Medical Association. All rights reserved. RxNorm® is a registered trademark of the National Library of Medicine.
