Health Data Quality

Clean Clinical Data Unlocks the Value of Personalized Medicine, Life Sciences Research, Drug Discovery & Collaboration

Real-world clinical data is unusually valuable, but it is also unusually complex and diverse. Because even the most disciplined clinical practices will generate dirty data, Melissa Informatics provides the tools for data quality improvement to help:

  • Improve patient care and support precision medicine research
  • Turn data from EMR records (digital or print format) into revenue and improved care
  • Connect multiple, disconnected
  • Realize new intellectual property from clinical practice data
  • Capture and report research quality clinical trials data at a lower cost
  • Achieve unexpected new revenue by making the most of your clinical data

Knowing your own data and leveraging data to continuously improve data quality is the key to success. Melissa Informatics combines over 30 years of deep domain knowledge and expertise in contact data quality and entity resolution, combined with the latest machine reasoning and machine learning techniques to provide the best AI-enabled products to solve the most complex data quality problems you face.

Health Data Quality & Cleansing Request More Information

Case Study: Parkinson’s Institute and Clinical Center (PICC)

PICC employed Melissa Informatics Sentient software to integrate and harmonize data from internal and external sources for new application development, publication and innovative revenue-bearing relationships.

Melissa Informatics Health Data Quality Solutions

Sentient Suite Visually access, explore, query, and report your data from multiple sources to uncover hidden relationships and stimulate innovation. Learn More
Druginator Autcomplete drug names during data entry and add additional information about drugs or lists of drugs to improve health data quality and patient care. Learn More
Knowledge Hub Access the most useful, comprehensive, integrated data (“content”), terminology standards (“lexicons”) and semantic data models (“ontologies”) for drugs, genes, proteins and diseases. Learn More
Contact Data Quality Validate, correct and standardize an individual’s name, address, phone and email, and merge duplicate records for a 360-degree view of patient information.
Identity Verification for Patient Onboarding Verify an individual’s identity including SSN/National ID check, age verification and date of birth/date of death.
Location Intelligence and Data Enrichment for Population Health Add latitude/longitude coordinates to postal addresses, property and demographic data for insight and analysis.