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Description
To protect sensitive information, including personally identifiable information (PII), organizations must implement techniques such as pseudonymization and anonymization for secondary purposes like comparative effectiveness studies, policy evaluations, and research in life sciences. This process is essential as businesses amass vast quantities of data to detect patterns, understand customer behavior, and foster innovation. Compliance with regulations like HIPAA and GDPR mandates the de-identification of data; however, the difficulty lies in the fact that many de-identification tools prioritize the removal of personal identifiers, often complicating subsequent data usage. By transforming PII into forms that cannot be traced back to individuals, employing data anonymization and pseudonymization strategies becomes crucial for maintaining privacy while enabling robust analysis. Effectively utilizing these methods allows for the examination of extensive datasets without infringing on privacy laws, ensuring that insights can be gathered responsibly. Selecting appropriate de-identification techniques and privacy models from a wide range of data security and statistical practices is key to achieving effective data usage.
Description
Verana Health operates as a platform for real-world data that converts both structured and unstructured information from electronic health records into curated, de-identified, disease-focused data modules through its clinician-informed and AI-enhanced VeraQ population health data engine. By aggregating data from key collaborations with prominent medical registries, including the American Academies of Ophthalmology, Neurology, and Urological Association, the platform integrates insights from over 20,000 clinicians and approximately 90 million patient records, thereby supplying high-quality datasets in near real-time for the purposes of generating real-world evidence, identifying clinical trial sites and subjects, reporting clinician quality, and managing medical registries. Users can access this wealth of information through cloud services like AWS Data Exchange and Amazon Redshift, which provide self-service API access, a user-friendly dashboard, and tools for customizable cohort discovery. Furthermore, the system employs advanced AI and machine learning algorithms along with comprehensive data quality assessments to ensure the reliability and accuracy of the information provided. This innovative approach not only facilitates efficient data utilization but also enhances the overall quality of healthcare research and practice.
API Access
Has API
API Access
Has API
Integrations
AWS Data Exchange
Amazon Redshift
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Fasoo
Country
United States
Website
en.fasoo.com/products/analyticdid/
Vendor Details
Company Name
Verana Health
Country
United States
Website
veranahealth.com
Product Features
Product Features
Population Health Management (PHM)
Analytics
Cost-of-Care Analysis
Data Storage
EMR/EHR Integration
Patient Engagement
Patient Identification
Patient Risk Stratification
Patient-Reported Outcomes
Payment Bundling
Predictive Alerts
Test & Treatment Reminders
Utilization Tracking