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Description
Kelmar’s KAPS system for managing unclaimed property is a highly scalable and configurable Software as a Service (SaaS) solution designed specifically for governmental unclaimed property initiatives. This platform empowers administrators to oversee every stage of the process, beginning with the input of reports and receipts and continuing through due diligence mailing, escheatment, claims processing, and payment execution, all through a relational database interface that emphasizes system configurations instead of custom coding. KAPS is compatible with public-facing state websites and incorporates cloud-based document imaging, automated outreach to owners, integrated LexisNexis verification for identification, and utilizes the Kelmar Fraud Index for AI-driven risk assessments. The system is provided with secure, industry-standard authentication measures and is subjected to annual audits for SOC 2 Type 2 and ISO 27001:2022 compliance, alongside possessing GovRAMP authorization. Furthermore, additional features enhance processes related to auction closures, allow for manual online reporting for smaller holders, and facilitate the management of tangible property, ensuring a comprehensive approach to unclaimed property management. Each of these elements contributes to a more efficient and transparent handling of unclaimed assets, making it a vital tool for governmental entities.
Description
LexisNexis Health Equity and Inclusion Insights offers an extensive and actionable dataset focused on the social determinants of health (SDoH) at the individual level. This valuable information empowers healthcare organizations to enhance population health, advance clinical research, and pursue initiatives aimed at promoting health equity. By highlighting obstacles to care, the solution aids in refining care delivery and fostering more equitable healthcare choices, alongside developing diverse clinical research programs. It supplies de-identified datasets that can be integrated with other such datasets through LexisNexis Gravitas, a tokenization tool that utilizes a referential data layer for accurately matching de-identified records from various sources. Achieving health equity hinges on the ability to pinpoint health barriers and predictors of adverse health outcomes, allowing for targeted interventions that can positively impact individual patients. Ultimately, this focus on precision and actionable insights can lead to improved health outcomes across entire communities.
API Access
Has API
API Access
Has API
Integrations
KSS Call Manager
LexID
LexisNexis Instant Verify
LexisNexis Property Data
Integrations
KSS Call Manager
LexID
LexisNexis Instant Verify
LexisNexis Property Data
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
Kelmar
Country
United States
Website
www.kelmarassoc.com/unclaimed-property-solutions/management-systems
Vendor Details
Company Name
LexisNexis
Country
United States
Website
risk.lexisnexis.com/products/health-equity
Product Features
Product Features
Clinical Trial Management
21 CFR Part 11 Compliance
Document Management
Electronic Data Capture
Enrollment Management
HIPAA Compliant
Monitoring
Patient Database
Recruiting Management
Scheduling
Study Planning
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