ReddRadar
What is Sift Healthcare?
Sift Healthcare equips healthcare organizations to fully leverage their payments data to optimize the financial performance of the entire revenue cycle continuum. The platform provides a unified and normalized view of payments data, enabling data-driven decision-making.
Sift captures insurance claim and patient financial data into a HIPAA-compliant, cloud-based, normalized database. This provides a single source of truth for healthcare payments. By applying multiple data science techniques, Sift offers comprehensive and integrated recommendations for denials management, payer assessment, patient collections, and patient acquisition.
Features
- Denials Prevention: Proactive identification of potential claim denials.
- Smart Claim Edits: Intelligent suggestions for claim modifications to prevent denials.
- Appeal Workflow Prioritization: Prioritizes denied claims based on the likelihood of successful appeal.
- Patient Financial Engagement Intelligence: Recommends patient-specific collection strategies.
- Unified Payments Data: Normalizes and consolidates payments data for comprehensive oversight.
- Rev/Track: Automated daily reporting with operational intelligence for all levels of a provider organization or RCM.
Use Cases
- Optimize payer reimbursement processes.
- Enhance patient payment collections.
- Prevent claim denials and improve overturn rates.
- Gain a unified view of all payments data.
- Improve revenue cycle management workflow.
- Automated daily revenue cycle performance tracking
FAQs
-
What data sources does Sift use?
Preferable sources of data include 837, 835 and payment files. -
How does Sift ensure data security?
Sift captures data into a HIPAA-compliant, cloud-based and normalized database.
Related Queries
Helpful for people in the following professions
Sift Healthcare Uptime Monitor
Average Uptime
100%
Average Response Time
214.9 ms
Featured Tools
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
