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Rev/Engage Predictive Patient Payment Management

Rev/Engage Predictive Patient Payment Management

Rev/Engage Predictive Patient Payment Management

3 verified clients
Rev/Engage Predictive Patient Payment Management
Rev/Engage Predictive Patient Payment Management

Overview


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Avia Summary

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Rev/Engage Predictive Patient Payment Management is a solution provided by Sift Healthcare which was founded in 2017. It belongs to multiple categories of digital health solutions including Patient Billing & Payment and Revenue Cycle Management.
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It has 3 verified clients.
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Rev/Engage Predictive Patient Payment Management integrates with major EMRs such as Epic, Cerner, and Meditech.
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Some other resource(s) that may be helpful in learning about Rev/Engage Predictive Patient Payment Management include: Q&A with Dominic Foscato of Sift: A data-driven approach to financial engagement and Top Patient Billing and Payment Companies Report | 2023
DESCRIPTION

For hospitals, it is 4x harder to collect from patients than insurance payers. Patients now make up to 30% of hospital revenue but are 4x harder to collect from than insurance payers1 due to complexity, regulation and patient means. 

Sift Healthcare provides advanced analytics and machine learning integrations to optimize patient payments. Sift combines patient payment expertise and AI-driven intelligence to equip providers with an integrated toolset to optimize patient financial engagement.

Patient collections should be a dialogue, not a solicitation. Sift integrates AI into your patient engagement platform to guide patient communications activities – maximizing collections while improving patient engagement.

  • Account Segmentation
  • Patient Contact Strategy
  • Payment Plan Provisioning
  • Improved collections, increased payment plan adoption, and reduced inbound/outbound calls

Propensity-to-pay for a person, not a number. Sift goes beyond credit scores, leveraging historical data to determine the best engagement approach for each patient.

  • Improved Patient Satisfaction
  • Pre-service patient financing and collection recommendations that help avoid surprises and set expectations
  • Lookalike predictive models, not credit scores and rule logic
  • Increased upfront collections with more empathy
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EHR integration

Acute care EMR, Ambulatory EMR, Patient portal, Access +/or revenue cycle
None provided
Epic, Cerner, Meditech, Allscripts
None provided
Use cases and differentiators

Sift's intelligence tools and integrated ML recommendations around patient payments enable health systems to:

  • Pre-clear patients upfront.
  • Get more patients on payment plans, earlier.
  • Execute omnichannel contact across the entirety of the patient journey.
  • Help patients commit to meeting their financial obligations before service.
  • Utilize an integrated view of insurance-patient responsibility to optimize resolution and present patient responsibility, early and more accurately.

VP or Revenue Cycle, PFS executives, PFS team, SBO and CBO personnel, Patient Payment Collections Team

  • Unified and normalized data sets that are accessible and provide a full view of patient payment behavior 
  • Dynamic machine learning based workflows, rather than rigid rules-based logic
  • Intelligence that enables the most effective use of EHR functionality 
None provided
Company information

Founded in 2017

2.5M total equity funding

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  • AMC
  • Pediatric Facilities
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