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Surprises in the No Surprises Act: An Interview with Greg Fann
is an update on the No Surprises Act, which is a U.S. Act aimed to reduce the risk that a person unexpectedly ... if it’s all right, we can also refer to it as the NSA. Greg Fann (GF): Thank you, Kristi. It’s good to ...- Authors: Kristi Bohn
- Date: Aug 2024
- Competency: Communication; External Forces & Industry Knowledge; Technical Skills & Analytical Problem Solving
- Publication Name: Health Watch
- Topics: Health & Disability; Health & Disability>Health insurance; Public Policy; Public Policy; Health & Disability>Claims - Health & Disability; Health & Disability>Provider networks
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Provider Risk-Sharing and Random Noise
paid to the provider. Table 1 breaks this down for dif- ferent size groups. Table 1 Sample Random Variation ... HMOs. Managed Care, Dec. 1, 2000. https://www .managedcaremag.com/archives/2000/12/downstream-without-paddle ...- Authors: Thomas Messer
- Date: Jul 2019
- Competency: External Forces & Industry Knowledge; Strategic Insight and Integration; Technical Skills & Analytical Problem Solving
- Publication Name: Health Watch
- Topics: Health & Disability>Health care; Health & Disability>Health care quality; Health & Disability>Payment models; Health & Disability>Provider networks; Health & Disability>Provider risk
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Give Me Some Credibility: Addressing the Challenge of Volatility in Value-Based Contracts—Part 2
improve credibility enough that a larger provider's own prior period experience can be used directly, ... for providers to trust. Questions of the form “it's not clear or fair that I should be measured based ...
- Authors: Maria Knox, James Pisko, Keith Passwater
- Date: May 2023
- Competency: External Forces & Industry Knowledge; Results-Oriented Solutions; Technical Skills & Analytical Problem Solving
- Publication Name: Health Watch
- Topics: Health & Disability; Health & Disability>Health care; Health & Disability>Health care quality; Health & Disability>Health insurance; Predictive Analytics; Health & Disability>Provider networks; Health & Disability>Provider risk; Predictive Analytics>Modeling techniques