Bind Benefits, Inc.

Matthew Chock

Shawn Wagoner

Glen Eiden

Matthew Wiandt

Trevor Fast

Anthony Miller

Henning Chiv

Jessica Zeaske

Charley Hastings

Jason Haupt

Nels Marcus Thygeson

David Dickey

Thomas Anton Klun

Benjamin Kowitt

Mark Peterson

Maxwell L Peterson

The Use Determination Risk Coverage Datastructure for On-Demand and Increased Efficiency Coverage Detection and Rebalancing Apparatuses, Processes and Systems ('UDRCD') transforms coverage enrollment request, event signal, ACGG request, search request, props ratios calculation request, encounters build request, episodes build request, price calculation request, price range generation request, price range lookup request inputs via UDRCD components into coverage enrollment response, add-in recommendation, ACGG response, search response, props ratios calculation response, encounters build response, episodes build response, price calculation response, price range generation resp., price range lookup resp. outputs. An episodes build request datastructure identifying an encounter type is obtained. An anchor encounter datastructure is selected. A set of other encounter datastructures for the anchor encounter datastructure is determined. A props ratio relevance function associated with the encounter type is determined, and used to determine a set of accessory encounter datastructures for the anchor encounter datastructure. An episode datastructure is generated.

Use determination risk coverage datastructure for on-demand and increased efficiency coverage detection and rebalancing apparatuses, processes and systems

The Use Determination Risk Coverage Datastructure for On-Demand and Increased Efficiency Coverage Detection and Rebalancing Apparatuses, Methods and Systems ('UDRCD') transforms coverage enrollment request, event signal, ACGG request, search request inputs via UDRCD components into coverage enrollment response, add-in recommendation, ACGG response, search response outputs. A set of clinical conditions is determined. A set of treatments is determined for each clinical condition. Treatment paths data that specifies a set of treatment paths, wherein each treatment path comprises an ordered subset of treatments, is determined for each clinical condition. Providers are determined for each treatment. Practice patterns data that specifies, for each clinical condition treated by each provider, how likely the respective provider is to utilize each of the treatment paths is determined. An atomized coverage graph data structure is generated that includes a set of clinical condition objects, a set of treatment objects, and a set of provider objects.

Use determination risk coverage datastructure for on-demand and increased efficiency coverage detection and rebalancing apparatuses, methods and systems

The Use Determination Risk Coverage Datastructure for On-Demand and Increased Efficiency Coverage Detection and Rebalancing Apparatuses, Methods and Systems ('UDRCD') transforms coverage enrollment request, event signal inputs via UDRCD components into coverage enrollment response, add-in recommendation outputs. A coverage enrollment request from a user is obtained. Available options for an enrollment user interface are configured based on the plan sponsor settings. Copay setting selections for individual core coverage services, atomized condition add-in selections, and atomized procedure add-in selections are obtained via the enrollment user interface. A core coverage cost and add-in coverage costs are calculated using the associated modeling data. A user cost for the user is calculated based on the core coverage cost, the subsidization settings for the core coverage cost, the add-in coverage costs, and the subsidization settings for the add-in coverage costs. The enrollment user interface is configured to display the calculated user cost for the user.

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Apple Valley, MN, United States of America

Matthew Chock