KelseyCare

CHALLENGES

  • Current EDPS submission solution was not very robust or stable. No easy way to upgrade as each customer was on their own build.
  • No visibility into the rejection rates, submission rates or error reasons.
  • Needed a solution that allowed them to edit without going back into their core claims system and manage the process better.
  • Submissions were close to two years behind … needed to clean up and catch up.

RESULTS

  • Client chose Babel Health because of the key understanding that a better way was needed to edit encounters without having to update the core claims system.
  • Eligibility, claims and provider operational teams can now access error correction directly.
  • Able to staff appropriately based on the new visibility. Learned that they needed one additional Level 1 analyst versus another senior analyst necessary with former vendor.
  • Submission and error rates have improved due to the ability to remap without having to request new builds.
  • Rely on a fully managed SaaS/cloud environment on AWS, allowing dynamic scale, business continuity, CMS-approved security, and HIPAA compliance.
  • Biggest highlight: working with a knowledgeable team that is far superior to what they dealt with previously.

New England Health Plan

CHALLENGES

  • Legacy EDPS/RAPS submission solution did not allow for any control over the submission process. The plan was wholly reliant on the vendor’s submission schedules and reporting capabilities.
  • Could not perform ad hoc or batch error correction without extensive technical efforts to modify data transformations from the core adjudication system.
  • Needed a solution that would minimize internal IT support requirements so those assets could be refocused on other strategic projects.

RESULTS

  • Client’s submission rates were dramatically improved — from 62% to over 98%.
  • The overall burden on the IT group was reduced as was the error correction effort.
  • Preliminary estimates on the long-term implications for both error correction and retrospective correction of encounter data suggest the client had an estimated $6 million in revenue at risk if the submission improvements not been made.