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A routine Medicaid code update that surfaced $16M+ in lost revenue

Hired to add a state-mandated code to a health plan’s nursing facility file, our team noticed the process was mishandling records. The plan confirmed it, filed corrections with the state and recovered $16M+. We then rewrote the process to stop the loss.

Built onSQL Server

Industry
Healthcare
Engagement
Custom Development
A caregiver walking arm in arm with an older woman

A Medicaid health plan brought Smart Data in for a narrow job: update its Nursing Facility Level of Care (NFLOC) historic file process to handle a new retroactive code from the Ohio Department of Medicaid. That process sends nursing facility records for the plan’s members to the state, and what reaches the state shapes what the plan is paid.

While making the change, our team noticed records that did not add up. The process was mishandling some cases, and we believed it had been costing the plan revenue for some time. We said so.

The challenge

The file had been running for years, and nothing flagged the problem because nothing was technically failing. Records went out, some came back rejected and the gaps stayed quiet.

  • Records went to the state for members who were not eligible on the dates that mattered, so the state rejected them
  • Duplicate records with missing admission dates were sent again and again
  • Updates and deletes for members the state had no record of were resent on every file, and rejected every time
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The solution

  • A small Smart Data team, a developer and a business analyst with senior technical oversight, reviewed and reconciled the historical file
  • We showed the health plan where the process was mishandling records and why it was likely losing revenue
  • The plan’s own analysis confirmed it, and it sent adjusting files to the state
  • The plan then brought Smart Data back for an initial rewrite of the process in SQL Server, to stop the ongoing loss

The results

  • $16M+ in lost revenue returned to the health plan

  • Eligibility is checked against each member’s threshold and discharge dates before a record goes to the state

  • Duplicate records with missing admission dates are removed before the file is sent

  • Records the state has rejected as having nothing to update are no longer resent

Client

Industry

HealthcareInsurance

Platform and technology

  • SQL Server

Related services

Application development and modernizationData engineeringHealthcareInsurance

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  3. You get a written proposal

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