eValuator’s $31M Impact Validated Via 835 Remittance Analysis

eValuator 835 Case Study

OVERVIEW

After implementing eValuator, the client aimed to confirm its financial impact by analyzing 835 remittance data for inpatient claims in the calendar year 2023. A post-payment analysis comparing actual reimbursements with pre-billing predictions validated eValuator’s impact, demonstrating that correcting approximately 2,300 under-coded encounters increased cash for inpatient services by over $31 million.

CLIENT PROFILE

Client Profile 2

CHALLENGES

Validate Pre-Bill Financial Projections
Pre-bill projected reimbursements provided estimates of financial impact but not actual reimbursements across payors.

Quantify Bottom Line Impact
Without actual reimbursement data, it was challenging to validate eValuator’s true bottom-line impact to the executive team.

Validate Coding Accuracy Improvements
Actual reimbursement data from eValuator’s pre-billing coding changes was needed to verify coding accuracy improvements.

GOALS

Leverage 835 Remittance Data to Validate Pre-Bill Projections
Compare actual reimbursement data using 835 remittance data with eValuator pre-billing predicted impacts to confirm the accuracy of projections.

Aggregate Actuals by Payor to Quantify Bottom Line Impact
Quantify eValuator’s true impact on the organization’s financial performance and prove the return on investment to the executive team.

Validate Coding Accuracy for Potential Auditing Expansion
Confirm coding accuracy improvement to make a case for potentially expanding the audit staff to further optimize cash capture.

835 Validated Example 1

OUTCOMES

Graph2

Confirmed $31M Total Cash Impact
Analysis shows eValuator optimized around 2,300 under-coded encounters, capturing $31 million in cash and averaging $14K per correction.

Actuals Exceeded Pre-Bill Projections
The executive team concluded that actual financial impact exceeded eValuator’s
pre-bill projections.

Cost Avoidance & Savings
By identifying issues pre-bill, client avoided potential rebilling costs & contingency fees
of 20–40%, saving $6–12million from the $31 million.

My goal is and has always been about correct coding. I still wish we could push up our review numbers. Maybe this ROI will provide some leverage for additional staffing.
– Corporate HIM System Director

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