Denial Avoidance Flow

From Historical Denials to Proactive Claim Readiness

Decisive Connect helps teams learn from historical denial outcomes, approve the right intervention strategy, and resolve current charge issues before they become denied claims. The highest-value denial is the one that never occurs, because it avoids delayed reimbursement, claim resubmission, appeal overhead, and preventable operational work.

Claim History

What was billed

Historical claim activity shows the services, codes, modifiers, providers, locations, and payer context behind reimbursement outcomes.

Remittance Outcomes

What happened

Payments, adjustments, denials, remarks, and reason codes reveal where preventable revenue leakage occurred.

Current Charges

What is about to bill

Current charge activity is reviewed before claim submission to identify known conditions that create denial risk.

Denial Avoidance Process

Detect risk, resolve trusted issues, delegate exceptions, and prevent denials.

Historical outcomes and current workflow data reveal risk, governance defines the appropriate resolution path, and approved actions occur before issues become denied claims.

Step 01

Detect | Find exposure and patterns

Detect Revenue Risk

Analyze connected claims, remittance, charge, and workflow data to measure exposure, reveal recurring denial patterns, and prioritize the highest-value opportunities.

Step 02

Resolve | Automate approved actions

Resolve Trusted Risks

Apply client-approved automations to high-confidence risks, retaining the evidence, logic, action, and execution history needed for review.

Step 03

Delegate | Route work intelligently

Delegate Exceptions

Route true exceptions to the right people with supporting context while delegating repetitive resolution steps from manual queues to automation.

Step 04

Prevent | Act before submission

Prevent Denials

Review current charge activity against approved patterns and route each issue to the right resolution path before the claim is submitted.

Integration Model

Start Rapid. Expand Direct.

Decisive Connect can start denial avoidance with Rapid Connect, a lower-friction model that avoids the initial need for VPN connectivity, direct database users, and ODBC/JDBC setup. Direct Connect can be added over time for real-time access, broader data coverage, more robust analytics, and advanced workflow automation.

Rapid initial deployment

Provider-side EHR/RCM ops jobs create standard extracts, push them to Decisive Connect by SFTP, and receive automation-ready files back through the same lightweight exchange pattern.

Rapid start

Rapid Connect

EHR/RCM ops jobs -> extracts -> SFTP -> pipelines -> response files
  • Provider-controlled SFTP exchange
  • Scheduled EHR/RCM extract jobs
  • Standard file layouts
  • Pipeline activation on file arrival
  • SFTP return files for automation

Expanded model

Direct Connect

EHR/RCM systems -> VPN / API / ODBC/JDBC -> Decisive Connect
  • Direct network connectivity
  • Database or API credentialing
  • Expanded EHR/RCM data model coverage
  • Near-real-time workflow intelligence
  • More robust analytics and automation use cases

Revenue Leakage Assessment

Revenue Leakage Assessment powered by Rapid Connect

Rapid Connect creates a focused way to prove value before a broader deployment. The assessment can be offered as a fixed-fee engagement, credited toward implementation when the client moves forward, or waived for strategically qualified opportunities.

The model starts with Rapid Connect-based ingestion of historical claims and remittance data. Decisive Connect analyzes denial outcomes, applies AI/ML pattern detection, and maps recurring risk patterns to candidate automated resolutions that can prevent similar denials before claim submission, when the organization still has the best opportunity to protect reimbursement without downstream rework.

Assessment output

A quantified view of the client's largest denial problem areas, denied gross revenue exposure, and quick-hit automation opportunities that can accelerate time to ROI.

1

Ingest history

Historical claims and remittance files are delivered through Rapid Connect and normalized for analysis.

2

Detect risk patterns

AI/ML identifies recurring denial drivers, payer patterns, functional ownership, and preventable risk conditions.

3

Map automated resolutions

Patterns are mapped to candidate actions that could correct the issue before claim submission.

4

Quantify ROI

The assessment estimates denial volume, denied gross revenue, and high-confidence automation opportunities.

Lower onboarding friction

Avoid the initial lift of VPN connectivity, direct database access, database users, and network routing before value is proven.

Less vendor governance burden

SFTP extracts and HL7 interfaces can reduce dependence on heavier EHR/RCM vendor governance and pricing models tied to direct access patterns.

Revenue Leakage Assessment

Run AI/ML against historical claims and remittance data to quantify denial problem areas before a broader platform commitment is required.

Quick-hit ROI model

Identify high-confidence denial patterns and estimate the gross revenue exposure that could be mitigated by turning on automation early.

Historical data

Claims + Remits

837 claims, 835 remits, or RCM remit records.

AI/ML insights

Patterns + Risks

Denial drivers mapped by payer, workflow, category, and owner.

Automation path

Resolve Before Submission

Pattern-based resolutions become candidates for denial avoidance automation.

Rapid Connect Technical Flow

EHR / RCM Ops Jobs

Provider-controlled scheduled jobs produce standard extracts from the existing operational environment.

Claims, Remits, Charges

X12 837, X12 835, RCM remit records, and normalized charge extracts are prepared for transfer.

Inbound SFTP

Files are pushed to Decisive Connect without a VPN or persistent database connection.

Pipeline + AI/ML

Arrival triggers validation, normalization, denial analytics, pattern detection, and governed decisioning.

Outbound SFTP

Automation-ready files are returned for job interfaces, HL7 DFT workflows, or downstream work queues.

No VPN for initial launch

The provider pushes files out through a controlled SFTP pattern instead of opening a live database path.

Provider-owned extraction

Extract logic runs as approved EHR/RCM ops jobs and produces repeatable, normalized files.

Automation return path

Decisive Connect can return files for EHR/RCM job interfaces, operational work queues, or HL7 DFT workflows.

Governed Pattern Intelligence

Turn denial history into approved intervention paths.

Historical outcomes create a practical operating view of denial risk: where leakage starts, which teams own the workflow, which actions should happen earlier, and which interventions should be automated, reviewed, or monitored.

Quantified opportunity

Revenue Leakage Analysis

Quantify the client's largest denial and underpayment issues, then organize them by authorization, eligibility, medical necessity, coding, charge capture, credentialing, payer requirement, and other operational categories.

Root-cause signal

Pattern Intelligence

Identify recurring conditions that explain why denials are happening, where those risks originate, and what action can be taken earlier to avoid repeat leakage.

Operational control

Governed Intervention Paths

Give client stakeholders a clear approval model for deciding which scenarios can be resolved autonomously and which should be reviewed before action is delegated to automation.

Operating Model

A repeatable path from insight to prevention

  1. 1Historical claims and remittance outcomes establish where denials and underpayments are concentrated.
  2. 2Denial drivers are grouped into operational categories the revenue cycle team can act on.
  3. 3Repeatable patterns are mapped to actions that can be taken before claim submission.
  4. 4Stakeholders approve whether each pattern should be automated, reviewed, or monitored.
  5. 5Current charges are evaluated against approved patterns before they become claims.
  6. 6Outcomes are tracked so the governance model can adapt as payer behavior and workflows change.

Governance Model

Client-controlled automation boundaries

Autonomous automation

Low-risk, high-confidence scenarios approved for automatic correction before billing.

Review before automation

Scenarios that need human validation before a proposed resolution is approved or delegated.

Observe and measure

Emerging patterns monitored for volume, impact, and confidence before an intervention path is approved.

Pre-Bill Charge Review

Current charges are reviewed before they become claims.

Decisive Connect compares current charge activity against approved denial-risk patterns and routes each item into one of three operational paths based on risk, confidence, and governance approval.

Clear to Bill

The charge does not match a governed risk pattern and can continue through normal billing readiness workflows.

At Risk: Automate

The charge matches a high-confidence pattern approved for automatic correction before the claim is submitted.

At Risk: Review

The charge matches a denial-risk pattern that needs review, with recommended actions a user can approve, delegate, or route.

Outcome: prevent denials at the source

The denial avoidance flow moves the organization beyond retrospective reporting and into governed, proactive intervention. Historical outcomes show where risk exists, governance defines what can be automated, and current charge review resolves issues before claims go out the door. The result is fewer avoidable denials, less rework, fewer appeals, and faster reimbursement.