Cost of poor data quality in registration leading to denials and patient complaints
Definition
Data quality failures at registration—misspelled names, wrong DOB, incorrect plan or network, missing prior auth flags—cause preventable claim denials and billing errors that must be reworked or written off. These errors also drive patient complaints and refund processing when patients are billed incorrectly.
Key Findings
- Financial Impact: Given that almost half of denials are linked to registration and eligibility errors, and each denial costs an estimated $25–$118 to rework, hospitals can incur hundreds of thousands of dollars annually in rework and refunds attributable to poor registration data quality.
- Frequency: Daily
- Root Cause: Lack of standardized data capture; limited validation at the point of registration; failure to use automated eligibility and demographic checks; and insufficient quality monitoring of front‑end processes.
Why This Matters
This pain point represents a significant opportunity for B2B solutions targeting Hospitals.
Affected Stakeholders
Patient access leaders, Registration staff, Revenue integrity and quality teams, Patient financial services, Patient experience/complaint handling teams
Deep Analysis (Premium)
Financial Impact
$100,000–$400,000 annually (rework + refund overhead) • $100,000–$400,000 annually (WC claims complex; rework cost $60–$118 per case; high admin overhead) • $100,000–$500,000 annually (1-5% error rate × volume × $25–$118 rework cost)
Current Workarounds
Analyst calls payer to clarify coverage; contacts provider/patient to correct info; resubmits manually • Analyst calls payer to verify eligibility; requests patient info from ED staff; manually resubmits; tracks in log • Analyst contacts employer/WC insurer to verify; manually resubmits; tracks in WC case log
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Methodology & Sources
Data collected via OSINT from regulatory filings, industry audits, and verified case studies.
Evidence Sources:
- https://iha.org/performance-measurement/encounter-data-improvement/resources/patient-insurance-eligibility-training/
- https://www.experian.com/blogs/healthcare/insurance-verification-in-healthcare-why-accuracy-and-speed-matter/
- https://rcmcentric.com/essential-steps-for-accurate-patient-registration-updating-and-verifying-patient-information/
Related Business Risks
Claim denials and write‑offs from faulty registration and eligibility data
Excess labor and rework to fix registration and insurance errors
Delayed payment and extended AR from slow or missed eligibility verification
Throughput bottlenecks from manual registration and insurance checks
Regulatory and payer compliance risk from inaccurate eligibility and registration data
Opportunistic misuse of insurance due to weak identity and coverage verification
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