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Fraud, Waste & Abuse : HCL’s Intelligent Rule Based Solution


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As health care costs keep escalating, the potential for fraud, waste, and abuse does, too. The White House has reported total recoveries over the past three years (ending in 2011) to the tune of $10.7 billion. Also, the number of individuals charged with fraud rose from 821 in fiscal year 2008 to 1,430 in fiscal year 2011 – a nearly 75% increase.

HCL has developed a fraud, waste and abuse management framework, enabling customers to benefit from either the full power of an End-to-End framework or a point solution that caters to specific issues. HCL’s Fraud, Waste & Abuse (FWA) Management Solution offers services supported by analytical tools that helps the Payer/PBM handle the issue of increasing healthcare fraud, waste and abuse.

Leverage HCL’s intelligent rule based FWA solution to proactively identify potential fraud cases, wasteful and abusive billing practices and avoiding pay and chase scenarios. To learn more, please visit:

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Fraud, Waste & Abuse : HCL’s Intelligent Rule Based Solution

  1. 1. Copyright © 2014 HCL Technologies Limited | HCL – Healthcare Payer Solutions Fraud, Waste and Abuse Management
  2. 2. 2 Copyright © 2014 HCL Technologies Limited | Payer Pain Points and Current Market trends COST IDENTIFYING FRAUD, WASTE AND ABUSE RULE LOGIC USED TO IDENTIFY, RECOVER & PREVENT FWA LOSSES  1 in 5 claims are erroneously paid out because of abuse, fraud or wastage  Through “Pay and Chase” Payers recover only a fraction of the dollars lost in Fraud, Waste and Abuse(FWA)  Health plans are being challenged to operate within a 15 to 20 percent MLR and as such, pay and chase technology only adds to increased costs  Presence of Multiple systems and entities in a Payer environment makes it cumbersome to determine fraud  Limited size of investigation team is a constraint in FWA detection  Processing errors adds to the delay in determining FWA  Rule logic is the health plan’s first line of defense after adjudication.  Provides actionable logic for the plan to prevent losses either through a pre-payment denial or a fast tracked audit post-payment.  Rule logic must be adaptable to address health plans financial risks due to various payment modalities and contract requirements.  Rule logic enables HCL to address these needs for all types of claims, Rx, Professional, Facility, DME, etc. MARKET DATA  Market expenditures on FWA $68-$226 Billion (2011). Spend projected to increase to $360-390 billion by 2014 and $458 billion by 2019 Reported on May 29, 2012 in Semiannual Report to Congress  $1.2 Billion in recoveries for the first half of FY2012  $483.1 Million in audit receivables  $748 Million in investigative receivables
  3. 3. 3 Copyright © 2014 HCL Technologies Limited | HCL’s FWA Management Service Line Components Rule Engine Scoring Engine Reports/ Dashboards Workflow Management Claims Validation Recovery Services Special Investigation Services Automated Prepayment Denials Net New Rules Development CLAIMS OPS/ QA CONTRACT MANAGE- MENT NETWORK MANAGE- MENT Identification Recovery Prevention MEDICAL MANAGE- MENT
  4. 4. 4 Copyright © 2014 HCL Technologies Limited | HCL’s FWA Detection Solution Framework Receive Claims Claims Adjudication Multidimensional Scoring Model FWA Validation Services (PEGA) Valid Claims Valid Claims Suspected Claims Payment Pend for SIUs Pend for recovery Pharmacy Professional Facility Partner Component HCL Components on PEGA Framework LEGEND Payment Rule and Score Model Refinement Dashboard Reports Health Plan, Geography, Member, Provider Alert Engine SIUs for Investigation and Legal action Recovery Management (PEGA) Rule Engine (PEGA) HCL component Upstream/ Downstream Applications
  5. 5. 5 Copyright © 2014 HCL Technologies Limited | HCL’s FWA Detection Solution Framework – Continued… Scoring Model identifies aberrant claim line billing and assigns an aberrance score to the line providing a reason code.. This identifies new and emerging patterns of FWA that the payer is unaware of within their claim data. Claims are sent to the auditor for review. Auditor validates services billed verses services documented/rendered. Audit findings are presented to provider and plan then proceeds to Claim Recovery Services to recover overpayments. Provides: Improved ROI Fast-track recovery of losses Improved SIU referrals Claim Validation Services Claims identified for recovery of overpayments are sent to recovery analyst Internal & External Data Sources Referral of suspicious claims to SIU for case investigations Communication of audit outcomes to key stakeholders: Medical management, Provider Contracting, Network Management, Claim Operations • Rule Engine • Scoring Model Rule Engine identifies inappropriately billed claim lines and will deny or suspend the claim line preventing losses from going out the door. Claim Recovery Services Reports & Dashboards SIUs
  6. 6. 6 Copyright © 2014 HCL Technologies Limited | HCL FWA Sample Rule Categories Healthcare Fraud Prevention & Detection Rules BILLING ERRORS  Drug-Place of Service Mismatch  Drug Not covered for Age  Drug Not covered for Gender  Prior Authorization COVERAGE RELATED ABERRANCIES  Drug Not covered  Drug-Season Mismatch  Pregnancy-Drug Conflict  Drug-Disease mismatch  Drug-Specialty mismatch  Drug-Drug Interactions  Drug-Supplies Mismatch COVERAGE RELATED ABERRANCIES  Drug Not covered  Drug-Season Mismatch  Pregnancy-Drug Conflict  Drug-Disease mismatch  Drug-Specialty mismatch  Drug-Drug Interactions  Drug-Supplies Mismatch BILLING ENHANCEMENTS  Contractual billing enhancements  Billing for non-rendered services  Re-billing and/or Duplicate billing PAYMENT METHODOLOGY BASED BILLING  Per diem  Fee for service  % of charges INPATIENT STAY ABUSE  Pattern of billing for outlier days for inpatient services UTILIZATION MANAGEMENT  Drug usage  Medical device usage OVERUTILIZATION  Identifies patterns of excessive quantity per timeframe OUTPATIENT BILLING DURING INPATIENT STAY  Billing of outpatient services required for inpatient admission  Pre-Admission tests UP-CODING OF SERVICES  Billing of relatively higher level of services than actual UNBUNDLING  Increased billing by billing comprehensive and component procedures at the same time NON-COVERED SERVICES  Unlisted and/or Expired services  Potentially Cosmetic and/or Investigational services Rx Claim Rules Facility Claim Rules
  7. 7. 7 Copyright © 2014 HCL Technologies Limited | FWA Technical Architecture
  8. 8. 8 Copyright © 2014 HCL Technologies Limited | Sample Rules Categories RULE CATEGORY DESCRIPTION SCENARIO RULE SCENARIOS Overutilization Identifies patterns of excessive qty per timeframe indicative of fraud/ abuse Overutilization of controlled substances Total quantity is captured through the NDC and the number of units. We can find out the dosage consumed per day through the historical analysis. If the dosage consumed is greater than the recommended dose we will pend that claim for review. Drug-Gender Mismatch Identifies drug dispensed that are in conflict with patients’ gender Oral contraceptive for men and Caverject Injection for women Identify patients where drugs consumed are not matching with patients’ gender. Drug- Pregnancy Conflict Identifies drugs which should not be prescribed while the patient is pregnant Premarin given in pregnancy Identify patients who are dispensed pregnancy contraindicating in their pregnant state. Excessive Frequency Identifies the drugs which have a minimum recommended time interval (in days) synagis > 1x per month tysabri 1x per month depo-provera q3 months Identify claims where minimum recommended time interval is being breached by looking on to their historical claims Clients can customize rule logic to meet their business requirements. All custom rule logic would be the responsibility of the client to maintain coding changes and business logic updates. HCL will provide coding updates and maintenance.
  9. 9. 9 Copyright © 2014 HCL Technologies Limited | Rule Engine Use Case 1 Use Case: Rule Engine should be able to accept and process the claim file to identify the suspicious claims along with claim status and reason code Sample Claim file (xml)  Accepts claim files in real- time  Take batch upload for retrospective analysis Sample Rule Category1: Overutilization - Identifies patterns of excessive quantity per timeframe Sample Rule Category2: Drug Gender Mismatch - Identifies drugs dispensed that are in conflict with the patient's gender Sample Rule Category3: Drug Pregnancy Conflict - Identifies drugs that are contraindicated in pregnancy OUTPUT Claim file with:  Claim status (Paid, Denied, Pending). If denied or pending then, o Reason Code o Reason Description SALIENT FEATURES  Validate each claim line in the claim  Identify suspicious claims based upon previous trends and patterns based upon the historical data available  Different versions of rule set can be maintained  Execution order of the business rule category in the engine is customizable  Capability to handle filters and exclusions INPUT IN BUSINESS RULE ENGINE PROCESS Claims Processing Systems (FACETS, AMISYS)
  10. 10. 10 Copyright © 2014 HCL Technologies Limited | Rule Engine Use Case 2 SALIENT FEATURES  Report can be filtered based on claim status as Pend or Clean  Report would consist of the following details: Claim details, Reason code for which the claim is flagged, Rule ID, Drug details, Patient details, Provider details, Pharmacy details  Report can be saved in pdf and excel format Use Case: To generate the report to identify the suspicious claims that have been flagged by the business rule engine
  11. 11. 11 Copyright © 2014 HCL Technologies Limited | Validation Services - Use Case 1 Use Case: The Auditor reviews the flagged claim for accuracy and determines the need for additional documents to perform validation services SALIENT FEATURES  Validate each claim line in the claim  Conversation Log and case history of the claim is maintained  Audit log is maintained for every user action  All the attachments related to the claim can be viewed  Users can search NDC, Member, Provider, Pharmacy and Rules User selects from the list of assigned claims visible in the work queues displayed on the dashboard User would review the following:  Flagged Claim line(s )  Provider details  Pharmacy details  Member Details  Provider contractual data  Member benefit details  Reason code for flagged claim line(s) User can take the following actions on the claim –  Resolve billing issue with current data  Request additional medical documentation  Create Audit Finding Report  Generate Audit Finding Report to Payer  Transfer the claim to SIU/ Medical Management, etc. if necessary for further review  Transfer claim to recovery management team  Notify provider of audit findings  Track and report recoveries  Close claim audit
  12. 12. 12 Copyright © 2014 HCL Technologies Limited | Value of Rules  Client experiences immediate ROI upon implementation  Automated process – reduction in administrative costs  Prevention of losses pre-payment  Avoidance of “Pay and Chase”  Fast-tracked identification of post-payment audit opportunities  Payer has the ability to move audit findings to pre-payment rule logic through net-new custom rules identified through the audit process
  13. 13. 13 Copyright © 2014 HCL Technologies Limited | Low Score High Probability of Fraud Prepayment Prevention of losses Higher waste and abuse recoveries Better referrals to SIU Business Benefits Increase throughput with FWA Validation Services ROI Provides integrated system payment determination on claim lines Rules Engine Claims recommended for payment are sent through Scoring Engine Present Score and Reason Descriptions Scoring Engine Aberrant claim lines are identified and sent for FWA Validation Services Investigation and identification of fraudulent provider/ member schemes Special Investigation Units Improved FWA investigations Provider/ member profile capabilities Overpayment validation – further investigation by BPO teams FWA Validation Services Validation Recommendation: • Payment • Pend • Deny BPO Validation services includes recovery management and claim adjustment to reflect findings
  14. 14. 14 Copyright © 2014 HCL Technologies Limited | For Questions, Please Contact:
  15. 15. 15 Copyright © 2014 HCL Technologies Limited |