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

Copyright © 2014 HCL Technologies Limited | www.hcltech.com

HCL – Healthcare Payer Solutions Fraud, Waste and Abuse Management

2 Copyright © 2014 HCL Technologies Limited | www.hcltech.com

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


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


HCL’s FWA Detection Solution Framework

Receive ClaimsClaims

Adjudication

Multidimensional Scoring Model

FWA Validation Services (PEGA)

Valid Claims

Valid Claims

Suspected Claims

PaymentPend for

SIUsPend for recovery

Pharmacy

Professional

Facility

Partner Component

HCL Components on PEGA Framework

LEGEND

Payment

Rule and Score Model Refinement

Dashboard ReportsHealth Plan,

Geography, Member, Provider

Alert Engine

SIUs for Investigation and Legal action

Recovery Management (PEGA)

Rule Engine(PEGA)

HCL component

Upstream/ DownstreamApplications


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 ROIFast-track recovery of lossesImproved 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


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


FWA Technical Architecture


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 monthtysabri 1x per monthdepo-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.


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 timeframeSample Rule Category2: Drug Gender Mismatch - Identifies drugs dispensed that are in conflict with the patient's genderSample 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 Codeo 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)


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


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


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


Low Score HighPrepayment 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 investigationsProvider/ 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


For Questions,Please Contact: [email protected]

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

Business

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