Fraud, Waste & Abuse : HCL’s Intelligent Rule Based Solution
-
date post
18-Oct-2014 -
Category
Business
-
view
280 -
download
0
description
Transcript of 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
3 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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
5 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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
6 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
FWA Technical Architecture
8 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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.
9 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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)
10 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
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
14 Copyright © 2014 HCL Technologies Limited | www.hcltech.com
For Questions,Please Contact: [email protected]
15 Copyright © 2014 HCL Technologies Limited | www.hcltech.com