Selected Case Types
Methodology
Our proven hardware and software approaches scale easily to meet the requirements of multi-terabyte data sources and deliver valuable data intelligence by rapidly analyzing, correlating and mining large and complex data sets from vastly different sources.The following list represents a sample of the types of cases we have supported or are currently supporting. Click the links below to learn more or contact us directly for case specifics and other details.
- AWP drug over-pricing
- Best price violations
- Diagnostic radiology/testing
- Durable medical equipment
- Federal contractor
- Federal grantee
- Home health agency
- Inappropriate hospital admissions
- Inappropriate surgical procedures
- Kickbacks
- Medical transportation
- Off-label prescription marketing
- Part D prescription drug benefit
- Pediatric dentistry
- Physical therapy
- Services not rendered
- Software manipulation
- Unbundling
- Up-coding
Case Details
- AWP drug over-pricing
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- Integrate defendant and wholesaler transaction data to determine “but-for” prices
- Perform claim-by-claim re-adjudication, overpayment calculations, and extrapolations on hundreds of millions of Medicaid and Medicare claims
- Contribute to expert and rebuttal reports
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- Best price violations (bundling)
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- Develop alternative bundling models
- Construct bundles using defendant transaction data
- Unbundle to calculate “but-for” best prices and “but-for” unit rebate amounts
- Apply “but-for” URAs to utilization and calculate damages
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- Best price violations (line-item pricing)
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- Identify “but-for” best prices in defendant transaction data and calculate “but-for” unit rebate amounts
- Apply “but-for” URAs to utilization and calculate damages
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- Diagnostic radiology/diagnostic testing
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- Perform peer review and other statistical analyses
- Identify changes in behavior patterns over time associated with significant events (acquisition, sale, investigations, etc.)
- Calculate damages
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- Durable Medical Equipment
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- Analyze defendant accounting, transaction, tracking, and shipment data to identify falsified doctors’ orders
- Calculate damages
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- Federal contractor
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- Integrate defendant accounting, credit card, timekeeping and other data sources to reconstruct Public Vouchers (invoices) submitted to the federal government
- Analyze and quantify internal inconsistencies
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- Federal grantee
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- Analyze defendant transaction data to identify and characterize misuse of federal funds
- Analyze defendant accounting data to identify additional areas of grant non-compliance
- Calculate damages
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- Home Health Agency
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- Integrate government claims data and third-party audit data to estimate volume and costs of services not meeting home-bound and/or medical necessity standards
- Calculate damages
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- Inappropriate hospital admissions
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- Analyze billing patterns, lengths of stay, and other factors associated with inpatient, outpatient, and emergency department claims
- Calculate damages
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- Inappropriate surgical procedures
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- Analyze relevant, comprehensive national data and complete patient claim histories to identify potentially inappropriate procedures
- Identify outlier hospitals and systems
- Quantify potential damages
- Support statisticians, medical experts, and chart reviewers
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- Kickbacks (physician/hospital)
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- Identify patterns and relationships evident in physician/hospital claims data
- Identify changes in patterns and relationships over time
- Calculate damages
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- Kickbacks (pharmaceutical manufacturer/physician)
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- Integrate defendant accounting and government claims data to identify, characterize and quantify changes of behavior related to payments and other inducements to physicians
- Calculate damages
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- Medical transportation
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- Analyze claims data to identify inconsistent or impossible services
- Identify outlier providers
- Calculate damages
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- Off-label prescription marketing
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- Develop models to identify a variety of off-label mechanisms, including high dosing, claims of superiority, unapproved uses, and unapproved combinations of drugs
- Calculate damages
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- Part D prescription drug benefit
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- Identify and re-price incorrectly billed drugs
- Perform claim-by-claim re-adjudication of Prescription Drug Event data and re-apportion corrected prices among payors
- Calculate damages
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- Pediatric dentistry
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- Analyze Medicaid data to identify and characterize age/procedure/quantity inconsistencies
- Calculate damages
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- Physical therapy
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- Identify outlier behavior
- Identify up-coding
- Extrapolate damages based on error rates
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- Services not rendered
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- Integrate defendant claims, appointment, and accounting data to identify improbable daily procedure quantities
- Calculate damages
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- Software manipulation
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- Analyze changes to source code over time
- Perform automated regression testing to identify impact of changes over time across many parameters
- Identify thresholds and boundaries of expected results
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- Unbundling
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- Identify outlier behavior
- Identify and quantify patterns of billing over time to establish baseline behaviors
- Calculate damages
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- Up-coding (diagnostics and physician services)
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- Quantify and characterize anomalous billing patterns
- Identify trends over time
- Calculate damages
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- Up-coding (DRG)
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- Identify outlier behavior
- Identify and quantify causality relationships between admission diagnoses and DRGs over time
- Establish peer norms
- Calculate damages based on causality and peer norms
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