Relationship Mapping

Identify hidden relationships that may indicate healthcare fraud


Identify key players, connections, and frequently missed patterns of behavior indicative of healthcare fraud.

Healthcare is a prime target for fraudsters. Healthcare fraud schemes evolve as frequently as relationships do, becoming more complex and wide reaching. Relationship Mapping looks beyond claims for healthcare fraud schemes that are often difficult to uncover due to the intricate nature of relationships.

Competing priorities and shrinking budgets leave healthcare organizations at a disadvantage, making it difficult to:

  • Find links among and between social groups
  • Uncover larger and hidden schemes
  • Detect non-network individuals or entities exposing them to risk
  • Surfacing social relationships warranting further investigation 

 This escalating threat requires greater transparency, stronger analytics and insights into claims, provider and identity information to identify possible healthcare fraud and collusion. The dangers of not addressing healthcare fraud include patient safety, cost inefficiencies, missed recoveries, and reputational risk.

 

Relationship Mapping is an advanced analytic, linking and visualization solution from LexisNexis. Utilizing proprietary analytics, Relationship Mapping not only identifies links and relationships, but focuses on hidden patterns of information sharing and interactions within potentially fraudulent clusters providing tips for your Special Investigations Unit (SIU) and compliance departments.

How is Relationship Mapping different from other healthcare fraud solutions?

While other industry solutions only use claims data for their visualizations or geolocations, Relationship Mapping expands your view. This powerful solution combines visualizations, proprietary linking technology, disparate data sets, referential identity and provider databases and your claims to expose hidden schemes and help organizations prioritize cases.

Relationship Mapping offers two core modules to help organizations get ahead of healthcare fraud:

LexisNexis Suspect Address:
LexisNexis Suspect Address uncovers suspected healthcare fraud or identity theft that has occurred at suspect addresses within their billing providers. LexisNexis analytics identify questionable addresses, linking them to the related businesses and individuals. This helps uncover relationships among providers; between providers and suspect entities not associated with your health plan’s provider network; business ownership; address churn; and other combinations of relationships that would not otherwise be apparent, all indicating possible healthcare fraud.

LexisNexis Drug Socialization™:
LexisNexis Drug Socialization™ can detect unusual socialization of drugs and identify the patient-provider groups and the pharmacies connected socially. This module identifies the relationships between prescriber, pharmacy and patient, linking them together through unusual prescribing habits, aberrant dispensing patterns and drug seeking behavior.


Combating the opioid crisis

Relationship Mapping can play a key role in fighting the opioid crisis. It identifies entities (high-risk providers, patients, and pharmacies) and clusters (e.g. social groups or networks) that drive widespread drug diversion and the proliferation of opioids.

At the Patient Level
Relationship Mapping identifies individuals who are opioid naïve, who abuse prescriptions, who are "doctor shopping", who partake in recreational drug use, who obtain prescriptions in order to sell them on the black market, who exhibit doctor-shopping behavior, or whose Morphine Equivalent Dose (MED) exceed the daily safe limits.

At the Prescriber Level
Our solution can detect excessive script-writing (pill mills), high-dose script writing, providers seeing a significant number of high-risk patients, those who are prescribing Opioids to large social and/or family groups, as well as providers who are part of a patient’s social network.

At the Pharmacy Level
Analysis can find pharmacies that are filling abnormally high numbers of suspect prescriptions (pill mills), whose patients appear to come from a single provider, who may be filling manufactured scripts, who appear to be a target for fraudsters, or whose fill rates for high-risk substances differ from their peers.

Key Features to Find Hidden Relationships Indicative of Healthcare Fraud:

  • Holistic identity resolution across multiple data types, intelligently connecting all entities.
  • Full complement of LexisNexis data, including individuals and entities found outside of your data.
  • Web-based investigative dashboard with graphical reporting of results.
  • Scoring and prioritization that looks at all provider types and the strength of their relationships.

These challenges can be solved through identity and healthcare analytics:

These challenges can be solved through identity and healthcare analytics.

  • Piece together multiple sources of data.
  • Identify key players, connections, and frequently missed patterns of behavior.
  • Simplify individual involvement and the structure of criminal organizations.

Data

Leverage non-healthcare data to identify new and previously unknown relationships.

Linking

Link entities to uncover schemes quickly and increase automation

Visualization

Accelerate responsiveness to research potential schemes and efficiently allocate resources.

     

Get it now: For more information about LexisNexis® Relationship Mapping, call 866.396.7703.

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See the Benefits of LexisNexis Relationship Mapping

The LexisNexis Relationship Mapping services are not provided by “consumer reporting agencies,” as that term is defined in the Fair Credit Reporting Act (15 U.S.C. § 1681, et seq.) (“FCRA”) and do not constitute “consumer reports,” as that term is defined in the FCRA. Accordingly, the LexisNexis Relationship Mapping service may not be used in whole or in part as a factor in determining eligibility for credit, insurance, employment or another purpose in connection with which a consumer report may be used under the FCRA.

Due to the nature of the origin of public record information, the public records and commercially available data sources used in reports may contain errors. Source data is sometimes reported or entered inaccurately, processed poorly or incorrectly, and is generally not free from defect. This product or service aggregates and reports data, as provided by the public records and commercially available data sources, and is not the source of the data, nor is it a comprehensive compilation of the data. Before relying on any data, it should be independently verified.