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Verisys’ FACIS Provides Valuable Data to Assist with Underwriting for Medical Professional Liability

August 14, 2019

Health care providers are required to carry current medical professional liability insurance as part of the credentialing and privileging process, as well as to qualify to participate in Federal and State health care and private payer programs.

Determining risk is a science in the underwriting business regarding full transparency on the providers being insured. While techniques and technology advance to predict and manage risk, a simple gate-keeping philosophy, followed by continuous monitoring, is a very effective process to mitigate risk.

The procedure of underwriting has evolved from manual to automated using third-party data sources to build predictive models through risk-scoring algorithms. Using artificial intelligence and predictive tables don’t take into consideration the gaps in practitioner self-reporting and data sets used to screen participants in the underwriting process.

Most data sources used in risk scoring are contributory, relying on individuals, hospitals, or practices to report adverse data in a timely manner. Four examples of widely used data sets that are contributory with no enforcement of disclosure are:

  • L.U.E.®, Comprehensive Loss Underwriting Exchange is LexisNexis’ listing of property loss claims.
  • MIB, Medical Information Bureau, Inc., lists information from private policy applications for health and disability carriers.
  • NPDB, National Practitioner Data Bank, lists claims against providers.
  • FSMB, The Federation of State Medical Boards lists license information on providers that fall within the membership of 70 state medical and osteopathic boards.

Even with data collected from these disparate data sets, records are not always verified and correctly matched to a name or to an alias. Additionally, there are many gaps in data never being reported. For instance, if a claim makes it to court and the provider is uninsured, that data often remains buried somewhere in the 3,144 county records and in the 94 U.S. district courts.

In 1992, Verisys Corporation launched the Fraud Abuse Control Information System, FACIS®, and began collecting data on health care providers. As technology progressed and the cost of storing data decreased, the sources of data increased, the speed of accessing the data became real-time, and aggregation, name matching, and data delivery facilitated the accessibility of data to a wide audience.

With records going back to the early 1990s, FACIS has historic, longitudinal data on exclusions, debarments, sanctions, and disciplinary actions on all license types, across every U.S. jurisdiction. In addition, FACIS publishes press releases on indictments from all 94 U.S. District Courts and every State Attorney General.

In addition to the FACIS database, Verisys’  Verified License Search and Status (VLSS®) provides license history and current license status with alerts to any change or adverse action. This database covers the breadth and depth of FACIS in that it collects data from all primary source publishers of license information and then correctly matches to the provider profile.

Additional data points to check for screening and monitoring are:

  • DEA for prescription abuse
  • NPI to check for medical provider identity fraud
  • National Sex Offender Registry to be aware of registered sex offenders
  • National Adult Abuse Registry (a Verisys product) for records on those who have been accused, investigated, or sanctioned for physical, mental, or financial abuse of a patient
  • Social Security Administration/Death Master File to check for misuse of a Social Security number of a deceased individual

This is the depth of data that when used for screening during the initial underwriting process, and for ongoing monitoring over the life of the policy, provides real-time, comprehensive information to accurately calculate price based on risk. This in-depth data will also help determine when to cancel a policy for material misrepresentation. Verisys has the most comprehensive data in the health care industry that can help your organization predict and mitigate risk in your underwriting process.

Susen Sawatzki Written by Susen Sawatzki
Healthcare Industry Expert
Muse. Writer. Publisher. Producer. Creator of Inspiring Narratives.
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