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DODD Claims Cost and Fraud Optimization
DODD Claims Cost and Fraud Optimization
Actionable interventions that will help detect fraud, improve cost projections, and streamline claims analysis.
The Ohio Department of Developmental Disabilities (DODD) Claims data mart contains over 286 Million records of billing information since the calendar year 2002. Claims data can be linked to DODD individuals, providers, services,
and projected cost/budget which results in a much larger and complex data set. Querying billing data associated with
the other entities described above can be very difficult, time-consuming, and resource-intensive for complex reporting or analysis.
Nearly 96,000 Ohioans access DODD services by working with their county board of developmental disabilities, direct service providers, and provider agencies to get the support they need to live the life they want. More than 36,600 people access person-centered supports through a home and community-based service waiver settings; that might be someone living at home on their own, with family, with a roommate, or with someone who provides full-time care through Ohio Shared Living.
Claims information with individuals, providers, and cost projection/budget data in the State of Ohio Data Analytics platform will provide distributed processing power, faster storage, and analytical tools for data science processing and statistical analysis. DODD power users will be able to run faster queries. Analytical and projection algorithms implemented against data will be able to provide results fast and in a timely manner. 
Operational Reports and Dashboards will be implemented to:
  • Organize and store analytical data stores as to support ongoing application of analytical methods to support
    the operational use of work products, analytical and predictive models developed as a result of completion of
    Analysis Dimensions 1-4 inclusive;
  • Organize and store analytical data associated with audit and claims history to offload this data from
    operational systems while maximizing the use and usefulness of the data utilizing the State’s Data Analytics
  • Implement an IT change model to identify all records changed or modified by users, including users that
    change multiple records or records associated with multiple entities (e.g., recipients, claims, payments or
    other operational aspects) that may indicate inappropriate or fraudulent activities (e.g., unusual data
    accesses, changes, programmatic changes, unapproved, suspicious changes or changes outside of “normal”
    operating hours or standards);
  • Develop a comprehensive record change history by entity e.g., recipients, claims, payments or other
    operational aspects) to report on “normal” (i.e., legitimate business uses and access) as well as “abnormal”
    record access potentially related to inappropriate or fraudulent behaviors as identified in Dimensions 1-4;
  • Provide the State operational tools to support all elements of this Section via tabular, graphical or visual
    dashboards (as mutually agreed) to operationalize all analyses, models and reports contained in this