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Population Risk Management: Reducing Costs and Managing Risk in Health Insurance

In: Intelligent And Other Computational Techniques In Insurance Theory and Applications

Author

Listed:
  • Ian Duncan

    (Lotter Actuarial Partners, 915 Broadway Suite 607, New York, NY 10010, USA)

  • Arthur Robb

    (Landacorp Inc., 4151 Ashford Dunwoody Road Suite 505, Atlanta, GA 30319, USA)

Abstract

The following sections are included:BackgroundWhat Is a High-Risk Member?Elements of Population Risk ManagementIdentification (Targeting) of High-Risk PopulationsData: Available SourcesMedical ChartsSurvey DataMedical ClaimsPharmacy ClaimsLaboratory ValuesConclusions on DataImplementation Issues and How They Affect Prediction MethodologiesGoalsBudgetsStaffingComputing ResourcesData WarehousingPrediction MethodologiesClinical MethodsStatistical MethodsApplication of Interventions and Other Risk Management TechniquesTargeting the Right MembersEffectiveness and OutcomesResults, Including a Methodology for Optimizing Inputs to and Estimating Return on Investment from Intervention ProgramsUsing the Risk Management Economic ModelSummary and ConclusionsReferences

Suggested Citation

  • Ian Duncan & Arthur Robb, 2003. "Population Risk Management: Reducing Costs and Managing Risk in Health Insurance," World Scientific Book Chapters, in: A F Shapiro & L C Jain (ed.), Intelligent And Other Computational Techniques In Insurance Theory and Applications, chapter 7, pages 261-298, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812794246_0007
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