A payer s perspective business intelligence and analytics
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A Payer’s Perspective: Business Intelligence and Analytics. AmeriHealth Mercy. Overview Started as Mercy Health Plan in early 1980’s Managed care solutions for physical health, behavioral health, and pharmacy services Predominant focus is on Medicaid populations

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Amerihealth mercy
AmeriHealth Mercy

Overview

  • Started as Mercy Health Plan in early 1980’s

  • Managed care solutions for physical health, behavioral health, and pharmacy services

  • Predominant focus is on Medicaid populations

  • Physical Health plans in 6 States, 2 more going live in 2012

    Challenges

  • Limited funding

  • Characteristics of population


Underlying goals of payer analytics
Underlying Goals of Payer Analytics

  • Understand utilization and cost trends

  • Improve clinical outcomes

  • Prevent unnecessary services

  • Improve HEDIS scores

  • Maximize revenue

  • Influence policy

  • Align incentives

  • Identify trends early – appropriate interventions


Critical functions
Critical Functions

  • Add value to existing data

  • Getting data into the right hands at the right time

  • Continually seek out new data sources


Key data domains
Key Data Domains

  • Member

  • Provider

  • Claims – PH/BH/Rx

  • Care Management

  • Pharmacy

  • External Data Sources






Member data
Member Data

  • Demographics

  • Claims data (Medical, Dental, Vision) – including historical data

  • Pharmacy data

  • Race/Ethnicity/Language

  • Coverage Category

  • Lab Results

  • Risk Scores – prospective, concurrent

  • PCP History

  • Clinical Conditions

  • Maternity History

  • Etc….



Early intervention
Early Intervention

  • Early Identification and Stratification of High Risk Maternity Cases

  • Prenatal Vitamins

  • Lab Codes

  • Lab Test Results

  • Member Risk Score

  • Medication History

  • Diagnosis codes (e.g., SMI)

  • Age

  • Health Risk Assessment Reponses

  • Prior Delivery History


Patient stratification algorithms
Patient Stratification Algorithms

  • Likelihood of Hospitalization






Strategic analytic tools
Strategic Analytic Tools

  • Today:

  • Verisk Groupers

  • DxCG Risk Scoring

  • Likelihood of Hospitalization

  • Treo Services

  • MedAssurant – Catalyst

  • Internal Algorithms

  • Access Databases

  • Soon:

  • Sybase IQ

  • WEB Intelligence (WEBi)

  • User Maintained Production Schemas

  • Data Quality/Profiling


Looking ahead
Looking Ahead

  • Future Directions:

  • Innovative algorithms

  • “Logical” phone queues

  • Infrastructure strategies

  • Reform implications

  • HIE

  • Social media


Innovative member algorithms
Innovative Member Algorithms

  • Ability to “Impact” Member

  • Success in contacting Member

  • Ratio of PCP to ER visits

  • Medication compliance

  • Rate of historical “preventable” events

  • Participation in prior programs

  • Overall family “compliance” score




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