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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 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 • 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 • Add value to existing data • Getting data into the right hands at the right time • Continually seek out new data sources
Key Data Domains • Member • Provider • Claims – PH/BH/Rx • Care Management • Pharmacy • External Data Sources
“Make Every Member Contact Count” • “360o View of the Member”
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 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 • Likelihood of Hospitalization
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 • Future Directions: • Innovative algorithms • “Logical” phone queues • Infrastructure strategies • Reform implications • HIE • Social media
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
Thank You!! • Questions?