Managed Care Models for ABD Populations PDF
Preview Managed Care Models for ABD Populations
Managed Care Models for ABD Populations: Identification, Stratification and Care Coleen Kivlahan, MD, MSPH Schaller Anderson, Inc. CHCS Medicaid Best Buys Webcast Tuesday, May 29, 2007 1 SA’s Complex and ABD Members Arizona: 8,524 LTC; 41,000 ABD; 11,000 HCG (high risk pool); 13,000 SNP California: 66,000 TANF and ABD children Delaware: 9,000 ABD Maryland: 12,300 ABD Total = More than 100,000 members (March 2007 data) 2 Annual Claim Costs by Percentile (Medicare vs. Commercial vs. Medicaid) $70,000 $60,000 $50,000 s t s o C $40,000 a t i p a C re $30,000 P $20,000 $10,000 $- 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% Percentile of Medicaid Members Medicare Medicaid-ABD Commercial Medicaid-TANF Avg. Medicare Avg. Medicaid-TANF Avg. Comm 3 ABD High Utilizer in the Traditional Insurance Model No PCP or medical home 1. Uses ER for primary care 2. Little to no information passing between ER, inpatient 3. setting and care manager No way to identify her as high utilizer and inform 4. interventions No concurrent review, only retrospective review 5. No prior authorization for key procedures 6. Lack of integration of pharmacy, lab or BH data 7. Limited intensive care management 8. 4 More than Half of People with Serious Chronic Conditions* Have Three or More Physicians No Physicians 3% 1 Physician 6% 2 Physicians 26% 3 Physicians 23% 4 Physicians 5% 5 Physicians 6% 6+ Physicians 11% • People with serious chronic conditions have a condition that is expected to last a year or more, requires ongoing medical attention, and limits what one can do. Serious chronic conditions are a subset of chronic conditions, which are also expected to last a year or more but limit what one can do, and/or may require ongoing medical care. Source: Serious Chronic Illness Survey, conducted by the Gallup Organization, 2002. 5 Physicians Believe that Poor Care Coordination Produces Poor Outcomes Percent of Physicians Who Believe That Poor Outcomes Result From Poor Care Coordination Receipt of Contradictory Information 54% Unattended Emotional Problems 49% Adverse Drug Interactions 44% Unnecessary Hospitalization 36% Patients Not Functioning to Potential 34% Experience of Unnecessary Pain 34% Unnecessary Nursing Home Placement 24% 0% 10% 20% 30% 40% 50% 60% Source: National Public Engagement Campaign on Chronic Illness—Physician Survey, conducted by Mathematica Policy Research, Inc., 2001. 6 Our Predictive Modeling tool includes: Predictive Risk Score – Multiple factors, including the Medicaid Rx, a pharmacy based risk adjustment tool, are used. Chronic Care Risk Stratification -- Members are stratified on the basis of their compliance or adherence to program goals and outcomes, and ranked by the risk of future avoidable costs that each enrollee represents. Co-morbidity -- Each member is assigned additional algorithm weight if a significant co- morbid condition is identified. Predictive Pathways uses the Charlson Index to identify and apply additional diagnostic weight for those conditions having significant morbidity implications. Impact Rating -- A member’s primary condition is assessed and scored based on the possible level of impact from care management on the member’s financial and clinical outcomes. 12-Month Claims Cost -- A rolling 12 months of claims cost (pharmacy, medical, DME, procedures, lab, etc) (excluding trauma and maternity) is calculated. Cost is stratified into high-cost, moderate and low-cost enrollees, with higher weights given to those members having higher accumulated costs. Care Gaps -- The presence or absence of evidence-based effective interventions for each of the four conditions in disease management: CHF, COPD, Diabetes and asthma. 7 It should also include: Self-report data (HRA) Functional status QOL indicators Social and behavioral indicators Cognitive markers Biomarkers Pharmacy adherence measures for key meds 8 Predictive Modeling Ranks for all Members: sorted by ABD population 9 47-year-old with CHF, diabetes, schizophrenia: 23 ER visits, no PCP 10
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