New Approaches Focusing on Dynamic Variables Related to Changes in Member’s Health Status:

1. New Approaches Focusing on Dynamic Variables Related to Changes in Member’s Health Status: Diabetic HbA1c Predictive Model Brenton B. Fargnoli Blue Cross & Blue Shield of Rhode Island

2. Outline • Background • Predictive Rules • Validity • Applications

3. Background

4. The Diabetic Epidemic • Prevalent • 23.6 million people (7.8% of population) • Expensive • Medical Expenditures: $116 Billion National Diabetes Statistics, 2007 American Diabetes Association, 2007 • National Diabetes Statistics, 2007

5. Lab Data Gap Clinical and Economic Effectiveness: • HbA1c<7%: (6, 4.5) • HbA1c>9%: (6, 4.5) • Annual HbA1c Screening: (1,1) • Thus, it is the lab values, not the presence of screenings which are significant. de Brantes et al., Am J Managed Care, 2008

6. Variables Associated with HbA1c Level Association • Age • Drug Adherence • Drug Therapy • Co-Morbidities • Physician Visits • Ethnicity Shectman et al., Diabetes Care, 2002 No Association • Gender • Income • A1c screenings

7. Predictive Rules

8. HbA1c’s Continuous Risk Gradient • 1% HbA1c Reduction Associated with Decreases: • 43% Amputations • 36% Nephropathy, Neuropathy, Retinopathy • 30% Depression • 24% ESRD • 14.5% Cataracts • 14% MI • 12.5% Stroke IMPACT Product

9. Applied HbA1c-Comorbidity RelationshipRetinopathy Example: Performed for 156 combinations of 9 Co-Morbidities

10. Predicted A1c from # of Co-Morbidities

11. Polynomial Extrapolation

12. Drug Intensity-Disease Intensity Relationship • High Intensity (+0.75) • Type II Insulin use • ≥ 3 oral anti-diabetics • Low Intensity (-0.75): • No pharmaceuticals needed Adapted and Modified from Shectman et al., Diabetes Care, 2002

13. Drug Adherence • Reflects: • Self-Management • Drug Effectiveness • Calculated with Avg. Days Supply Method • (% Adherence – 82%) x (-1.5) Adapted and Modified from Shectman et al., Diabetes Care, 2002

14. Rules Summary • Co-Morbidities: • 0: 6.77 • 1: 7.40 • 2: 8.06 • 3: 8.17 • 4: 10.11 • 5: 11.81 • 6: 13.80 • 7: 16.10 • 8: 18.70 • 9: 21.59 • No PCP nor Eye Appts for full year: (+0.75) • Pharmacy • Insulin: (+0.75) • ≥ 3 oral anti-diabetics: (+0.75) • None (-0.75) • (% Adherent – 82%) x (-1.5) Predicted HbA1c=(Co-Morbidity Index + Pharmacy Index)/2 Note: All adjustments are from 7.40

15. Validity

16. Paired T-TestAll InclusiveExcluding Physician Visit Outliers Predictions compared with 2005-2007 BCBSRI HEDIS Data

17. Predictive Power

18. Limitations • Variance • Patients skipping full year of appointments • Variables limited to data fields within pharmacy and insurance claims

19. Applications

20. Disease Management Patient-Level • Identify Actionable Members • Measure Intervention Effectiveness

21. Marketing Population-Level • Track and report group’s year over year changes in predicted mean HbA1c

22. References • NIH. National Diabetes Statistics 2007. http://diabetes.niddk.nih.gov/dm/pubs/statistics/ • American Diabetes Association. Direct and Indirect Costs of Diabetes in the United States. http://www.diabetes.org/diabetes-statistics/cost-of-diabetes-in-us.jsp • de Brantes F, Wickland P, Williams J:The Value of Ambulatory Care Measures: A Review of Clinical and Financial Impact from an Employer/Payer Perspective. Am J of Managed Care 14: 360-368,2008 • IMPACT Product: Meta-analysis of case-controlled, longitudinal studies • Schectman J, Nadkarni M, Voss J: The Association Between Diabetes Metabolic Control and Drug Adherence in an Indigent Population. Diabetes Care 25: 1017-1021,2002

23. Questions