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. 2 Outline Background Predictive Rules Validity Applications

3. Background 3

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 4

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 5

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 6

7. Predictive Rules 7

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 8

9. Applied HbA1c-Comorbidity Relationship Retinopathy Example: A1C %:9.48.47.46.45.4 Retinopathy Prevalence: 0.55660.35630.2280.14590.0934 (1-Prevalence) 0.44330.64380.7720.85410.9066 P (0 Co-Morbidities) 0.11510.28920.42360.53070.6123 P(Only Retinopathy) 0.14460.16010.12510.09070.0631 P(Ret&Neur Only) 0.06010.03710.01750.00770.0033 P(Ret + 1) 0.18440.14350.08230.04650.0264 P(R, Neur, Dep Only) 0.00570.00270.00090.00040.0002 9 Performed for 156 combinations of 9 Co-Morbidities

10. Predicted A1c from # of Co-Morbidities 10 9.48.47.46.45.4 Predicted A1c P(0)0.11520.28940.42360.53070.612286.7732 P(1 Only)0.29150.41950.40380.36300.318887.4010 P(2 Only)0.25440.22700.14600.09430.062848.0573 P(3 Only)0.29340.25300.16590.08720.048738.1723

11. Polynomial Extrapolation 11

12. Drug Intensity-Disease Intensity Relationship 12 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 13

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) 14 Predicted HbA1c=(Co-Morbidity Index + Pharmacy Index)/2 Note: All adjustments are from 7.40

15. Validity 15

16. Paired T-Test All Inclusive Excluding Physician Visit Outliers ActualPredicted Mean 7.1164705887.216149433 Variance 1.1313921570.431441838 Observations 85 Pearson Correlation 0.289856571 Hypothesized Mean Difference 0 df 84 t Stat -0.854070714 P(T<=t) two-tail 0.395494943 t Critical two-tail 1.988610165 16 PredictedActual Mean 7.3887.31215 Variance 2.2750060.437331 Observations 100 Pearson Correlation 0.338633 Hypothesized Mean Difference 0 df 99 t Stat 0.531475 P(T<=t) two-tail 0.59628 t Critical two-tail 1.984217 Predictions compared with 2005-2007 BCBSRI HEDIS Data

17. Predictive Power Method 1Method 2 Deviation from Mean-0.07585+0.09968 Avg. Absolute Deviation0.893410.75371 1.0 Deviation Confidence77%80% 17

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

19. Applications 19

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

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

22. References NIH. National Diabetes Statistics 2007. http://diabetes.niddk.nih.gov/dm/pubs/statistics/ 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.jsphttp://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 22

23. Questions 23