new approaches focusing on dynamic variables related to changes in member’s health status:
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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. Outline. Background Predictive Rules Validity Applications. Background. The Diabetic Epidemic. - PowerPoint PPT PresentationTRANSCRIPT
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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
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Outline
• Background
• Predictive Rules
• Validity
• Applications
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Background
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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
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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
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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
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Predictive Rules
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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
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Applied HbA1c-Comorbidity RelationshipRetinopathy Example:
A1C %: 9.4 8.4 7.4 6.4 5.4
Retinopathy Prevalence: 0.5566 0.3563 0.228 0.1459 0.0934
(1-Prevalence) 0.4433 0.6438 0.772 0.8541 0.9066
P (0 Co-Morbidities) 0.1151 0.2892 0.4236 0.5307 0.6123
P(Only Retinopathy) 0.1446 0.1601 0.1251 0.0907 0.0631
P(Ret&Neur Only) 0.0601 0.0371 0.0175 0.0077 0.0033
P(Ret + 1) 0.1844 0.1435 0.0823 0.0465 0.0264
P(R, Neur, Dep Only) 0.0057 0.0027 0.0009 0.0004 0.0002
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Performed for 156 combinations of 9 Co-Morbidities
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Predicted A1c from # of Co-Morbidities
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9.4 8.4 7.4 6.4 5.4 Predicted A1c
P(0) 0.1152 0.2894 0.4236 0.5307 0.61228 6.7732
P(1 Only) 0.2915 0.4195 0.4038 0.3630 0.31888 7.4010
P(2 Only) 0.2544 0.2270 0.1460 0.0943 0.06284 8.0573
P(3 Only) 0.2934 0.2530 0.1659 0.0872 0.04873 8.1723
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Polynomial Extrapolation
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Drug Intensity-Disease Intensity Relationship
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• 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
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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
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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)
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Predicted HbA1c=(Co-Morbidity Index + Pharmacy Index)/2
Note: All adjustments are from 7.40
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Validity
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Paired T-Test All Inclusive Excluding Physician Visit Outliers
Actual Predicted
Mean 7.116470588 7.216149433
Variance 1.131392157 0.431441838
Observations 85 85Pearson Correlation 0.289856571Hypothesized Mean Difference 0
df 84
t Stat -0.854070714
P(T<=t) two-tail 0.395494943
t Critical two-tail 1.988610165
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Predicted Actual
Mean 7.388 7.31215
Variance 2.275006 0.437331
Observations 100 100Pearson Correlation 0.338633Hypothesized 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
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Predictive Power
Method 1 Method 2
Deviation from Mean -0.07585 +0.09968
Avg. Absolute Deviation 0.89341 0.75371
1.0 Deviation Confidence 77% 80%
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Limitations
• Variance
• Patients skipping full year of appointments
• Variables limited to data fields within pharmacy and insurance claims
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Applications
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Disease Management
Patient-Level
• Identify Actionable Members
• Measure Intervention Effectiveness
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Marketing
Population-Level
• Track and report group’s year over year changes in predicted mean HbA1c
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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
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Questions
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