The 2004 Healthcare Conference 25-27 April 2004, Scarman House, University of Warwick David Mirkin &...
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The 2004 Healthcare Conference25-27 April 2004, Scarman House, University of Warwick
David Mirkin & Joanne Alder
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DISEASE MANAGEMENT
What is a DM program? Why do we need DM? Clinical Measures of Success Actuarial Issues in Measurement Does a DM program save money?
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DMAA Definition of DM
Disease Management is a system of coordinated health care interventions and communications for populations with conditions in which patient self-care efforts are significant. Disease management: supports the physician or practitioner/patient relationship and
plan of care emphasizes prevention of exacerbations and complications
utilizing evidence-based practice guide lines and patient empowerment strategies
evaluates clinical, humanistic and economic outcomes on an ongoing basis with the goal of improving overall health.
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DMAA Definition of DM
Disease Management Components include: : Population Identification processes Population Identification processes Evidence-based practice guidelines Evidence-based practice guidelines Collaborative practice models to include physician and support-Collaborative practice models to include physician and support-
service providers service providers Patient self-management education (may include primary Patient self-management education (may include primary
prevention, behavior modification programs, and prevention, behavior modification programs, and compliance/surveillance) compliance/surveillance)
Process and outcomes measurement, evaluation, and Process and outcomes measurement, evaluation, and management management
Routine reporting/feedback loop (may include communication Routine reporting/feedback loop (may include communication with patient, physician, health plan and ancillary providers, and with patient, physician, health plan and ancillary providers, and practice profiling)practice profiling)
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Critical to DM Success
Best Practice: Making sure physicians know and use the latest treatment approaches. (evidence based best practice guidelines)
Compliance: Teaching patients about the disease and how to self-manage
Utilization: Monitoring care for appropriateness. Outcomes: Data analysis and feedback to providers
and patients
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Types of DM Programs
“Silo” or Disease Specific Programs Diabetes CHF Coronary Artery Disease Asthma COPD
Integrated DM Programs (Patients with 2 or more chronic diseases)
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DM Goals
Short Term Goals and Interventions Identify and enroll patients with the disease. Assess patients risk level and assign to risk category. Improve treatment regimens. Reduce related hospitalizations, emergency room visits and
ancillary services. Increase required outpatient screening visits and tests. Monitor pertinent clinical data. Improve therapy adherence. Increase patient satisfaction
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DM Goals
Outcomes: Long Term Goals and Measurements of Effect Improve/maintain optimal health. Evidence of therapy adherence. Improved clinical status as measured by disease specific
clinical indicators. Reduced utilization of hospitalization, emergency room. Reduced specific disease related complications. Patient satisfaction. Physician compliance.
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Why Disease Management?
A Common Lay Question & Perception “Why do we need disease management programs? I thought
that we paid doctors to manage the patients. Why do we need to pay extra money to do what the doctors are being paid to do”
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Why Disease Management?
Outcomes which are possible (evidence based literature supports) are not being achieved for the population at risk Clinical Functional
Financial
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3.4% 12.7% 3.74 7.94 3.1% 13.9% 4.48 6.32
Health Plan Premium Growth Compared To Other Indicators
1998-2003
4.8%
2.2%
1.6%3.3%3.1%
2.3%1.4%
4.4%
3.5%
3.7%4.3%
3.4% 3.1%
13.9%12.7%
11.0%
8.3%
3.7%
1998 1999 2000 2001 2002 2003
The Bottom LineThe Bottom Line
PremiumPremium
Worker’s EarningsWorker’s Earnings
General InflationGeneral Inflation
KFF/HRET, 9/2003KFF/HRET, 9/2003
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Population Outcome Failure
Evidence based best practice not applied Large Variances in practices nationwide
Poor patient compliance Lack of knowledge of disease Not empowered Lack of self management
Fragmentation of Care Lack and Fragmentation of Resources Lack of system integration
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From Silos To Quality Care
Payers
Consumers/Patients
Hospitals
Providers
Employers
Healthcare System DM Integration
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Do You Need To Have Programs For All Diseases?
The 80-20 rule still holds:
80% of the health care costs tend to come from 20%
of the patients, therefore that’s where the attention
should focus.
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Chronic Disease United States 2000
US Population Year 2000 – 276 million 151 million (55%) are well or have acute illnesses 125 million (45%) have chronic conditions
125 Million With Chronic Illness 70 million (56%) have 1 chronic Condition 55 million (44%) have 2 or more chronic conditions
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Future Cost of Chronic Disease
By 2030, 148 million Americans will have a chronic disease and their health bill will reach $798 Billion.
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DM Program Outcomes Metrics
Clinical/Functional ROI Decreased Morbidity Decreased Mortality Improved Quality of Life
Financial ROI Cost Minimization Cost Benefit Cost Effectiveness
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CLINICAL OUTCOME METRICS FOR DIABETES
METRIC METRIC DEFINITION
Foot examination % of members with diabetes who completed one foot examination using Semmes-Weinstein monofilament, palpation of pulses and visual examination in the measurement year.
ACE inhibitors/ARBs % of diabetes members with microalbuminuria or clinical albuminuria (ADA Guidelines) taking ACE inhibitors or ARB.
A1C level at target % of diabetes members with an A1C level <7.0% in the past year. (ADA Guideline)
LDL level at target Percentage of diabetes members with LDL levels < 100 mg/dL within the past two measurement years. (use last measure to report) (ATP III Guideline)
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CLINICAL OUTCOME METRICS FOR DIABETES
METRIC METRIC DEFINITION
Fasting lipid panel % of members with diabetes who completed one test in the measurement year
LDL level* % of diabetes members with LDL < 130 mg/dL within the past two measurement years. (use last measure to report)
ASA % of diabetes members >30 years of age taking an aspirin each day.
Smoking quit rate % of diabetes members who reported smoking at the beginning of the measurement period who at the time of measurement had quit smoking
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Diabetes Disease Management Outcomes
DCCT/NIH Trials Retinopathy ↓ 35% - 74% Severe non-proliferative retinopathy and laser therapy ↓ 45% 1st appearance any retinopathy ↓ 27% Development Microalbuminuria ↓ 35% Development Neuropathy ↓ 60%
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Congestive Heart Failure: Outcomes
University of Pennsylvania Health Systems-
Hospitalization rates dropped dramatically from
532/1,000 patients to 19/1,000 patients.
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Ischemic Heart Disease Outcomes - Statin Treatment Reduces CHD Events and Deaths
Milliman Actuarial Models, Framingham Risk Scoring, NHANES III, ATP III
-23
-52
-63-70
-60
-50
-40
-30
-20
-10
0
Primary Events Secondary Events Death
An
nu
al #
of
CH
D E
ven
ts
Employer With 100,000 Employees
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Actuarial Issues in the Financial Measurement of Disease Management Programs
Return on Investment Regression to the Mean Statistical Credibility Trend Estimation Operational & Other Issues
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Measurement of Total Program Savings
Method One: Comparison of pre-enrollment medical expenses (baseline year) to post enrollment expenses (intervention year).
Method Two: Comparison of medical expenses for a control group to an intervention group for like period.
Method Three: Comparison of requested services to approved services or other detailed comparisons
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Actuarial Considerations in the Measurement of Total Program Savings
Regression to the Mean
Statistical Credibility
Others
1. Depends on method used
2. Population management issues
3. Operational issues
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Other Considerations for Measurement of Program Savings
Method One: Pre-enrollment expenses to post enrollment expense comparison
1. Utilisation and cost trend estimation
2. IBNR and claims runoff issues
Method Two: Control group versus intervention group expense comparison
1. Age/sex 4. Underwriting
2. Benefit design 5. Others
3. Industry
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Modified Exponential Modeling for AMI Admissions
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
1 2 3 4 5 6 7 8 9
Years of Data
Uti
liza
tio
n R
ate
Per
1,0
00
5% Error = (5.0,31.5) 1% Error = (7.2,30.3)
Ultimate Rate = 30.0
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Modified Exponential Modeling for Bypass Surgery (CABG)
0.0
20.0
40.0
60.0
80.0
100.0
120.0
1 2 3 4 5 6 7 8 9
Years of Data
Util
izat
ion
Rat
e P
er 1
,000
5% Error = (4.3,53.7) 1% Error = (6.2,51.6)
Ultimate Rate = 51.1
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Table 3Comparison of One Year, Three Year, and Modeled Ultimate Rates of Utilization
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Why Should We Talk About ‘Statistical Credibility’?
Disease populations are often small percentages of the total population
Disease population is high cost, high variance
Often savings calculations are based on only a portion of the health care dollar for the diseased members
Savings guarantees and ROI target calculations need to reflect program impact rather than statistical fluctuation
An ignorance of credibility can lead to faulty or misleading conclusions
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Typical Disease Prevalence Rates for a US Commercial Population (Employer Insured Active Employees)
Diabetes 3.8% - 8.1%
Asthma 1.6% - 5.1%
CAD 1.9% - 2.6%
CHF 0.3% - 1.1%
COPD 0.3% - 1.2%
Source: Disease Management News, September 25, 2002
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Typical PMPM Claim Costs Ranges by Disease Category for a Commercial Population (US $$$)
Diabetes $400 - $800
Asthma $150 - $500
CAD $400 - $1,300
CHF $1,500 - $2,100
COPD $500 - $1,400
Source: Disease Management News, September 25, 2002
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The ChoiceThe Choice