The 2004 Healthcare Conference25-27 April 2004, Scarman House, University of Warwick

David Mirkin & Joanne Alder

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?

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.

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)

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

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)

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

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.

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”

Why Disease Management?

Outcomes which are possible (evidence based literature supports) are not being achieved for the population at risk Clinical Functional

Financial

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

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

From Silos To Quality Care

Payers

Consumers/Patients

Hospitals

Providers

Employers

Healthcare System DM Integration

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.

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

Future Cost of Chronic Disease

By 2030, 148 million Americans will have a chronic disease and their health bill will reach $798 Billion.

DM Program Outcomes Metrics

Clinical/Functional ROI Decreased Morbidity Decreased Mortality Improved Quality of Life

Financial ROI Cost Minimization Cost Benefit Cost Effectiveness

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)

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

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%

Congestive Heart Failure: Outcomes

University of Pennsylvania Health Systems-

Hospitalization rates dropped dramatically from

532/1,000 patients to 19/1,000 patients.

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

Actuarial Issues in the Financial Measurement of Disease Management Programs

Return on Investment Regression to the Mean Statistical Credibility Trend Estimation Operational & Other Issues

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

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

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

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

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

Table 3Comparison of One Year, Three Year, and Modeled Ultimate Rates of Utilization

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

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

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

The ChoiceThe Choice