IMPACT OF DISPARITIES IN CARDIOVASCULAR CARE

ON AFRICAN AMERICAN DEATHS

Kevin Fiscella, MD, MPH University of Rochester

School of Medicine & Dentistry

Background

Burgeoning health care disparities literature

Challenge of prioritizing health care disparities

Need for a common metric for evaluation

Purpose

Population impact - annual deaths

Present a simple model using black-white disparities in CVD

Estimate the number of African American CVD deaths that would be avoided/delayed if disparities in CVD care were eliminated

The Model

AA deaths prevented/delayed =

absolute disparity x absolute risk reduction

Components of absolute disparity (AD)

Disparity in provision/prescription of intervention

Disparities in use of or adherence to intervention

Estimating AD

AD= (EPB x Rxw x Adw) - (EPB x RxB x AdB)

EPB = Eligible black population i.e. the number who are candidates for the intervention annually

Rxw = Provision/prescription of the intervention for whites

Adw= Adherence to the intervention for whites

RxB = Provision/prescription of the intervention for blacksAdB= Adherence to the intervention for blacks

Common thread: clinician-patient communication

Communication affects patients’ willingness to accept a treatment and clinician’s willingness to provide or prescribe it

Communication affects patients’ adherence

Absolute risk reduction

Baseline mortality in the absence of intervention

Relative risk reduction associated with the intervention

ARR= RRR x base mortality rate

CVD Interventions

AMI following hosp discharge – drug treatment

AMI – reperfusion and revascularization

Chronic angina - drug treatment

Chronic heart failure - drug treatment

Heart failure following hosp discharge – drug treatment

Hyperlipidemia – drug treatment

Hypertension - drug treatment

Long-term post MI – drug treatment

Unstable angina –drug treatment

Unstable angina - drug treatment

Sudden death prevention – ICD insertion

Population size and mortality rates

Condition Size of population (crude)

Base annual

Mortality (crude)

AMI admits 83,490 22%

HF admits 110,000 33%

UA admits 54,000 16%

Chronic AMI 950,000 5%

Chronic angina 575,00 2.5%

Chronic HF 444,000 10%

Hypertension 9.4 million 1.6%

Hyperipidemia 10.4 million 0.5%

Sudden death 13,600 15%

Key disparity (black/white ratio) estimates

Drug treatment in the year following hospital discharge - 0.95 (0.92- 0.98)

CABG - 0.80 (0.6-0.8)

PTCA - 0.90 (0.7-0.9)

Fibrinolysis - 0.90 (0.85-0.95)

Adherence to treatment for chronic condition – 0.80 (0.7-0.9)

Adjusting summed deaths

Avoiding double counting from hospital readmissions from same year and transfers

Avoiding double counting from comoribidity e.g. AMI and HF, CAD and hypertension

Adjusting for less than additive relative risk

Findings

Condition Disparity Deaths AMI first year following admission 1,200

Chronic angina 450

Heart failure (> 1 year following admission) 1,750

Heart failure first year following admission 1,930

Hyperlipidemia 430

Hypertension 1420

AMI (>1 year following admission) 930

Sudden death prevention- ICD 200

Unstable angina first year following admission 800

TOTAL 8,800

Key findings

Common conditions with high mortality requiring daily adherence have the greatest impact on disparities e.g. heart failure and AMI.

Interventions with high reach e.g. cardiac rehabilitation (990) have greater impact than those with smaller reach e.g. reperfusion therapy (740) or ICDs (200).

Disparities in drug adherence is a major driver accounting for 4,980 deaths.

Limitations Lack of reliable data for many estimates

Assumptions e.g. differential impact, sustained benefit, synergistic effects

No stratification by age or gender

Annual deaths not QALYS

Conclusions

Population impact represents a key (though not the only) metric for prioritizing health care disparities

The population impact model could be adapted by health care organizations that care for defined populations using their own internal data to assess the impact of health care disparities

Acknowledgements

Funding: RWJF and NHLBI/NIH

Collaborators: Richard Dressler

Advice: Simon Capewell

Sensitivity

95% CI - 5,700-11,110

Adherence disparity: 0.70-.90 - 6,310-

11,290