Brian F. Gage, M.D., M.Sc.
Project Overview:
What is the association between cardiovascular prognostic factors and mortality in Medicare beneficiaries with atrial fibrillation?
What is the association between cardiovascular prognostic factors imputed from Medicare part A data and mortality in Medicare beneficiaries with atrial fibrillation?
What is the association between the Deyo-modified Charlson index and mortality in Medicare beneficiaries with atrial fibrillation?
The objectives of this study are: to quantify the association between common cardiovascular prognostic factors (eg. hypertension and diabetes) and mortality in patients who have atrial fibrillation; to determine how well cardiovascular prognostic factors imputed from administrative data predict mortality; and to quantify the accuracy of using the Deyo-modified Charlson index for mortality risk adjustment and to compare it to alternative schemes (e.g., A. Elixhauser, 1998).
The study will use an existing database, the National Registry of Atrial Fibrillation (NRAF). With funding from the Agency for Healthcare Research and Quality (AHRQ) and in collaboration with the Medicare Peer Review Organization (PROs), we assembled the NRAF dataset, a registry of Medicare patients who have chronic atrial fibrillation and a high mortality rate (approximately 19% in year 1). The NRAF dataset contains both administrative and chart-review data on 3932 Medicare beneficiaries.
Progress Report:
This project focuses on mortality in elderly patients with heart disease. Congestive heart failure affects at least 5 million Americans. Prior research has focused on heart failure in patients who have systolic dysfunction (inability of the heart to squeeze normally). However, among the elderly, diastolic dysfunction (inability of the heart to relax normally) is more common than systolic dysfunction and both type of heart failure increase mortality and decrease quality of life.
The investigators have correlated how gender, age, heart function, laboratory tests, and medications affect the risk of death in patients who have heart failure. They found that predictors of mortality were different in the two subpopulations: among elderly patients with diastolic dysfunction a common test of renal function (BUN) was the only independent predictor of death; among elderly patients with systolic dysfunction the independent predictors of death were advanced age, prior heart attack, high-dose diuretics (water pills), or more severe systolic dysfunction on echocardiography. Patients with systolic dysfunction had a significantly greater risk of death. Thus, although both types of heart failure have similar signs (e.g. ankle swelling) and symptoms (e.g. shortness of breath), their prognosis and factors affecting prognosis differed.
How comorbid conditions affect the risk of death in patients who have atrial fibrillation (AF) and other heart conditions is unclear. AF causes an irregular heart rate and affects 2-3 million Americans. Prior research has determined that patients with AF have a high mortality rate. The cause of this increased mortality is partly from an increased rate of stroke in AF and partly from the company that AF keeps-advanced age, high blood pressure, diabetes, and heart disease. Determining which factors are most strongly associated with mortality may allow clinicians to determine treatment priorities.
The goal of this project is to determine how to control for the affect of co-morbid conditions when quantifying the risk of death from AF and other heart diseases. To quantify the effect of co-morbid conditions, investigators analyze large data sets. The most available large data sets are administrative data, such as Medicare Part A Records (MedPAR) that contain thousands of records, each with lists of co-morbid conditions noted as ICD-9 (International Classification of Disease-9) codes. The goal of this project is to learn how to use these data to quantify the affect of co-morbid conditions on mortality in Medicare beneficiaries who have AF and other heart disease.
Final Report:
In patients with heart failure, predictors of mortality vary by age and by the presence of preserved or reduced LVEF. Traditional predictors of mortality in patients with reduced LVEF may not apply to elderly patients with preserved LVEF.
Now that we have finished the above manuscript, we will focus on how to control for the effect of co-morbid conditions when quantifying the risk of death from AF and other heart diseases. This knowledge will help clinicians to understand the interaction between AF and comorbidities, and to target specific comorbid conditions to reduce risk of death. We will focus on two popular comorbidity measurements that use administrative databases-the Charlson-Deyo scheme1 and the Elixhauser scheme.2 Neither scheme was developed and tested in populations with heart disease. Thus, their applicability to the AF population is unknown. Purposes of the study are: (1) to evaluate predictive accuracy of two existing comorbidity schemes to each other and to a disease-specific co-morbidity index, CHADS2, that has been used to predict stroke in the AF population.3
We have made two important pieces of progress towards the AF analysis. First, we have obtained permission from the Center of Medicare and Medicaid Services to obtain administrative data from approximately 15,000 patients who have AF. The primary analysis of these data is supported by a grant from the American Heart Association, but funding from the Longer Life Foundation allows for a specific analysis of mortality. Second, we have developed the macros in SAS that will allow us to implement the Charlson-Deyo and the Elixhauser schemes and to compare their predictive accuracy on the basis of calibration and discrimination.
