Economic Consequences of Advanced Testing for Subclinical Cardiovascular Disease

Summary

Principal Investigator: Leslee J Shaw
Abstract: DESCRIPTION (provided by applicant): The current application is written as a response to requests for applications in the area of NIH Challenge Grants in Health and Science Research (RC1) in the Broad Challenge Area of (04) CLINICAL RESEARCH, Specific Challenge Area: 04-HL-104 - To perform secondary analyses of existing data to answer important clinical and preventive medicine research questions, specifically to determine the cost effectiveness of preventive interventions. This Secondary Data Analysis: The Economic Consequences of Advanced Testing for Subclinical Cardiovascular Disease (CVD) is proposed to be completed in the NIH- NHLBI-sponsored Multi-Ethnic Study of Atherosclerosis (MESA). Despite the burden of CVD, routine testing beyond measurement of cholesterol, is not considered of medical necessity and supported by national healthcare coverage decisions. Recent technology evaluations by the US Preventive Services Taskforce and others have voiced strong concerns over the untoward consequences of additional CVD testing (beyond measurement of cholesterol) including the potential for unwarranted, induced testing and a lifelong stigma and anxiety following a diagnosis of subclinical atherosclerosis. Past arguments have cautioned over embarking on nationwide screening for CVD due to a lack of high quality evidence on improved risk detection. Recent data from large patient registries and population series report a high degree of prognostic accuracy for CAC, Hs-CRP, and C-IMT;including the recently results from the NIH-NHLBI-sponsored MESA revealing effective risk stratification of women and men of diverse ethnicity from geographically-diverse regions of this country. Yet, concerns remain that testing will beget more testing and initiation of a strategy for detection of markers for subclinical atherosclerosis may result in early and lifelong higher patterns of resource consumption that would not have been realized without the initial documentation of measureable subclinical CVD. Accordingly, high quality evidence unfolding the cost implications of CVD testing is necessary in order to frame the frequently reported improved detection of risk within the context of the potential untoward sequelae of testing where excessive costs exceed any derivable benefit. However, meaningful data on "real world" resource consumption patterns and healthcare costs following subclinical CVD testing in asymptomatic individuals is limited;principally comprised of decision models or small patient series. Challenges within the field of cost effectiveness of testing in asymptomatics include reliance upon decision modeling lacking input from "real world" resource utilization;rendering the modeling results difficult to interpret. For example, models that indicate a sizeable cost savings for strategies guided by Hs-CRP or CAC results may be optimistic and fail to consider the untoward consequences of testing or costs which may ensue for less extensive abnormalities or from test layering. The data available in MESA represents a sizeable step forward in our knowledge base of induced patterns of testing and treatment from a large cohort of middle-aged and elderly adults. We propose to examine downstream costs using a resource-based methodology in a large population cohort of adults enrolled in the MESA. Our application includes a systematic approach to cost analysis based on Medicare reimbursement rates for estimating 4-5 year CVD costs. Our analytical approach will be to compare costs within the context of the added benefit of advanced CVD testing including improved risk re-classification as well as the cumulative costs (including those associated with incidental findings and expected radiation- induced cancers). We propose that an analytic approach that emulates iterative steps in risk detection initially classifying outcome based on the FRS followed by a given advanced testing option. Thus, allowing for calculation of the incremental costs in relation to the added benefit of improved classification of risk or risk re- classification;using recent approaches described by Pencina and Wilson. We propose a novel, disease- specific cost effectiveness metric of cost per net reclassification of CVD events (i.e., the cost per 1 new CVD event detected with advanced CVD testing when compared to the FRS). Our analytical approach is both iterative and strategy based examining costs associated with an FRS strategy compared with a strategy with one or more of our advanced tests (CAC scoring, C-IMT, or Hs-CRP). We believe that this novel cost effectiveness metric more closely corresponds to more recent risk classification approaches and distinguishes the added cost and benefit of advanced testing compared with the standard FRS. Limited information is available to inform public policy with regards to the economic consequences of advanced testing for subclinical CVD ensuing following index testing using either laboratory, such as Hs-CRP, or imaging biomarkers, such as CAC scoring. Given the paucity of available data, the current application of secondary data analysis in MESA identifying resource consumption patterns and estimating downstream costs of care can provide a tremendous step forward in the quality of available evidence. This current evaluation empowers MESA with an unparalleled potential to identify the most efficient and accurate methods for CVD testing in asymptomatic individuals. The current application combines exceptional clinical outcomes, imaging, and economic expertise put forth in the evaluation of available MESA data to advance our understanding of the clinical and economic benefits and risk associated with CVD testing in asymptomatic individuals. The current study aims to evaluate 5-year cost for heart disease care in over 6 thousand individuals. We further propose to compare costs of heart disease care in subgroups of adults with low to high risk cardiac biomarkers. We will compare costs in addition to the added benefit of improved detection of heart disease risk using several cardiac biomarkers.
Funding Period: ----------------2009 - ---------------2011-
more information: NIH RePORT