Elderly patients often face high-risk health care decisions about vascular disease, and informed decisions are needed to obtain the best results. Carotid revascularization, via surgical carotid endarterectomy or carotid artery stenting, is among the most frequently performed vascular procedures, and is widely recommended to prevent future stroke. Such treatment is commonly performed for asymptomatic stenosis, where the risk of future stroke is low without intervention, so the potential benefit of intervention is much less than in symptomatic patients. When considering revascularization for asymptomatic carotid stenosis, patients and providers must weigh the up-front risk of surgery against the long-term risk of stroke, taken in the context of the patient's life expectancy. The best decision in ths clinical scenario is revascularization for low-risk patients who will live long enough to benefit from surgery, and medical treatment for higher risk patients with shorter life expectancy. However, providers and policymakers have found it difficult to identify the key variables to inform these decisions, both in terms of the short-term risks of endarterectomy, as well as the long- term risks of stroke or death. Health IT can be leveraged to support two key facets of this health care decision: (1) short-term surgical risk stratification by using detailed patient and procedural variables, such as those present in a clinical registry, and (2) longitudinal follow-up o assess the effectiveness of the revascularization in preventing stroke during the patient's remaining life. Our group has demonstrated that the first component can be established using real world data from a regional registry, and the second can be achieved in a broad, cost-effective manner by using administrative claims data. In the present application, we will develop and implement a merged clinical registry and claims health IT tool that will support clinical decision-making, in the ambulatory setting, for patients with asymptomatic carotid artery disease. This approach leverages the clinical detail present in registries with the complete follow-up available from administrative claims. Specifically, we will: (1) identify which asymptomatic patients are likely to receive unnecessary carotid revascularization, using a merged registry-claims dataset, and design a Health IT tool to convey these findings to providers, and (2) determine the potential cost savings associated with avoiding unnecessary carotid endarterectomy in asymptomatic patients. This health IT tool will identify patients who are least likely to benefit from carotid revascularization and allow patients and providers to make more informed choices in the ambulatory setting regarding medical management versus revascularization. This tool will also serve as a model for broader implementation, through the Society for Vascular Surgery Vascular Quality Initiative, and will inform policy makers about opportunities for reducing health care expenditures by reducing unnecessary care.

Public Health Relevance

Carotid revascularization is the most commonly performed vascular procedure, the goal of the procedure being to reduce future stroke risk. The procedure has maximum benefit in patients with symptomatic carotid disease, but is more often performed for asymptomatic patients where the risk of future stroke is low without intervention and for whom the potential benefit of endarterectomy is much less. Health IT can be leveraged to support two key facets of health care decision-making for patients with asymptomatic disease who are considering revascularization, namely: (1) short-term procedural risk stratification by using detailed patient and procedural variables, such as those present in a clinical registry, and (2) longitudinal follow-up to assess the effectiveness of clinical care in preventing stroke during the patient's remaining life. In the present application, we will develop and implement a merged clinical-claims health IT tool that will support clinical decision-making in the ambulatory setting for patients with asymptomatic carotid artery disease.

Agency
National Institute of Health (NIH)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21HS021581-02
Application #
8733508
Study Section
Health Care Technology and Decision Science (HTDS)
Program Officer
White, Jon
Project Start
Project End
Budget Start
Budget End
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Dartmouth College
Department
Surgery
Type
Schools of Medicine
DUNS #
City
Hanover
State
NH
Country
United States
Zip Code
03755
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