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Measuring quality of care for people with Mulitple Chronic Conditions

Measuring quality of care for people with Mulitple Chronic Conditions
衡量多种慢性病患者的护理质量
批准号:
8726014
负责人:
ELIZABETH A BAYLISS
金额:
$17.93万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-05-01 至 2016-10-31

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DESCRIPTION (provided by applicant): The population of persons with multiple chronic conditions (MCC) is large, growing, and consumes a disproportionate share of healthcare resources. It is well recognized that we need to optimize care for this population. However, there are no existing standards, guidelines, or measures of care quality designed specifically for MCC patients or populations. For example, existing disease-specific goals and metrics may incentivize inefficient care delivery and risk adverse unintended consequences, and standard prevention guidelines may need to be altered based on morbidity burden. There have multiple calls to develop and implement metrics that are relevant across chronic conditions and can be used on a population level to promote patient-centered approaches to MCC care. We will develop and evaluate a preliminary composite measure of care quality for populations with MCC. This 'MCC quality composite' will be based on electronically available data and will be applicable across conditions. It will enhance our understanding of how to provide high quality health care for patients with MCC by: a) permitting evaluation of system-level interventions to improve MCC care in real-world settings, b) demonstrating actionable areas for systems and clinicians to improve MCC care, c) establishing a basis for future MCC quality metric development, and d) introducing the concept of routine evaluation of MCC care quality. The proposed project will take advantage of a unique data infrastructure of systematically collected patient- reported data, rich clinical data, and health plan administrative data on over 44,000 Medicare beneficiaries with MCC in an integrated delivery system. We will use a modified Delphi process to enhance and refine a list of measure components. We will then use multivariable modeling to evaluate the MCC composite by assessing hospital utilization and patient experience as a function of the measure, and describing patient-level characteristics associated with receipt of high quality MCC care. Successful completion of the proposed project will improve care for the AHRQ priority populations of the elderly and persons with chronic illness; and will address the goal of the US Department of Health and Human Services (HHS) initiative on MCC to "identify, develop, endorse, and use key quality metrics, in the form of performance measures, to promote best practices in the general care of individuals with MCC."
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