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Quality Measures in Breast Reconstruction: A Systematic Review.
Quality Measures in Breast Reconstruction: A Systematic Review. Annals of plastic surgery Nazerali, R. N., Finnegan, M. A., Divi, V., Lee, G. K., Kamal, R. N. 2017Abstract
The importance of providing quality care over quantity of care, and its positive effects on health care expenditure and health, has motivated a transition toward value-based payments. The Centers for Medicare and Medicaid Services and private payers are establishing programs linking financial incentives and penalties to adherence to quality measures. As payment models based on quality measures are transitioned into practice, it is beneficial to identify current quality measures that address breast reconstruction surgery as well as understand gaps to inform future quality measure development.We performed a systematic review of quality measures for breast reconstruction surgery by searching quality measure databases, professional society clinical practice guidelines, and the literature. Measures were categorized as structure, process, or outcome according to the Donabedian domains of quality.We identified a total of 27 measures applicable to breast reconstruction: 5 candidate quality measures specifically for breast reconstruction surgery and 22 quality measures that relate broadly to surgery. Of the breast reconstruction candidate measures, 3 addressed processes and 2 addressed outcomes. Seventeen of the general quality measures were process measures and 5 were outcome measures. We did not identify any structural measures.Currently, an overrepresentation of process measures exists, which addresses breast reconstruction surgery. There is a limited number of candidate measures that specifically address breast reconstruction. Quality measure development efforts on underrepresented domains, such as structure and outcome, and stewarding the measure development process for candidate quality measures can ensure breast reconstruction surgery is appropriately evaluated in value-based payment models.
View details for DOI 10.1097/SAP.0000000000001088
View details for PubMedID 28570449