Beginning in 2021, the Centers for Medicare & Medicaid Services (CMS) will allow reporting through Merit-Based Incentive Payment System (MIPS) Value Pathways (MVP). According to the CMS, this new participation framework seeks “to move from siloed activities and measures and toward an aligned set of measure options more relevant to a clinician’s scope of practice that is meaningful to patient care.”
Goals of the Quality Payment Program (QPP) are to increase quality of care and improve patient outcomes. According to the CMS, quality measures are useful tools for quantifying processes, outcomes and/or systems that improve the ability to provide effective, safe, efficient, patient-centered, equitable and timely care. Although quality measures are already an integral facet of measuring value and patient outcomes, they haven’t reached their full potential. MVPs still face challenges endemic to quality measurement, such as crafting measures and collecting feedback.
Siloed Data
Lisa Suter, MD, associate professor of medicine, Section of Rheumatology, Yale University School of Medicine, New Haven, Conn., is a leading expert in rheumatology performance measurement and serves as a co-chair of the ACR’s Quality Measures Subcommittee. She has led, directed or consulted on the development of 33 hospital-level outcome measures, three clinician-level outcome measures and 11 clinician-level process measures; 25 are in current or planned use in federal payment programs.
The current difficulty, Dr. Suter believes, is that there are simultaneously too much and too little data. Providers collect large amounts of data during patient visits—health history, vital signs, new prescriptions and more—but those data are not always given context and purpose. “What we have right now is a lot of isolated data,” she says. “There is an overwhelming flood of information that’s not getting harnessed for advanced care. We don’t use it or leverage it.”
Measuring for quality aims to bridge that gap by tracking data and leveraging it for a better understanding of how to deliver comprehensive quality care. Quality measures capture and turn data into easily understood statistics, making it easier for previously siloed physicians to share information that increases the quality of care.
Creating Measures & Seeing Outcomes
Quality measures are created using the latest research with important treatment implications; many are based on clinical practice guidelines. Evidence-based guidelines are developed to reduce inappropriate care, minimize geographic variation in practice patterns and enable effective use of healthcare resources. Adherence to practice guidelines is voluntary and cannot guarantee any specific outcome, but they are intended to provide guidance for patterns of practice.
