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Case Study - Maximizing the Quality Performance Score

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Summary: Gastroenterology Associates of Pensacola, one of the busiest endoscopy centers in Florida, achieved Exceptional Performance for the second consecutive year, and a 95% score for the Quality performance category for their 2018 MIPS submission. By utilizing SPH Analytics' Population Care™ | Quality Measures solution for MIPS measurement and reporting, with SPH's proprietary Three Facet Data Mining™ to identify custom codes and terminology used in their Allscripts EHR and practice management system, the practice is now set up for success in quality improvement for years to come. Background: CMS is required by law to implement the Quality Payment Program, which rewards value and outcomes through the Merit-based Incentive Payment System (MIPS). Eligible providers who bill Medicare Part B are required to submit data in four areas: Quality, Improvement Activities, Advancing Care Information (now re-named to Promoting Interoperability), and Cost on an annual basis. The Quality category includes nearly 300 MIPS Registry measures to evaluate clinical care and patient outcomes. For 2018, eligible clinicians were required to choose up to six measures to be submitted and scored for the Quality category. The clinical quality measure includes a calculation of the numerator and denominator of the measure to give a performance met percentage across the patient population. The denominator represents the patients or encounters that qualify for the measure, and the numerator represents the clinical process or outcome to be performed or tracked on those patients. Many of the numerator concepts are defined by Quality Data Codes (QDCs), and appropriate documentation according to the measure specification is required to accurately calculate measure performance. Challenge: Gastroenterology Associates' previous electronic medical record (EMR) was not automatically generating the Quality Data Codes (QDCs) required for the MIPS Registry Measures, which would have resulted in both an inaccurate and lower Quality Performance score. Maximizing the Quality Performance Score Preparing for MIPS data submission Case Study SPH Population Care

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