Quality Improvement in Otolaryngology-Head and Neck Surgery: Developing Registry-Enabled Quality Measures From...

Quality measurement can drive improvement in clinical care and allow for easy reporting of quality care by clinicians, but creating quality measures is a time-consuming and costly process. ECRI (formerly Emergency Care Research Institute) has pioneered a process to support systematic translation of clinical practice guidelines into electronic quality measures using a transparent and reproducible pathway. This process could be used to augment or support the development of electronic quality measures of the American Academy of Otolaryngology-Head and Neck Surgery Foundation (AAO-HNSF) and others as the Centers for Medicare and Medicaid Services transitions from the Merit-Based Incentive Payment System (MIPS) to the MIPS Value Pathways for quality reporting.

We used a transparent and reproducible process to create electronic quality measures based on recommendations from 2 AAO-HNSF clinical practice guidelines (cerumen impaction and allergic rhinitis). Steps of this process include source material review, electronic content extraction, logic development, implementation barrier analysis, content encoding and structuring, and measure formalization. Proposed measures then go through the standard publication process for AAO-HNSF measures.

The 2 guidelines contained 29 recommendation statements, of which 7 were translated into electronic quality measures and published. Intermediate products of the guideline conversion process facilitated development and were retained to support review, updating, and transparency. Of the 7 initially published quality measures, 6 were approved as 2018 MIPS measures, and 2 continued to demonstrate a gap in care after a year of data collection.

Developing high-quality, registry-enabled measures from guidelines via a rigorous reproducible process is feasible. The streamlined process was effective in producing quality measures for publication in a timely fashion. Efforts to better identify gaps in care and more quickly recognize recommendations that would not translate well into quality measures could further streamline this process.