October 9 - 12, 2012
Building 10 & Natcher Conference Center
- General Schedule of Events
- Opening Plenary Session
- Concurrent Symposia Sessions
- Poster Sessions
- National Graduate Student Research Conference
- FARE Award Ceremony
- Special Exhibits on Resources for Intramural Research
- TSA Research Festival Exhibit Show
- Clinical Center Tours
- Research Festival Committees
- Past Research Festivals
Metrics for assessing the Quality of Value Sets in Clinical Quality Measures
| Thursday, November 07, 2013 — Poster Session II | |||
|---|---|---|---|
12:00 p.m. – 2:00 p.m. |
FAES Academic Center (Upper-Level Terrace) |
NLM |
RSCHSUPP-37 |
Authors
- R Winnenburg
- O Bodenreider
Abstract
Background: Value sets enumerate the list of concepts (terminological codes) corresponding to clinical data elements and are a key element of clinical quality measures. Here, we assess the quality of value sets in clinical quality measures, both individually (completeness, correctness) and as a population of value sets (non-redundancy). Materials and methods: The concepts from a given value set are expected to be rooted by one or few ancestor concepts and the value set is expected to contain all the descendants of its root concepts (extension) and only these descendants. We assess the completeness and correctness of individual value sets by comparing the original list of concepts to the extension derived from the roots. We assess the non-redundancy of value sets for the entire population of value sets (within a given code system) using the Jaccard similarity measure. Results: Applied to 1,054 value sets from clinical quality measures for the 2014 Meaningful Use criteria, we identified 127 inconsistent value sets and 453 incomplete value sets, as well as 58 duplicate value sets. Conclusion: These metrics facilitate the curation of value sets by providing compact indicators of their completeness, correctness, and non-redundancy.
