Abstract 223: Innovations in Quality Improvement

Abstract

Innovative Medical Platform Optimizing Research and Technology (IMPORT)> Background: A medical group, pharmaceutical company, and data harvesting and integration company collaborated to test an innovative approach to quality improvement (QI) that utilizes clinical expertise, advanced outcomes analytics, electronic medical records (EMR), and a cloud technology data harvesting platform. The objective of this project was to measure the ability of this collaborative project to effectively and efficiently identify quality improvement opportunities. Methods: This was a retrospective EMR analysis which utilized Solution for Quality Improvement (SQI) platform on an advanced electronic medical record system. All patients in one primary care medical practice seen from 7/1/2009 - 7/31/2011 were included. The primary outcomes were effectiveness of the platform to integrate data, measured by data density of diabetes laboratory and clinical quality performance values from structured EMR fields and unstructured physician notes; and efficiency, measured as the time period from SQI data mapping to final results analysis. A secondary outcome was the ability of the project to identify and target meaningful QI opportunities. Results: SQI collected data from 9,294 patient records, including 73,706 office visits and 35,602 physician dictated visit notes. Of these records, 6,251 cardiovascular patients were identified with diabetic patients accounting for 1,561 (25%) of these. Values and measurement dates for A1c, LDL, and blood pressure values were harvested in 83%, 75%, and 96% of these diabetic patients, respectively. The collection of other diabetic preventive services performance indicators was relatively low. Additional QI is being done to ensure complete capture of data. The time period for analysis, including 3 iterative rounds of expanded data identification, was 15 weeks total. Through this project, 3 specific areas of QI were prioritized: improve dictation/documentation of preventative diabetes care recommendations; implement diabetes panel management; and develop electronic diabetes patient reported outcomes screening tools. Conclusion: This collaboration led to an efficient and effective QI analysis in diabetes care. Results of the analysis have led to development and implementation of meaningful QI initiatives. Future implications include the use of this project’s approach to rapidly re-measure performance after implementation of the QI initiatives and expansion of the collaboration from a 4 physician practice to the network of 100 primary care physicians.