269551 Getting to meaningful use: Improving data reliability and validity for diabetes and cardiovascular disease care among 13 community health centers

Monday, October 29, 2012 : 2:30 PM - 2:50 PM

Chatrian Kanger, MPH , Division of Evaluation, Louisiana Public Health Institute (LPHI), New Orleans, LA
Snigdha Mukherjee, PhD , Louisiana Public Health Institute, New Orleans, LA
Lisanne Brown, PhD , Division of Evaluation and Research, Louisiana Public Health Institute, New Orleans, LA
Mark Diana, PhD , Global Health Systems and Development, Tulane University, New Orleans
Deborah Even, MSN, MPH , Health Systems Division, Louisiana Public Health Institute, New Orleans, LA
Rodrigo Gamarra, MD, MHA , Management, Access Health Louisiana, Luling, LA
Haichang Xin, PhD , Evaluation Division, Louisiana Public Health Institute (LPHI), New Orleans
Amanda Carruth , Health Systems Division, Louisiana Public Health Institute, New Orleans, LA
Anjum Khurshid, MBBS, PhD , Health Systems Development, Louisiana Public Health Institute, New Orleans, LA
While the benefits of standardized electronic medical record (EMR) data and measurement may be obvious to improve population-level disease management and to support core public health functions, many communities still face challenges implementing and adhering to the standards. Most clinicians want to follow nationally recognized quality measures, such as NCQA/HEDIS. But how can members of a care team meaningfully utilize their own data if they do not trust the numbers or are not even aware that discrepancies exist between how their EMR system is capturing and reporting their data compared to national quality measure specifications? In an effort to build trust in EMR-generated clinical quality and outcomes reports, the Crescent City Beacon Community implemented a data reporting & standardization project within a 16-month period among 18 diverse community health centers in the Greater New Orleans (GNO) area. The project succeeded in bringing together Data/Quality Improvement managers to form a supportive learning collaborative, forged a unique partnership with EMR vendors, and provided rapid feedback to practices via local-level technical assistance. Pre/post intervention data reporting error rates, error types, and implications will be shared. Successes and lessons learned regarding implementing a community-wide project of this nature will be noted throughout. The resources needed to execute this type of effort will also be discussed.

Learning Areas:
Chronic disease management and prevention
Program planning
Public health or related research

Learning Objectives:
1. Design a data standardization and reporting strategy to improve population-level data capture and reporting across diverse clinical practice sites 2. Identify threats to data validity and reliability when translating national (e.g. NCQA/HEDIS) measure specifications into EMR vendor specifications. 3. Discuss the importance of data reporting standardization and the need for data quality audits.

Keywords: Reporting, Quality Improvement

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been an Evaluation Manager working with community health centers implementing EMRs for the past 6 years. My work has primarily focused on providing hands-on technical assistance to Data and QI Managers in data capture, extraction/reporting, and interpretation of clinical quality measures in their clinical settings using their EMR systems.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.