Abstract 175: Development of a National Dataset for Ambulatory Quality Improvement and Research

    loading  Checking for direct PDF access through Ovid

Abstract

Background: Electronic Health Record (EHR) data provides a wealth of patient data valuable to providers, organizations, registries, and researchers. The Guideline Advantage™ (TGA) has been developed by the American Heart Association, American Cancer Society, and American Diabetes Association as a national ambulatory registry to cover primary and secondary prevention across multiple disease groups.

Methods: The program leverages EHR data to populate a clinical registry and provide population health measurement and analytic tools to drive improvements in population health and support registry-based research. TGA uses a data extraction model without the restrictions and resource demands of traditional data abstraction or interface mechanisms typical of clinical registries. This model supports customization and flexibility in data alignment which allows for more accurate measurement and representation of the care being delivered. The web-based population health tool delivers a clear lens into clinical data from a population level to a patient level, simplifying data stewardship and improvement tracking. Through these methods, the program has grown to include 25,091,500 patient observations for 797,079 unique patients. 408 providers and their clinical teams have access to population health analytic tools, quality improvement support, and resources to drive improvements in the care they are delivering.

Discussion: While there are several disease-specific registries in existence, there have not yet been integrated solutions that can expand across key chronic and acute conditions facing ambulatory patients. To obtain data across multiple conditions without a high resource burden, TGA is maintaining a data extract model that foregoes traditional barriers and resource burdens such as extensive query development, abstraction, or maintaining costly interfaces. The data extraction model affords the ability to obtain exponentially more data than abstraction models allowing the registry to cover multiple disease groups. This breadth of data improves the application of the registry in both the practice setting and research. With this data, practices are able to look across their entire population to identify high-risk or at-risk populations with a single condition or comorbid conditions and create cohorts of patients to target with quality improvement strategies. Providing clinicians and researchers a clear look into complete and longitudinal clinical data is critical to supporting quality improvement activities pivotal to success in value-based care models and the advancement of novel research in primary and secondary prevention.

Related Topics

    loading  Loading Related Articles