Online Program

Development of an EMR-based database for anticoagulation/anticlotting outcome research

Wednesday, November 6, 2013 : 9:30 a.m. - 9:50 a.m.

Kourosh Ravvaz, MD, MPH, Doctoral Program in Biomedical and Health Informatics, University of Wisconsin-Milwaukee, Milwaukee, WI
Peter Tonellato, PhD, Center for Biomedical Informatics, Harvard Medical School, Boston, MA
Michael Michalkiewicz, PhD DVM, Patient Centered Research, Aurora Health Care, Aurora Research Institute, Milwaukee, WI
Warfarin is one of the most frequently prescribed drugs used to prevent blood clotting. However, warfarin's therapeutic window is narrow (2.0 < INR < 3.0) relative to a large diverse urban patient population where therapeutic dosing may vary as much as 15 fold. Consequently, warfarin initiation requires intensive patient monitoring and achieving “therapeutic” dosing may require frequent dose modification following complex dose-adjustment protocols. Dozens of algorithms exist that integrate clinical and genetic factors into individualized predictive models for warfarin dose. However, there has been little testing of algorithms across a large diverse urban population. Consequently, the value of sophisticated algorithms based on genetic and clinical data remains an open question.

Objective: The Aurora Health Care (AHC) Research Institute and Zilber School of Public Health, University of Wisconsin-Milwaukee are conducting a multi-phase retrospective EMR-based longitudinal anticoagulation clinical database project to study anticoagulation dosing algorithms. Methods: Steps in the database development include: requirements analysis (identification of clinical variables); Data collection, quality control and integration process; and modeling and simulation analysis. Data sources included two EMR systems. A one-way honest broker was used to protect patient confidentiality. Results: The initial database contains over 110,000 unique anticoagulation patients from 15 inpatient facilities across south-eastern Wisconsin from 2002-2009. Age, race and geographical distributions of the cohort are consistent with the State of Wisconsin and Milwaukee County. This is one of the largest warfarin urban patient population databases. Preliminary simulations include segmenting the population and identifying the optimal warfarin dosing protocol for any given segment. Discussion: We have developed a normalized “Anticoagulation” registry containing over 110, 000 patients with the goal of simulating and testing warfarin dosing algorithms designed to achieve therapeutic dose more quickly. Such a resource is invaluable to pursue the broad objectives of individualized and thus, improved patient-centric outcome research.

Learning Areas:

Other professions or practice related to public health
Public health or related research
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Demonstrate the value of a retrospective EMR-based longitudinal anticoagulation clinical database in patient-centric outcome research.

Keyword(s): Outcomes Research

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have played a major role in designing and conducting the study. So, I am able to deliver appropriate content with regard to the content of my submitted abstract.
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.