169 Developing Clinical Rules Logic for Emerging Infectious Diseases for Use in Public Health Decision Support Engine

Sunday, June 19, 2016: 3:00 PM-3:30 PM
Exhibit Hall Section 1, Dena'ina Convention Center
Julie M Lipstein , L-3 National Security Solutions, Reston, VA
Sunanda McGarvey , Northrop Grumman, Atlanta, GA
Catherine Staes , University of Utah, Salt Lake City, UT

BACKGROUND: Hospitals, laboratories, and clinicians are required by law to report certain infectious diseases of interest to local or state Public Health Departments.  Typically the information to indicate when a case report should be sent is presented in a format that is not easily computable or accessible.  In a world where more Electronic Health Record systems are being implemented, the goal is to transition these case reports from a manual process to a more automated and electronic process.  This not only lessens the burden for public health reporters but also ensure more timely, complete, and accurate data being sent to Public Health. 

METHODS: This poster aims to highlight the difficulties and issues using CSTE Position Statement format and criteria when developing computable clinical rules logic.  It also demonstrates the limitation of a two-dimensional table format when the criteria could be more accurately represented in clinical rules logic. 

RESULTS: In using an emerging and complicated disease such as Severe Acute Respiratory Syndrome (SARS-CoV) it becomes more apparent that Decision Support engines and rules logic formats are necessary to more accurately reflect reporting criteria.  While some criteria are easily translated into rules logic (e.g., laboratory and clinical findings), other criteria (e.g., epidemiologic) do not convert to rules logic easily as they are often times not coded in a standardized format within an Electronic Health Record.

CONCLUSIONS: The Centers for Disease Control and Prevention is teaming up with the Council of State and Territorial Epidemiologists to develop the Reportable Conditions Knowledge Management System (RCKMS) for jurisdictions to manage their reporting criteria centrally and allow for easier conversion into clinical rules logic for inclusion into the Public Health Decision Support engine.  The RCKMS is envisioned to be an authoritative, real-time portal to enhance disease surveillance by providing comprehensive information to public health reporters about the “who, what, when, where, and how” of reporting.