Performer: AZCERT, Inc.
Principal Investigator: Raymond L. Woosley, MD, PhD
Project Duration: 9/22/14 - 3/31/17
Regulatory Science Challenge
More than 160 medications, including 15 commonly prescribed antibiotics, have a known risk of causing life-threatening conditions, such as cardiac arrhythmia (particularly as manifested through prolongation of the QT period), and even sudden death. The safe use of these medicines requires that healthcare practitioners integrate an overwhelming amount of scientific and clinical data to assess their patients’ risk factors and choose from the many therapeutic options available.
The availability of electronic medical records is making it possible to create decision support systems for use in the clinic, helping ensure the safe use of medicines. However, some systems issue alerts that have limited impact because of alert fatigue, resulting in 60% to 90% of alerts being ignored. To be successful, support systems must be evidenced-based and provide clinically relevant, actionable alternatives at the point of care.
This project created and evaluated a Clinical Decision Support System for the safe and appropriate use of antibiotics that generates electronic alerts when a health care practitioner prescribes an antibiotic that poses a relevant risk of serious cardiac adverse events for a specific patient. By integrating information on the known risks of a drug with a patient’s specific characteristics, the system can help to personalize therapy and improve health outcomes. Two of the 26 hospitals in the Banner Health network participated in this demonstration project, with one site using the Clinical Decision Support System program and the other serving as comparison (control) site. Data from a baseline period was evaluated to ensure similarity of rates of antibiotic use and patient complexity. All of the products of this work are available to health care providers as open source. For more information, please see CredibleMeds.
- Expand the database of drugs recognized as prolonging QT (QTdrugs) to include therapeutic alternatives that can support the clinical decision tree for safe use of antibiotics.
- Develop a clinical decision tree algorithm for the appropriate use of antibiotics that incorporates the QTdrugs lists.
- Develop criteria for calculating a QT risk score and the score threshold for issuance of alerts in the pilot phase.
- Institute a Clinical Decision Support System tool incorporating the appropriate use of the developed antibiotics algorithm and QT risk scores, and assess the System effectiveness as demonstrated by actions taken within 8 and 24 hours of alert firing.
The final report from the researchers to the FDA included the following results:
- Established the infrastructure and partnerships necessary to create and implement a Clinical Decision Support System for use in modern health care environments.
- Developed a clinical decision tree for safe use of antibiotics based on an analysis of the types of infections that require treatment in the two clinical sites, the cultured infectious organisms, their sensitivities and the preferred therapies for these organisms.
- Analyzed the data generated by the use of the Clinical Decision Support System from the two clinical sites that were chosen for comparison and determined which outcome metrics had sufficient events to power a statistical analysis.
- During the five-month test period, the QT Risk Warning was triggered 101 times.
- After a warning, 17% of patients underwent an EKG within 24 hours and 14.1% were discontinued from a “known risk medication.”.
Schwartz PJ, Woosley RL. Predicting the Unpredictable: Drug-Induced QT Prolongation and Torsades de Pointes. J Am Coll Cardiol. 2016 Apr 5;67(13):1639-1650. doi: 10.1016/j.jacc.2015.12.063. PMID: 27150690.Woosley RL, Black K, Heise CW, Romero K. CredibleMeds.org: What does it offer? Trends Cardiovasc Med. 2018 Feb;28(2):94-99. doi: 10.1016/j.tcm.2017.07.010. Epub 2017 Aug 1. PMID: 28801207.
Woosley, R.L. Antibiotics, QT prolongation, TdP and Sudden Death: Fact or Fiction, Cardiology Today, September 2017 https://goo.gl/zbSjoL
Woosley RL, Whyte J, Mohamadi A, Romero K. Medical decision support systems and therapeutics: The role of autopilots. Clin Pharmacol Ther. 2016 Feb;99(2):161-4. doi: 10.1002/cpt.259. Epub 2015 Oct 22. PMID: 26352903.