Clinician Responses to a Clinical Decision Support Advisory for High Risk of Torsades de Pointes

Author:

Gallo Tyler12,Heise C. William13ORCID,Woosley Raymond L.14ORCID,Tisdale James E.56ORCID,Tan Malinda S.7,Gephart Sheila M.8,Antonescu Corneliu C.9ORCID,Malone Daniel C.7ORCID

Affiliation:

1. Division of Clinical Data Analytics and Decision Support University of Arizona College of Medicine–Phoenix AZ

2. Department of Pharmacy Practice and Science University of Arizona College of Pharmacy Phoenix AZ

3. Department of Medical Toxicology Banner–University Medical Center Phoenix Phoenix AZ

4. Arizona Center for Education and Research on Therapeutics Oro Valley AZ

5. Department of Pharmacy Practice College of Pharmacy Purdue University Indianapolis IN

6. Division of Clinical Pharmacology School of Medicine Indiana University Indianapolis IN

7. College of Pharmacy University of Utah Salt Lake City UT

8. Community and Health Systems Science Division College of Nursing University of Arizona Tucson AZ

9. BannerHealth Greeley CO

Abstract

Background Torsade de pointes (TdP) is a potentially fatal cardiac arrhythmia that is often drug induced. Clinical decision support (CDS) may help minimize TdP risk by guiding decision making in patients at risk. CDS has been shown to decrease prescribing of high‐risk medications in patients at risk of TdP, but alerts are often ignored. Other risk‐management options can potentially be incorporated in TdP risk CDS. Our goal was to evaluate actions clinicians take in response to a CDS advisory that uses a modified Tisdale QT risk score and presents management options that are easily selected (eg, single click). Methods and Results We implemented an inpatient TdP risk advisory systemwide across a large health care system comprising 30 hospitals. This CDS was programmed to appear when prescribers attempted ordering medications with a known risk of TdP in a patient with a QT risk score ≥12. The CDS displayed patient‐specific information and offered relevant management options including canceling offending medications and ordering electrolyte replacement protocols or ECGs. We retrospectively studied the actions clinicians took within the advisory and separated by drug class. During an 8‐month period, 7794 TdP risk advisories were issued. Antibiotics were the most frequent trigger of the advisory (n=2578, 33.1%). At least 1 action was taken within the advisory window for 2700 (34.6%) of the advisories. The most frequent action taken was ordering an ECG (n=1584, 20.3%). Incoming medication orders were canceled in 793 (10.2%) of the advisories. The frequency of each action taken varied by drug class ( P <0.05 for all actions). Conclusions A modified Tisdale QT risk score–based CDS that offered relevant single‐click management options yielded a high action/response rate. Actions taken by clinicians varied depending on the class of the medication that evoked the TdP risk advisory, but the most frequent was ordering an ECG.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Pocket cardiology;Comprehensive Precision Medicine;2024

2. Interpretable Machine Learning Prediction of Drug-Induced QT Prolongation: Electronic Health Record Analysis;Journal of Medical Internet Research;2022-12-01

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