A computerized scoring system to improve assessment of heparin‐induced thrombocytopenia risk
Author(s): ,
T. Gallo
Affiliations:
Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine – Phoenix, Phoenix, USA. Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Phoenix, USA
Correspondence: Tyler Gallo, University of Arizona, College of Medicine – Phoenix, 475 N. 5th Street, Phoenix, AZ 85004, USA|Tel.: +1 602 827 2696|E‐mail: tgallo@email.arizona.edu
,
S. C. Curry
Affiliations:
Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine – Phoenix, Phoenix, USA. Department of Medical Toxicology, Banner – University Medical Center Phoenix, Phoenix, USA
,
A. Padilla‐Jones
Affiliations:
Banner Research Institute, Banner – University Medical Center Phoenix, Phoenix, USA
,
C. W. Heise
Affiliations:
Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine – Phoenix, Phoenix, USA. Department of Medical Toxicology, Banner – University Medical Center Phoenix, Phoenix, USA
,
K. S. Ramos
Affiliations:
Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine – Phoenix, Phoenix, USA
,
R. L. Woosley
Affiliations:
Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine – Phoenix, Phoenix, USA
R. A. Raschke
Affiliations:
Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine – Phoenix, Phoenix, USA
ISTH Academy. Gallo T. Feb 8, 2019; 273372
Tyler Gallo
Tyler  Gallo
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Background
(HIT) is an immune‐mediated adverse drug event associated with life‐threatening thrombotic complications. The 4Ts score is widely used to estimate the risk for HIT and guide diagnostic testing, but it is not easily amenable to computerized clinical decision support (CDS) implementation.
Objectives
Our main objective was to develop an HIT computerized risk (HIT‐CR) scoring system that provides platelet count surveillance for timing and degree of thrombocytopenia to identify those for whom diagnostic testing should be considered. Our secondary objective was to evaluate clinical management and subsequent outcomes in those identified as being at risk for HIT.
Methods
We retrospectively analyzed data from a stratified sample of 150 inpatients treated with heparin to compare the performance of the HIT‐CR scoring system with that of a clinically calculated 4Ts score. We took a 4Ts score of ≥ 4 as the gold standard to determine whether HIT diagnostic testing should be performed.
Results
The best cutoff point of the HIT‐CR score was a score of 3, which yielded 85% raw agreement with the 4Ts score and a kappa of 0.69 (95% confidence interval 0.57–0.81). Ninety per cent of patients with 4Ts score of ≥ 4 failed to undergo conventionally recommended diagnostic testing; 38% of these experienced persistent, unexplained thrombocytopenia, and 4% suffered life‐threatening thrombotic complications suggestive of undiagnosed HIT.
Conclusion
The HIT‐CR scoring system is practical for computerized CDS, agrees well with the 4Ts score, and should be prospectively evaluated for its ability to identify patients who should be tested for HIT.
Keyword(s)
clinical, decision support systems, drug‐related side effects and adverse reactions, epidemiology, quality improvement, thrombocytopenia
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