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ANALYTICAL METHODS TO QUANTIFY RISK OF HARM FOR ALERT-OVERRIDDEN HIGH-RISK INTRAVENOUS MEDICATION INFUSIONS

<p>The medication errors
associated with intravenous (IV) administration may cause severe patient harm. To
address this issue, smart infusion pumps now include a built-in dose error
reduction system (DERS) to help ensure the safety of IV administration in clinical
settings. However, a drug limit alert triggered by DERS may be overridden by
the practitioners which can potentially cause patient harm, especially for
high-risk medications. Most analytical measures used to estimate the associated
risk of harm are frequency-based and only consider the overall drug performance
rather than the severity impact from individual alerts. Unlike these other
measures, the IV medication harm index attempts to quantify risk of harm for
individual alerts. However, it is not known how well these measures describe
the risk associated with alert-overridden scenarios. The goal of this research
was (1) to quantitatively measure the risk for simulated individual
alert-overridden infusions, (2) to compare these assessments against the risk
scores obtained among four different analytical methods, and (3) to propose
better risk quantification methods with a higher correlation to risk benchmarks
than traditional measures, such as the IV Harm index. </p>

<p>In this study, 25 domain
experts (20 pharmacists and 5 nurses) were recruited to assess the risk
(adjusted for risk benchmarks) for representative scenarios created based on
hospital alert data. Four analytical methods were applied to quantify risk for
the scenarios: the linear mixed models (Method A), the IV harm index (Method
B), Huang and Moh’s matrix-based ranking method
matrix-based method (Method C), and the analytical hierarchy process
method, adjusted by linear mixed models (Method D). Method A used seven alert
factors (identified as key risk factors) to build models for risk prediction,
and Methods B and C used two out of seven factors to obtain risk scores. Method
D used pairwise comparison surveys to calculate the risk priorities. The
quantified scores from the four methods were evaluated in comparison to the
risk benchmarks.</p>

<p>Risk assessment results
from the domain experts indicated that overdosing scenarios with continuous and
bolus dose field limit types had significantly higher risks than those of bolus
dose rate type. About the soft limit type, the expected risk in the group with
a large soft maximum limit was significantly higher than the group with a small
soft maximum limit. This significant difference could be found in the adult
intensive care unit (AICU), but not in adult medical/surgical care unit (AMSU).
The comparisons between four analytical methods and risk benchmarks showed that
the risk scores from Method A (<i>ρ</i> =
0.94) and Method D (<i>ρ </i>= 0.87) were
highly correlated to the risk benchmarks. The risk scores derived from Method B
and Method C did not have a positive correlation with the benchmarks.</p>

<p>This study demonstrated
that the traditional IV harm index should include more risk factors, along with
their interaction effects, for increased correlation with risk benchmarks.
Furthermore, the linear mixed models and the adjusted AHP method allow for
better risk quantification methods where the quantified scores most correlated
with the benchmarks. These methods can provide risk-based analytical support to
evaluate alert overrides of four high-risk medications, propofol, morphine,
insulin, and heparin in the settings of adult intensive care unit (AICU) and
adult medical/surgical care unit (AMSU). We believe that healthcare systems can
use these analytical methods to efficiently identify the riskiest
medication-care unit combinations (e.g. propofol in AICU), and reduce
medication error/harm associated with infusions to enhance patient safety.</p>

<p> </p>

  1. 10.25394/pgs.7430663.v1
Identiferoai:union.ndltd.org:purdue.edu/oai:figshare.com:article/7430663
Date16 January 2020
CreatorsWan-Ting Su (5930303)
Source SetsPurdue University
Detected LanguageEnglish
TypeText, Thesis
RightsCC BY 4.0
Relationhttps://figshare.com/articles/ANALYTICAL_METHODS_TO_QUANTIFY_RISK_OF_HARM_FOR_ALERT-OVERRIDDEN_HIGH-RISK_INTRAVENOUS_MEDICATION_INFUSIONS/7430663

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