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\begin{document}

\title{Characterising the Type and Impact of Prescribing Errors in a University
Health Board}



\author[1]{Aniket Paranjape}%
\author[1]{Andrew Carson-Stevens}%
\author[2]{K L  James}%
\affil[1]{Cardiff University}%
\affil[2]{Cardiff and Vale University Health Board}%


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  \date{June 14, 2024}


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\begin{abstract}
Medication incidents result in global economic burden and cause
avoidable patient harm. Prescribing errors constitute 18.5\% of all
medication incidents. Aim: Establish incidence, types, potential harm
and medicines involved in prescribing errors in Welsh University
Hospital Health Board. Medication chart review by medical student
undertaken to identify prescribing errors highlighted by pharmacists.
Pilot study conducted to ensure student was adequately trained. Data
collected on wards representing medicine, surgery, mental health and
specialist services. All in-patient prescriptions included. Potential
harm to patients categorised via consensus panel using WHO definitions.
366 prescribing errors identified in 2161 prescriptions (16.9\%). Of 206
patient charts, 148 charts contained [?]1 prescribing errors (71.8\%).
Three most common errors were `No maximum 24-hour dose specified'
(n=59), `Wrong dose of drug' (n=53) and `No indication' (n=37). 110
medications implicated but ten medications constituted 43.2\% of all
errors (n=158). Morphine (n=38), enoxaparin (n=30) and paracetamol
(n=22) were most erroneously prescribed medications. 244(66.7\%) errors
had potential for no patient harm, 56(15.3\%) mild, 47(12.8\%) moderate,
17(4.6\%) severe, and 2(0.5\%) had potential for death. Decision-making
errors (34.5\%, n=130) less common than prescription-writing errors
(65.5\%, n=236) but had greater harm potential; 70.0\%(n=85) of all
errors with harm potential were decision-making errors. Error rate
(16.9\%) comparable to previous research (7.5-14.7\%). `Wrong dose of
drug' was a harmful error which may be ameliorated by electronic
prescribing systems incorporating `clinical decision support'.
Prevalence of `No indication' errors makes strong case for
indication-based prescribing. Future studies should employ this
methodology to collect data post implementation of electronic
prescribing.%
\end{abstract}%



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\verb`Manuscript 2 AP .docx`  available at \url{https://authorea.com/users/735390/articles/711771-characterising-the-type-and-impact-of-prescribing-errors-in-a-university-health-board}

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