Premium Essay

Reducing Medication Errord

In:

Submitted By kford
Words 323
Pages 2
Reducing Medication Errors Medication errors are a major problem in the healthcare community, and especially in pediatrics. “Up to 27% of all pediatric medication orders result in a medication error.” Keiffer, Marcum, Harrison, Teske, and Simsic (2014). There is far less room for error with drug administration when working with pediatrics. It should be a primary goal to significantly reduce the cases of medication error in ever facility. I will discuss the importance of reducing medical errors relating to a Pediatric Cardiothoracic Intensive Care Unit. The article titled Reduction of Medication Errors in a Pediatric Cardiothoracic Intensive Care Unit discusses the rate of medication errors in their unit, and the steps that were taken to try to eliminate or reduce the number of medication errors. “A medication error is defined as an error that occurs with the prescribing, dispensing, administering, adherence, or monitoring of a drug regardless of whether it results in patient harm or has the potential to result in patient harm.” Keiffer et al. (2014). The authors note that medication errors occur more often with administration issues as opposed to prescribing, ordering dispensing, or monitoring. The article discusses the health care professionals’ courses of action taken to reduce medication errors for their patients. The medical team implemented interventions and methods including: a double check system, hands free communication, a safety systems checklist, a distraction-free zone, information huddles, and a medication bar coding system. With the methods and steps taken there was also documentation, compliance, limitations, and opportunities for improvement listed. Overall, the medical team was able to significantly lower the rate of medication errors for their unit. They were able to reduce the amount of harm causing medical errors from “0.43 to

Similar Documents

Premium Essay

Knowledge Discovery in Medical Databases Leveraging Data Mining

...Abstract Abstract The goal of this master’s thesis is to identify and evaluate data mining algorithms which are commonly implemented in modern Medical Decision Support Systems (MDSS). They are used in various healthcare units all over the world. These institutions store large amounts of medical data. This data may contain relevant medical information hidden in various patterns buried among the records. Within the research several popular MDSS’s are analysed in order to determine the most common data mining algorithms utilized by them. Three algorithms have been identified: Naïve Bayes, Multilayer Perceptron and C4.5. Prior to the very analyses the algorithms are calibrated. Several testing configurations are tested in order to determine the best setting for the algorithms. Afterwards, an ultimate comparison of the algorithms orders them with respect to their performance. The evaluation is based on a set of performance metrics. The analyses are conducted in WEKA on five UCI medical datasets: breast cancer, hepatitis, heart disease, dermatology disease, diabetes. The analyses have shown that it is very difficult to name a single data mining algorithm to be the most suitable for the medical data. The results gained for the algorithms were very similar. However, the final evaluation of the outcomes allowed singling out the Naïve Bayes to be the best classifier for the given domain. It was followed by the Multilayer Perceptron and the C4.5. Keywords: Naïve Bayes, Multilayer...

Words: 35271 - Pages: 142