Posted: March 23rd, 2023

Evaluation of Perioperative Medication Errors and Adverse Drug Events: Article Review

Nanji, K. C., Patel, A., Shaikh, S., Seger, D. L., & Bates, D. W. (2016). Evaluation of perioperative medication errors and adverse drug events. The Journal of the American Society of Anesthesiologists, 124(1), 25-34.

Research Problem/Purpose

Researchers collect and analyze data to solve a research problem. Therefore, they should reveal the issue they studied. In the reviewed study, “Evaluation of Perioperative Medication Errors and Adverse Drug Events” by Nanji et al. (2016), the problem entails the prevalence of medication errors (MEs) and adverse drug events (ADEs) during operative medical administration during operation. The purpose of the study was to, “assess the rates of perioperative medication errors (MEs) and adverse drug events (ADEs) as percentages of medication administrations, to evaluate their root causes, and to formulate targeted solutions to prevent them” (Nanji et al., 2016, p. 25). The investigators situated their investigation within the context of the current knowledge in healthcare. They explored a common problem in nursing and used previous research to provide a background of their exploration. The findings of the study will solve a relevant problem in nursing. Nurse anesthetists provide medication during an operation. Therefore, the results will offer relevant knowledge about safe administration to prevent medication errors and adverse drug events. Caregivers can use the findings to understand the causes of the problem and develop and implement an effective intervention.

Review of the Literature

The literature review helps researchers to place a study problem in the context of prevailing knowledge. For instance, the researchers should explore what other previous scholars have studied on the topic of perioperative medication errors and adverse drug events and their root causes. The authors did not use any section labeled literature review in the current report. However, they included their synthesis of previous knowledge in their introduction. They reviewed important concepts critical for the study, including medication administration, drug administration errors, and adverse drug events. They explored the concepts using recent data. 17 out of the 25 sources used in the study were written after 2000. The remaining articles were published before 2000 but were relevant to the study because they offered information on historical models and data pertinent to the research. Generally, all the articles used to inform the current analysis were current and appropriate.

Theoretical Framework

The theoretical framework provides the foundation for the study. It includes the model upon which the research is based. The study does not have a theoretical model. However, it has some assumptions on which the authors based their investigation. They applied the idea that preoperative medication administration is complex and poses a higher risk of errors and adverse effects than others. They also indicated the potential to reduce medication errors through systematic measuring and categorizing them to determine root causes. Their assumptions are relevant to the research. Faye Glenn Abdellah’s Twenty-One Nursing Problems Theory would be an appropriate model for the study because it helps caregivers to understand and analyze medical problems to create effective solutions. The concept would have assisted in finding the root cause of medication errors and adverse drug events in the preoperative setting. The theory would help collect relevant data from the context and use the analysis results to create a safe nursing practice.

Variables/Hypotheses/Questions/Assumptions

The report lacks a clear hypothesis or research question. However, the study presents a statement that informs data collection and analysis. The authors hypothesized that reductions in medication errors have occurred in the past due to effective error measurement, categorization, design, and implementation of effective interventions. The scholars identified the dependent and independent variables. The dependent variables were the rates of medication errors and adverse drug events, while the independent variable was preoperative medication administration. They clearly defined the variables under the section definitions. They defined the perioperative medication administration, medication errors, and adverse drug events. From the definitions, the reader can understand their interpretation and how they are operationalized and measured. The dependent variables are concrete and measurable because one can objectively measure the rates of medication errors and adverse drug events.

Methodology

The design of a study is critical because it determines the type of data the researchers collect to answer the study question and solve the identified problem. The current investigation was a quantitative prospective observational study. The authors used a deductive reasoning approach because they moved from a general statement to make conclusions following data collection and analysis. They collected data from a sample of 237 anesthesia care providers, “81 (34.2%) anesthesiologists, 53 (22.4%) certified registered nurse anesthetists (CRNAs), and 103 (43.5%) house staff” (Nanji et al., 2016, p. 26). They collected data from randomly selected operating rooms in a hospital setting. The study used a non-probability sampling method because the authors used all anesthesia care providers in the setting. Hence, to test the independent variable, the researchers observed the process from when the medication was obtained from the anesthesia cart to when it reached the patient. The dependent variables were measured by collecting data to determine the rates of medication errors and adverse drug effects during operations. The researchers did not reveal how they ensured the reliability and validity of their study. They incorporated the necessary ethical considerations, including seeking approval from the Partners Human Research Office and signed consent from participants.

Data Analysis

The researchers collected quantitative data for their study. Therefore, they needed to use a statistical analysis method relevant to the data. They performed all their analyses using SAS(R) version 9.3 (SAS Institute Inc., USA). Their statistical analysis presented their findings as numbers and rates of medical errors and adverse drug events per 100 drug administrations. They used the binomial distribution to perform sample size estimations during the data analysis phase. They used the “Cohen κ statistic” for the classification of incidence, severity, and preventability. They presented the results as numbers and rates as percentages, such as the percentage of medication errors and adverse drug events during operations with medication administrations. From the 277 operations with 3,671 medication administrations that the researchers observed, they revealed 193 that had medication errors and adverse drug events. The results related to the dependent variable since the rates of medication errors (MEs) and adverse drug events during medication administration operations were measured.

Summary/Conclusions, Implications, and Recommendations

The study has various strengths, such as the use of a sufficient sample from a hospital setting to collect data. However, it was limited by the use of observational data only. Besides, the researchers failed to propose effective interventions to address the problem. However, the results of the study are generalizable to other operative settings to implement interventions to prevent medication errors and adverse drug events. The survey can be used in practice to address the issue and improve the quality of care in hospitals. Nurses can use the evidence to determine the causes of medication errors and adverse drug events in their care settings, especially in an effective medication administration.

References

Nanji, K. C., Patel, A., Shaikh, S., Seger, D. L., & Bates, D. W. (2016). Evaluation of perioperative medication errors and adverse drug events. The Journal of the American Society of Anesthesiologists, 124(1), 25-34.