Study design, area, and period

A cross-sectional study was conducted from June 1, 2022 to August 30, 2022G.C in the emergency ward at the UoGCSH, located in Gondar town, northwest Ethiopia. The calculated flying distance from Addis Ababa, the capital city of Ethiopia, to Gondar is equal to 262 miles, which is equal to 421 km, and the driving distance between Addis Ababa and Gondar is 727.22 km [20]. The University of Gondar Comprehensive Specialized Hospital is a tertiary care facility with different wards, including emergency, ambulatory, pediatrics, oncology, gynecology, and surgery wards. According to the UoGCSH’s 2021/2022 annual report, around 280,000 patients visit the hospital and 12,000 are admitted to the emergency ward.

Population, inclusion, and exclusion criteria

Patients aged ≥ 18 years admitted to the emergency ward at UoGCSH were the source population. However, those adult patients admitted to the emergency ward at UoGCSH during the study were the study population. Patients who had at least one medication order and stayed for at least 24 h on the emergency ward were included. Patients were excluded if they were too ill to answer interview questions and/or did not have a caregiver.

Sample size determination and sampling procedure

The sample size was determined using a single population proportion formula with the assumption of a 95% confidence level, 5% margin of error, and 50% proportion. The prevalence of ME at the emergency ward was not known in Ethiopia. During the study, 50% population proportion was used:

n = (1.96)2(0.5 × 0.5)/ (0.05)2 = 384.2

By adding a 10% contingency (384.2*10% = 38) to the calculated sample size, 422 patients were estimated for the study. Where n = sample size, p = sample proportion/population proportion, z = confidence level/Z-score and \(^\)= margin of error.

A systematic random sampling technique was used to collect data from patients who fulfilled the inclusion criteria. It was estimated that 3000 patients would be admitted to the ward during the 3-month data collection period. The formula “k = N/n” was used to obtain the “k” value. As a result, k was set to "7," and the first patient admitted to the ward was chosen by lottery after rolling a piece of paper one through seven and randomly selecting one of the rolled papers. After the first patient was selected, every seventh patient admitted to the ward fulfilling the inclusion criteria was taken as a sample.

Variables of the study

The dependent variable was medication error. The independent variables include gender, patients with uncorrected/uncorrectable visual impairment, patients with uncorrected/uncorrectable renal impairment, patients diagnosed with pneumonia, presence of comorbidity, Charlson comorbidity index, duration of patient stay in the emergency ward after admission, and number of medications the patient is using after admission.

Operational definitions

Comorbidities: according to the center for disease control and prevention (CDC), comorbidities are defined as when a person has more than one disease or condition at the same time [21].

Patient harm: is any unintended and unnecessary harm resulting from, or contributed to by, health care [22].

Medication errors: are defined as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the healthcare professional, patient, or consumer.”[23].

Near miss or “close call”: a prevented medicine-related patient safety incident that could have led to patient harm.

Adverse drug event (ADE): is an event that occurs when a medicine is administered to a person in order to improve their health but instead causes harm or exposes the person to potential harm. The occurrence of an ADE does not necessarily indicate an error or poor quality of care.

Preventable adverse drug events: are adverse drug events that result from a medication error that reaches the patient and causes any degree of harm.

Potential adverse drug events: are adverse drug events resulting from medication errors that do not cause any harm, either because they are intercepted before reaching the patient or because of luck [24].

The NCC MERP Index: the severity of MEs and ADEs can be assessed using the detailed scale published by the National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP), which is categorized from A to I. Categories A through D of the NCC MERP Index are relevant to MEs; and Categories E through I of the NCC MERP Index are relevant to ADEs:

Category A: Circumstances or events that have the capacity to cause error.

Category B: An error occurred but the error did not reach the patient.

Category C: An error occurred that reached the patient but did not harm the patient.

Category D: An error occurred that reached the patient and required monitoring or intervention to confirm that it resulted in no harm to the patient and/or required intervention to preclude harm.

Category E: An error occurred that resulted in the need for treatment or intervention and caused temporary patient harm.

Category F: An error occurred that resulted in initial or prolonged hospitalization and caused temporary harm [25].

Prescription error: “a failure in the prescription writing process that results in wrong instructions about one or more of the normal features of a prescription. The ‘normal features’ include the identity of the recipient, the identity of the drug, the formulation, dose, route, timing, frequency, and duration of administration”[26].

Medication transcription error: “any discrepancy between the physician’s medication order and the medication order transcribed onto any document related to the patient concerned, such as the medical record, medication chart, medication request sheet, discharge medication chart, and/or any other similar document” [27]. In this study, when medication is written on the order sheet of the medical chart but not written on prescription paper for the patient or caregiver to buy or bring the medication, it is considered a transcription error.

Administration error: a failure in one of the nine “rights” of medication administration (right patient, medication, time, dose, route, documentation, action, form, and response) [28].

Monitoring error: failure to review a prescribed regimen for appropriateness and detection of problems or failure to use appropriate clinical or laboratory data for adequate assessment of the patient’s response to prescribed therapy [29].

“Omission of transcription”: when a medication written on an order sheet is not transcribed to a prescription paper (to allow the patient to bring and take the medication).

Dose omitted: a prescribed medication or dose that is already in the hands of the patient, caregiver, or nurse but is not given.

Actual severe harm: permanent harm experienced by the patient due to medication error.

Actual moderate harm: reversible harm experienced by the patient due to medication errors that require active treatment.

Actual mild harm: reversible harm experienced by the patient due to medication errors that require monitoring.

Potentially fatal harm: no harm has occurred, but the medication error could have an adverse outcome that could be fatal.

Potentially severe harm: no harm has occurred, but the medication error could cause permanent harm.

Potentially moderate harm: no harm has occurred, but active treatment is required to prevent harm that could be caused by a medication error.

Potentially mild harm: no harm has occurred, but monitoring is required to prevent harm that will be caused by a medication error.

“Start a drug”: is an intervention given by clinical pharmacists when a medication at hand is not started to be administered (by a nurse or by the patient himself/herself) or when a drug is written on the order sheet of the medical chart but not transcribed to prescription paper for the patient to bring and take the medication.

“Continue a drug”: is an intervention given by clinical pharmacists when the next dose to be administered is interrupted (missed) after administration has been started at a certain time.

Fully accepted: when a person accepts an intervention given by a clinical pharmacist without any doubt and acts immediately.

Partially accepted: when a person accepts an intervention given by a clinical pharmacist with some level of doubt and agrees to act based on that later point in time and/or partially act upon [30].

Not accepted: when a person does not accept an intervention provided by a clinical pharmacist.

Data collection instrument, procedure, and quality control

To collect the data, three clinical pharmacists were trained on the data collection tool. At the emergency ward, each patient was followed from admission until discharge and assessed on their medication use process. Medication errors were identified in accordance with the “Standard Treatment Guidelines for General Hospitals,” third edition, published in 2014, Ethiopia, and a pharmacotherapy book were also employed [31, 32]. In addition, different variables regarding medication errors were identified using publications by WHO, “Reporting and Learning Systems of Medication Errors: The Role of Pharmacovigilance Centers” and “Medication Errors: Technical Series on Safer Primary Care [33, 34].

Part of the questionnaire that needed the response of patients or caregivers (the socio-demographic data) was translated into the local language (Amharic), and then they were interviewed. The “Amharic” version of the questions was back translated into the English version to confirm translation consistency. Clinical information was gathered from patient medical records (procedure notes, physician orders, prescription papers, medication administration records, physician progress notes, pertinent laboratory reports, and nursing progress notes). Data were also collected through direct observation of patients and health care professionals during the medication use process. The Charlson comorbidity index and estimated 10-year survival were assessed [35]. The eGFR of patients was calculated using the Cockcroft–Gault Equations [36]. For patients with renal impairment, “Drug Prescribing in Renal Failure” was used as a guide to determine the appropriateness of the drug dose prescribed [37].

Questioners used in the Swiss Sentinel Surveillance Network study were used to gather socio-demographic data, clinical characteristics of patients and the presence of ME in patients [38]. A checklist prepared for the California Health Care Foundation for tracking MEs in hospitals was used to collect medication order information and the categorization or staging of medication errors [39], and a model form for reporting medication errors, designed by WHO in the “Reporting and Learning System for Medication Errors: The Role of Pharmacovigilance Centers” guideline, was used to obtain types of ME, patient outcomes, and possible causes of ME [33]. The severity of ME was reported according to the detailed scale published by the National Coordinating Council for Medication Error Reduction and Prevention (NCC MERP) [25]. Data collectors intervened when medication errors occurred during data collection. Interventions given by clinical pharmacists were obtained from a study done in Italy [30]. In addition, the tool employed to measure the acceptance rate of the interventions were obtained from a study done in Switzerland [40].

After the questionnaire was pre-tested on 5% (21 individuals) of the study population, some rearrangements were made to the instrument to make it more favorable for data collection. The consistency of the responses was evaluated after data was obtained from the pretested questionnaire. Three clinical pharmacists were assigned to collect data. They were trained for 3 days on the study objectives and how to use the tool or questionnaire properly. Data collectors were supervised while collecting data. The data was checked for its completeness and consistency on a daily basis.

Analysis of data

After data were entered, cleared, and checked with EpiData Manager 4.6.0.0, it was exported to Statistical Package for Social Sciences (SPSS) version 24 for analysis. The normality of the different variables included in the analysis was checked using histograms and the Shapiro–Wilk test. Descriptive statistics were used to characterize dependent and independent variables. The frequency and percentage of socio-demographic characteristics, clinical characteristics, medication-related characteristics, different variables that measure medication errors, the outcome of MEs, possible causes of MEs, medication-related interventions, and the rate of acceptance of the given interventions were performed. Categorical variables were described as frequency and percentages, and continuous variables as the median and interquartile range (IQR). Tables and figures were used to summarize and describe the results.

The “Enter method” is used for entering variables into the binary logistic regression model. All variables having a p value < 0.2 in bivariable binary logistic regression analysis were entered into multivariable binary logistic regression to test the strength of association between dependent and independent variables. Model fitness was checked using the Hosmer–Lemeshow goodness-of-fit test. The assumption of independence (adequacy of cells) was checked by chi-square statistics and the value obtained was (6.625). Only variables not violating the assumption were analyzed later by multivariable binary logistic regression. Prior to analysis, variables were tested for multicollinearity by the variance inflation factor (VIF). The included variables had VIF values in the range of 1–1.8 [41]. The presence of outliers was also checked using the inter-quartile range method (Q1–1.5*IQR and Q3 + 1.5*IQR) [42]. In the present study, no outliers were identified. The strength of the association was measured using an odds ratio (OR). A p value of < 0.05 was considered statistically significant with a 95% level of confidence.