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Journal of caring sciences. 9(1):1-8. doi: 10.34172/jcs.2020.001

Review Article

The Magnitude of Medication Administration Errors among Nurses in Ethiopia: a Systematic Review and Meta-analysis

Berhanu Boru Bifftu 1, *ORCID logo, Bezenaw Yimer Mekonnen 1ORCID logo
1Department of Community Health Nursing, School of Nursing, University of Gondar College of Medicine and Health Science, Gondar, Ethiopia
*Corresponding Author: MSc in Integrated Clinical and Community Mental Health, Email: berhanuboru@gmail.com

Abstract

Introduction: Nurses are the final safety check in the process of medication administration process to prevent errors that adversely affect life; yet death of comprehensive evidences in Ethiopia. The present study aimed to assess the pooled magnitude of MAEs (Medication Administration Errors) in Ethiopia.

Methods: Systematic literature search in the databases of Pub-Med, Cochrane, and Google Scholar for gray literature were performed until December 3, 2018. The quality of study was assessed using criteria adopted from similar studies. Heterogeneity test and evidence of publication bias were assessed. Moreover, sensitivity analysis was also performed. Pooled prevalence of MAE was calculated using the random effects model.

Results: A total of 2142 medication administrations were from observational and 681from self-reported studies were included in this systematic review and meta-analysis. The most prevalent and frequently reported type of MAEs was documentation error (52% to 87.5%) and time error (25.5% to 58.5%) respectively. Overall, the pooled magnitude of MAE was found to be 39.3% (95% CI, 29.1%-49.5%).It has no evidence of significant heterogeneity (I2 = 0%, P = 0.57) and publication bias Egger’s test (P = 0.40).

Conclusion: Overall, more than one in four observed/perceived medication administrations had errors. Documentation error is the most prevalent type of error. Nurses are suggested to strengthen their focus on the rights of medication administration guide particularly, documentation of their activities need special attention.

Keywords: Error, Ethiopia, Nurses, Medication Administration

Copyright

© 2020 The Author(s).
This work is published by Journal of Caring Sciences as an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/). Non-commercial uses of the work are permitted, provided the original work is properly cited.


Introduction

Patient safety incidents (PSIs) is defined as ‘any unintended or unexpected incident, which could have or did lead to harm for one or more patients receiving health care.1 Medication errors are any PSIs error during the process of prescribing, preparing, dispensing, administering, monitoring or providing advice on medicines.2-4 Error is defined as failure to execute action as intended. Medication error is any preventable event that harm user while it is in the control of the health care professionals or consumers.5 Such events may be related to professionals, health care products, procedures, and systems including: prescribing, order communication, product labeling, packaging, and nomenclature, compounding, dispensing, distribution, administration, education, monitoring, and use.5 Though medication errors can occur in any phase of the medication use process, medication administration error (MAEs) is one of the most common,6-10 expensive, un reversed and adversely affect the life of user.

MAE is an error during medication administration process such as preparation, administration, and documentation.11-13

Globally, different interventions are implemented including both process changes and use of technologies, yet MAEs remain a serious safety issue. For example, in USA 67%,14,15 in India 68.5%, in South-East Asia15-88%16 and in Ethiopia it reached up to 89.9%.17-20

In nursing, the medication administration process is a daily task account for around 40% of their working time11,21 and nurses are the final safety check.22 Due to this and professional, legal and ethical responsibility; nurses have a central role in the cause, identification and correction of errors.13,23-25 For the safety of medication administration; scientists, and expertise in the field developed standard or rights.20,22,26,27 Nurses can decrease MAEs with the application of these rights; although, a number of factors such as: type of medications, policies and procedures417-19,28,29 age of participant, work experience and working time/shift13,17-19,29 associated with MAEs. The impact of MAEs is huge on the life of patient: morbidity, mortality and length of hospital stay.4,8,29-31 MAEs can also lead nurses to develop error associated moral and ethical issues that reduce their quality of health.32 These adverse effect and its high prevalence is evidenced as studies from Western revealed; however, this is difficult to have a general concept in developing countries33,34 like Ethiopia. This is not because of a low incidence of MAEs rather a result of (i) inefficient documentation or reporting of errors, (ii) insufficient research with inconsistent report17-20 and (iii) lack of comprehensive systematic review and meta-analysis. The present study, address these reasons and showed the current available evidences for policy and decision maker and other researchers; therefore, this study aimed to assess the pooled magnitude of MAE among nurses in Ethiopia.


Materials and methods

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA)35 guideline.

We searched databases including: Pub-Med, Cochrane and Google Scholar. PubMed electronic database was searched until December, 3, 2018 using the search terms: ((medication error [MeSH Terms]) OR (medication error) OR (medication mistake [MeSH Terms]) OR (medication mistake) OR (drug error [MeSH Terms]) OR (drug error) OR (drug mistake [MeSH Terms]) OR (drug mistake) OR (adverse drug event [MeSH Terms]) OR (adverse drug event ) OR (near miss [MeSH Terms]) OR (near miss) OR (administration error [MeSH Terms]) OR (administration error) OR (medication administration error [MeSH Terms]) OR (medication administration error) OR (drug administration mistake [MeSH Terms]) OR (drug administration mistake) OR (drug administration [MeSH Terms]) OR (drug administration) OR (preparation error [MeSH Terms]) OR (preparation error) OR (omission error [MeSH Terms]) OR (omission error) OR (patient error [MeSH Terms]) OR (patient error) OR (dose error [MeSH Terms]) OR (dose error) OR (time error [MeSH Terms]) OR (time error) OR (route error [MeSH Terms]) OR (route error) OR (documentation error [MeSH Terms]) OR (documentation error)) AND ((reasons [MeSH Terms]) OR (reasons) OR (associated factors [MeSH Terms]) OR (associated factors) OR determinants factors[MeSH Terms]) OR (determinants factors)) AND nurses AND Ethiopia. There was no restriction on year of publication. The reference lists of included studies were manually searched. Likewise, Cochrane review database was searched using similar search terms tailored to it. Google Scholar was also searched for gray literature and published paper in unindexed journals. For the required information not clearly written, authors were contacted via email. All the included studies were written in English.

For the purpose of this study, MAEs were defined when there is one or combination of any MAEs (omission, patient, dose, drug/medication, time, route, documentation, unauthorized, rate, not wear/change glove, not wash/rub-hand before the procedure and administration techniques) or deviation from the prescriber’s medication order as written on the patient’s chart, manufacturers’ preparation/administration instructions, or relevant institutional policies during the medication administration process. Omitted drug error: is failure to administer a prescribed medication, patient error: when a medication of one patient is wrongly given to another patient, dose error: when prescribed quantity is not administered, medication error: when another medication is administered to the patient other than the prescribed, time error: when there is a difference of greater or less than 30 min between the ordered time and administered time, unauthorized drug error: medication administered was not authorized by the prescriber, technique error: the nurse performs less than 50% among the procedure put at the technique competency checklist for medication administration, route error: when medication is administrated in different route other than the ordered actual route, documentation error:

When medication that is administered to the patient is not documented in medication administration record sheet.17-20,36,37

This review targets all nurses in Ethiopia. Studies, in which participants were drawn from overall health care professionals, were excluded; unless the studies were separately documented for nurses.

This review included studies that investigated the prevalence of MAEs irrespective of the intent, data collection tools and/or definition. For those studies that reported MAEs using both data collection methods i.e.

Observational and self-administered questionnaire, we included the observational part because of its reliability as compared to self-administered. Studies that reported about adverse drug events (unpreventable errors) and studies that relayed on specific drug therapy (e.g. drug dosage adjustment), type/number of drug (e. g. single drugs), and drug classes (e.g. co-trimoxazole, Antiretroviral), disease condition (e.g. human immunodeficiency virus/acquired immunodeficiency syndrome, diabetes mellitus) were excluded.

Observational studies (cross-sectional and cohort/longitudinal) were included in this systematic review and meta-analysis. Studies that focused on review, case reports, and conference abstracts that did not provide enough information were excluded.

This review systematic review and meta-analysis included studies that carried out in Ethiopia from 2010 to 2018. Two review authors’ were independently assessed the quality of included studies using the criteria adopted from previous similar studies.16,38,39 This tool included thirteen items such as: 1) objectives of the study, 2) definition of what constitutes MAEs, 3) error categories specified, 4) definition of each error categories, 5) clearly defined denominator, 6) description of data collection method, 7) description of setting, 8) sampling and calculation of sample size, 9) description of reliability measures, 10) measures to ensure results as valid, 11) description of the limitations of study, 12) description of any assumptions made and 13) description of Ethical Committee Approval.

A score of “1” was given if the study met the criteria and “0” if not met. To determine the quality of each studies, the overall sum of each item score was considered and defined as “good” if the overall score ≥10, “average” for score ranged from 7-9 and “poor” for score<7. This quality appraisal score was assessed by two investigators (BBB and BYM) and disagreements were solved by discussion.

A standardized and pre-piloted checklist was used to extract the required information. Data were extracted on study characteristics and outcomes by two independent reviewers (BBB and BYM) and stored in a Microsoft Excel

Spread Sheet. The extracted data include details of: author’s name, year of publication, study area, study design (retrospective or prospective), data collection method (observational, chart review and self-reported), assessment tool, definition of MAEs, time frame, sample size and outcomes (number/prevalence of overall/each MAE’s type).

The extracted data were entered into a Microsoft Excel Database and then imported into STATA 14 that we installed packages for Meta-analyses online. In this study, MAEs were defined as the number of errors relative to the total opportunity for error. The total opportunity for error is the sum of the doses given plus the number of doses missed (omission errors) that is the percentage rate of MAEs was determined by dividing the number of actual MAEs that occurred by the total number of MAEs multiplied by 100. If the authors did not specify the denominator used, the total opportunity for error but evaluated the rate of omission errors; then the denominator was considered to be the total opportunity for error. The included studies used different types of MAEs, therefore, to summarize each different types of MAEs, we used the reported incidence of MAEs using text and table. For the analysis of overall pooled magnitude, meta-analyses was performed. The estimated pooled prevalence and weighted mean differences of MAE was calculated using random-effects model at 95% confidence interval.40 Test for Heterogeneity between the studies was performed using Cochran’s Q statistic and the I2 statistics.41 I2 values greater than 50% were considered as indicative of substantial heterogeneity. Evidence of publication bias was assessed using visual inspection of the symmetry in funnel plot42 and egger test.43 Sensitivity analysis was also conducted to examine influential study.44


Results

The literature search resulted in 102 recorded papers. Of this record, 41 studies were excluded just by reading their titles. Of the remaining 61 studies, 29 were excluded on the bases of the outcome assessment. Moreover, 14 studies were excluded after reading the abstract because of unclearly reported outcome variable. Finally, 11studies were excluded based on the eligibility criteria and the remaining 7 studies were included in the systematic review and meta-analysis ().

A total of seven studies [(five observational, including a total of 2142 medication administration interventions) and (two self-reported, including 681 participants)] were included in this systematic review and meta-analysis.

These studies were carried out in the year between 2010 and 2018. All studies were institution based cross-sectional study.

The included studies were carried out in Amhara (n=3), Oromia (n=3) and one study was in Addis Ababa. Majority of the studies (n=5) used pediatrics and adult patient while the remaining (n=2) studies from pediatrics and Intensive Care Unit (ICU) patients. For the assessment of MAEs, direct observation was the most ommonly used method for detecting MAEs (n=6).17-20,36,37

jcs-9-1-g001
Figure 1. Flowchart of the study

Two studies used self-administered questionnaire24,45 and other two studies used the combination of both methods (observational and self-administered questionnaire) (Table 1).20,37

Type and magnitude of MAEs

Regarding the types of MAEs, though the proportion of MAEs is varied for each type of error based on the number of rights used as a reference26,27 definitions46 and phases of medication administration process;11-13 in this study, around thirteen different types of MAEs were identified such as: wrong route, wrong time, wrong patient, wrong dose, wrong drug, error of omission, wrong rate, documentation errors, duration error, technical error, unauthorized and without hand washing/change glove.17-20,24,36,37 In each included study, five18 up to eight37 different types of MAEs were identified; though, one study reported only the overall result.45 The most frequently reported type of MAEs were wrong time and wrong dose errors (n=6.7).17-20,24,37 The next most common type of administration error was wrong route (n=5.7).17,19,20,24,47 The magnitude of MAEs was ranged from 0.9%47 for wrong duration to 87.5%17 for documentation error. Documentation error is the most prevalent type of MAEs as revealed by three studies 87.5%,1785.4%20 and 71.6%24 For each type of MAEs, the magnitude ranged from 25.5%18 to 58.5%17 for wrong time error, 4.4%47 to 68.4%20 for wrong dose errors, 8.2%17 to 40%20 for wrong route error, 15.1%37 to 63.5%20for wrong patient error, 8.3%18 to 63.5%24 for wrong drug/medication error and 19.3%37 to 47.3%47 for omissions error (Table 2).

Quality assessment of the included studies: The quality of the included studies varied between 4 and 12. Of which, two studies have good quality, four studies have average and one study has poor quality (Table 3).

Table 1. Characteristics of the included studies
Author
Year
Study areaWorking unitStudy DesignMethods of data collectionTime frameAssessment toolDefinition of MAEs (Yes/No)Sample SizeCases
Feleke
et al., 2010
OromiaPediatrics wardProspective observationalDirect observationalFebruary 18 to March 2,2009Observational checklistYes218196
Agalu
et al., 2012
OromiaICU, Specialized
teaching hospital
Prospective
Cross sectional
Direct observationalFebruary 7 to March 24, 2011.Observational checklistYes1200622
Feleke
et al., 2015
AmharaInpatient departments of Pediatric and Adult unitsProspective, observation-based, cross-sectional studyQuestionnaire-based
interviews, observations
March 24–April 7, 2014.Questionnaire & observational checklistYes360356
Alemu
et al., 2017
OromiaMedical,
Surgical ,
Pediatrics,
Oby-gyne,
OPD,
OR£ and
Others
Prospective
Cross sectional
Self-administered
and observational
checklist
March1–30, 2014Questionnaire and observational checklistYes139138
Wondmieneh et al., 2018Addis AbabaMedical,
Surgical ,
Pediatrics,
Oby-gyne,
Emergency
OPD,
ICU,
Oncology
Prospective
Cross sectional
ObservationalFebruary to March 2018.Questionnaire and observational checklistYes225216
Jember
et al., 2018
AmharaInternal medicine,
Surgical ward, Emergency room,
Psychiatry,
ICU, Pediatric ward
Quantitative cross sectional Self-administered questionnaireMarch 6 to May10, 2015QuestionnaireSelf developed397198
Bifftu
et al., 2018
AmharaInpatient departments of Pediatric and Adult units Quantitative cross sectionalSelf-administered questionnaireMay, 1 to 30, 2015QuestionnaireSelf-developed282203

Out Patient Department,£Operation Room

Table 2. Type and magnitude of medication administration errors in percent
Type of MAEsAuthors, year and percentage of MAEs
Fekadu
et al., 2010
Agalu
et al., 2012
Feleke
et al., 2015
Alemu
et al., 2017
Wondmiene et al., 2018Jember
et al., 2018
Bifftu
et al., 2018
Wrong route-9.18.24014.2-39
Wrong time25.230.353.658.534.7-52.1
Wrong patient---3015.1-63.5
Wrong dose23.44.423.133.823.1-68.4
Wrong drug--8.333.116.4-63.5
Omission error 19.347.3----28
Wrong rate-1.4-----
Wear/change glove----41.4--
Not Wash/rub-hand----76--
Documentation --87.585.452-71.6
Unauthorized 2.82.71.1----
Administration techniques error18.8-73.1----
Wrong duration-0.9-----

Table 3. Quality of included studies in the analysis of MAEs
Criteria for quality assessmentAuthors, year
Fekadu
et al., 2010
Agalu
et al., 2012
Feleke
et al., 2015
Alemu
et al., 2017
Wondmieneh et al., 2018Jember
et al., 2018
Bifftu
et al., 2018
Aims/objectives clearly statedYesYesYesYesYesNoYes
Definition of MAEsYesYesYesYesYesNoYes
Error categories specifiedYesNoYesNoYesNoYes
Error categories definedYesYesYesYesYesNoYes
Clearly defined denominatorYesYesYesYesYesNoYes
Data collection method described clearlyYesYesYesYesYesYesYes
Setting in which study conducted describedYesYesYesYesYesYesYes
Sampling and calculation of sample size describedYesYesYesYesYesYesYes
Reliability measuresNoNoYesYesNoNoNo
Measures in place to ensure that results are validNoNoYesYesNoNoNo
Limitations of study listedYesYesYesYesYesYesYes
Mention of any assumptions madeNoN oNoNoNoNoNo
Ethical committee approvedNoYesYesYesYesNoYes
Total score99121110410

Pooled magnitude of MAEs

The overall pooled magnitude of MAE was found to be 39.3% (95% CI, 29.1%-49.5%) using random effect model (I2 = 0%, P = 0.576) ().

jcs-9-1-g002
Figure 2. Forest plot presenting the pooled prevalence of MAE using random effect models with 95% CI

It has no evidence of significant heterogeneity test result (I2 = 0%, P =0.576) and publication bias from the visual inspection of the funnel plot and the Egger’s test (P =0.406).


Discussion

To our knowledge, this is the first systematic review and meta-analysis about the magnitude and nature of MAEs among nurses in Ethiopia. Overall the pooled magnitude of MAE was found to be 39.3% (95% CI, 29.1%-49.5%).

This result is consistent with study carried out in Iran [44.5% (27%-50.6%)].48 This result is higher than the previous systematic review and meta-analysis carried out in developed countries [19.6%],49 South East Asia [51.6%],16 Middle East [44.7%]38 and lower than the review in East Africa [56.4%%)].39 The difference might be due to variation in definitions and types/number of MAEs studied.46 For example, the cut-off point for time error, is ±30 minutes for some of the studies and ±60 minutes for the other to define/consider as error.49 This affects the overall magnitude of MAE. This is supported by a systematic literature review of studies that confirmed the variation in prevalence of MAEs because of the inconsistency definition of MAEs.46,50 The other possible reasons for the difference may be due to variation in the study settings,19,47,50 the assessment method (observational, self-reported and patient chart review) also contributed for the variation. This is supported by previous study in Ethiopia that revealed the prevalence of MAE was 71% for self-reported method as compared to 97% for observational method.20 Study from Korea also supports this.51 This may suggest the need of both methods to understand the difference between perceived and experienced prevalence of MAE.

Regarding the types of MAEs; though the proportion of MAEs for each type of errors is varied based on the standard or right used as a reference,26,27 definitions46 and phases of medication administration process,11-13 in this study around thirteen different types of MAEs were identified such as: wrong route, wrong time, wrong patient, wrong dose, wrong drug, omitted error, wrong rate, documentation errors, duration error, technical error, unauthorized, and without hand washing/change glove.17-20,24,36,37 Of these, the most frequently reported MAEs were wrong time and wrong dose17-20,24,37 and the third commonly reported MAE was wrong route.17,19,20,24,47 The magnitude of reported MAEs was ranged from 0.9%47 for wrong duration to 87.5%17 for documentation error.17 For each MAEs, the magnitude ranged from 25.5%18 to 58.5%17 for wrong time error, 4.4%47 to 68.4%20 for wrong dose errors, 8.2%17 to 40%20 for wrong route error, 15.1%37 to 63.5%20 for wrong patient error, 8.3%18 to 63.5%24 for wrong drug/medication error and 19.3%37 to 47.3%47 for omissions error. These result is supported with studies carried out in US where doses was the most common type of error reported.21 A systematic review and meta-analysis from Southeast Asia also showed time error, omission error and wrong dose were the most frequent reported errors.16 Regarding the magnitude of the errors, documentation error was the most prevalent type of MAE (87.5%). This showed the value nurses’ had for documentation. Documentation is a written evidence of interactions between and among health professionals, clients, their families, and health care organizations.52

Nursing documents is a source of communication that reveals the treatment and quality of care given. This makes it essential for nurses to bier in mind the saying ‘if it was not documented, it was not done’.53 That is why in Ethiopia, the Federal Ministry of Health Operational Standard for Nursing Care outlines that every nursing care provided must be clearly and correctly documented.54

The strength of this meta-analysis is the inclusions of all studies without restriction to study time and published studies in reputable peer reviewed journal to include all the available studies. However, this study had some important limitations. Lack of similar studies in Ethiopia limits the discussions. Although we used Pub-Med, Cochrane, Google Scholar and reference lists, there may be the possibility of having some overlooked.

Despite these, this systematic review and meta-analysis revealed the recently available evidence that may help to narrow the scant evidence of research in Ethiopia.


Conclusion

Overall, the magnitude of MAE was high in Ethiopia. Wrong route, wrong time, wrong patient, wrong dose, Wrong drug, omission error, wrong rate, and documentation errors were the reported type of MAEs. Of these, the most prevalent and most frequently reported type of MAEs was documentation error and wrong time error respectively. Authors suggested nurses to give more attentions on the rights of medication administration particularly, to strengthen their documentation behaviors.


Acknowledgments

Authors’ gratitude goes to University of Gondar for office arrangement and motivational support to conduct this protocol.


Ethical issues

None to be declared.


Conflict of interest

The authors declare no conflict of interest in this study.


Research Highlights

What is the current knowledge?

Nurses are the final safety check during the medication administration process with inconsistent reported prevalence MAEs and dearth of comprehensive evidences.

What is new here?

The present study showed high overall pooled prevalence of MARs. Moreover, it identifies the type of error frequently observed with its respective magnitude that may help as an indication for area of intervention during the planning of preventive strategies. In addition, the present study suggested areas that need to be strengthen or need special attention during medication administration process.


Authors’ contributions

BBB designed the review protocol in collaboration with BYM. BBB developed the search strategy and drafted the protocol. BBB and BYM were searches and conduct data selection and extraction. Both authors involved in data analysis and interpretation of results. Both authors have read and approved the final manuscript.


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Submitted: 13 Mar 2019
Accepted: 28 Jul 2019
First published online: 01 Mar 2020
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