Barriers to Reporting Medication Administration Errors among Nurses in an Accredited Hospital in Saudi Arabia

2016 ◽  
Vol 11 (4) ◽  
pp. 1-13 ◽  
Author(s):  
Ala’a Mohammad ◽  
Ibrahim Aljasser ◽  
Bokkasam Sasidhar
Keyword(s):  
Saudi Arabia ◽  
Medication Administration ◽  
Medication Administration Errors

scholarly journals Analysis of Reported E-prescribing Medication Administration Errors at King Saud Medical City, Riyadh: A Cross-Sectional, Retrospective Study

2020 ◽  
pp. 34-45
Author(s):  
Dalal Salem Al- Dossari ◽  
Mohammed Ibrahim Alnami ◽  
Naseem Akhtar Qureshi
Keyword(s):  
Saudi Arabia ◽  
Retrospective Study ◽  
Medication Errors ◽  
Drug Administration ◽  
Medication Administration ◽  
Care Hospital ◽  
Cross Sectional ◽  
Common Error ◽  
Clinical Pharmacists ◽  
Medication Administration Errors

Background: Drug prescription error is a medication error that most frequently happens in healthcare organizations and adversely affects the healthcare consumers. Most medication errors (MEs) but not all are captured and corrected before reaching the patient by designed system controls. Medication administration errors (MAEs) mostly are made by nurses but frequently reported by clinical pharmacists in hospitals in Saudi Arabia. Objective: This study aimed to analyze exclusively the voluntarily reported drug administration errors in a tertiary care hospital in Riyadh city. Methods: This cross-sectional, retrospective study evaluated consecutively collected medication administration report forms over a period of one year from January 1, 2015 to December 31, 2015. Results: The number of MAEs occurring during stage of drug administration constituted 7.1% (n=971) of total medication errors (n=13677). The maximum number of MEs (n=6838, 50%) and MAEs (n=455, 46.9%) occurred during the 4th quarter of the year 2015. The most common MAE happened to be category C (n=888, 91.5%) which means error occurred, reached the patient but without causing any harm. Concerning MAE types, the most common error included wrong frequency (40%) followed by wrong drug (17%), wrong time of administration (16%) and wrong rate of infusion (10%). Nurses made the most of the errors (92.2%) while the clinical pharmacists reported the most MAEs (75.5%). High alert medications (HAM) errors constituted 32.3% (n=314) of MAEs (n=971) and most common HAM errors included the wrong route of administration of Lanus Insulin (15%) followed by Insulin Aspart (15%), Enoxaparin (13%) and Insulin Protamine-Nvomix (12%). Look-alike and sound-alike (LASA) errors constituted 55.2% of MAEs (971/536) and most common LASA drugs identified were Gentamycin (13%), Insulin Mixtard (11%), NPH Insulin (8%) Intralipid vial (8%) and Insulin regular (6%). Conclusion: This retrospective study provides some important tentative pharmacovigilance insights into MAEs, which are partially comparable with current international trends in drug administration errors. Further studies on MAEs are warranted not only in the Kingdom of Saudi Arabia but also other Gulf countries.

scholarly journals Nursesʼ Willingness to Report Medication Administration Errors in Saudi Arabia

2012 ◽  
Vol 21 (3) ◽  
pp. 119-126 ◽  
Author(s):  
Hayfa H. Almutary ◽  
Peter A. Lewis
Keyword(s):  
Saudi Arabia ◽  
Medication Administration ◽  
Medication Administration Errors ◽  
Willingness To Report

scholarly journals Use of Pediatric Injectable Medicines Guidelines and Associated Medication Administration Errors: A Human Reliability Analysis

2021 ◽  
pp. 106002802199964
Author(s):  
Matthew D. Jones ◽  
Jonathan Clarke ◽  
Calandra Feather ◽  
Bryony Dean Franklin ◽  
Ruchi Sinha ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Medication Administration ◽  
Original Study ◽  
Human Reliability ◽  
Large Magnitude ◽  
Human Reliability Analysis ◽  
Video Recordings ◽  
Medication Administration Errors ◽  
Key Factor ◽  
Clinically Significant

Background: In a recent human reliability analysis (HRA) of simulated pediatric resuscitations, ineffective retrieval of preparation and administration instructions from online injectable medicines guidelines was a key factor contributing to medication administration errors (MAEs). Objective: The aim of the present study was to use a specific HRA to understand where intravenous medicines guidelines are vulnerable to misinterpretation, focusing on deviations from expected practice ( discrepancies) that contributed to large-magnitude and/or clinically significant MAEs. Methods: Video recordings from the original study were reanalyzed to identify discrepancies in the steps required to find and extract information from the NHS Injectable Medicines Guide (IMG) website. These data were combined with MAE data from the same original study. Results: In total, 44 discrepancies during use of the IMG were observed across 180 medication administrations. Of these discrepancies, 21 (48%) were associated with an MAE, 16 of which (36% of 44 discrepancies) made a major contribution to that error. There were more discrepancies (31 in total, 70%) during the steps required to access the correct drug webpage than there were in the steps required to read this information (13 in total, 30%). Discrepancies when using injectable medicines guidelines made a major contribution to 6 (27%) of 22 clinically significant and 4 (15%) of 27 large-magnitude MAEs. Conclusion and Relevance: Discrepancies during the use of an online injectable medicines guideline were often associated with subsequent MAEs, including those with potentially significant consequences. This highlights the need to test the usability of guidelines before clinical use.

The incidence and nature of prescribing and medication administration errors in paediatric inpatients

2010 ◽  
Vol 95 (2) ◽  
pp. 113-118 ◽  
Author(s):  
M. A. Ghaleb ◽  
N. Barber ◽  
B. D. Franklin ◽  
I. C. K. Wong
Keyword(s):  
Medication Administration ◽  
Medication Administration Errors

scholarly journals Prevalence of intravenous medication administration errors: a cross-sectional study

2017 ◽  
Vol Volume 6 ◽  
pp. 47-51 ◽  
Author(s):  
Tezeta Fekadu ◽  
Mebrahtu Teweldemedhin ◽  
Eyerusalem Esrael ◽  
Solomon Weldegebreal Asgedom
Keyword(s):  
Medication Administration ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Medication Administration Errors ◽  
Intravenous Medication

scholarly journals Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study (Preprint)

2020 ◽  
Author(s):  
Yizhao Ni ◽  
Todd Lingren ◽  
Hannah Huth ◽  
Kristen Timmons ◽  
Krisin Melton ◽  
...  
Keyword(s):  
Data Quality ◽  
Error Detection ◽  
Clinical Setting ◽  
Infusion Pump ◽  
Medication Use ◽  
Primary Source ◽  
Evaluation Study ◽  
Medication Administration ◽  
Medication Administration Errors ◽  
Smart Pump

BACKGROUND At present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized. OBJECTIVE This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration. METHODS We evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data, respectively. A novel concordance assessment was also developed to understand the detec-tion power and capabilities of SPR and EHR data. RESULTS Approximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data. CONCLUSIONS We integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting.

Sign in / Sign up

Export Citation Format

Share Document