Errors in the medication process: frequency, type, and potential
ABSTRACT To investigate the frequency, type, and consequences of medication errors in more stages of the medication process, including discharge summaries.
A cross-sectional study using three methods to detect errors in the medication process: direct observations, unannounced control visits, and chart reviews. With the exception of errors in discharge summaries all potential medication error consequences were evaluated by physicians and pharmacists.
A randomly selected medical and surgical department at Aarhus University Hospital, Denmark.
Eligible in-hospital patients aged 18 or over (n = 64), physicians prescribing drugs and nurses dispensing and administering drugs.
Frequency, type, and potential clinical consequences of all detected errors compared with the total number of opportunities for error.
We detected a total of 1065 errors in 2467 opportunities for errors (43%). In worst case scenario 20-30% of all evaluated medication errors were assessed as potential adverse drug events. In each stage the frequency of medication errors were-ordering: 167/433 (39%), transcription: 310/558 (56%), dispensing: 22/538 (4%), administration: 166/412 (41%), and finally discharge summaries: 401/526 (76%). The most common types of error throughout the medication process were: lack of drug form, unordered drug, omission of drug/dose, and lack of identity control.
There is a need for quality improvement, as almost 50% of all errors in doses and prescriptions in the medication process were caused by missing actions. We assume that the number of errors could be reduced by simple changes of existing procedures or by implementing automated technologies in the medication process.
SourceAvailable from: Lauren C. Bresee[Show abstract] [Hide abstract]
ABSTRACT: Medication administration omissions (MAO) are usually considered medication errors but not all MAO are clinically relevant. We determined the frequency of clinically relevant MAO of antimicrobial drugs in adult hospitals in Calgary, Alberta, Canada based on electronic medication administration record (eMAR). We examined 2011 data from eMAR records on medical wards and developed a reproducible assessment scheme to categorize and determine clinical relevance of MAO. We applied this scheme to records from 2012 in a retrospective cohort study to quantify clinically relevant MAO. Significant predictors of clinically relevant MAO were identified. A total of 294,718 dose records were assessed of which 10,282 (3.49%) were for doses not administered. Among these 4903 (1.66% of total); 47.68% of MAO were considered clinically relevant. Significant positive predictors of clinically relevant MAO included inhaled (OR 4.90, 95% CI 3.54-6.94) and liquid oral (OR 1.32, 95% CI 1.18-1.47) route of medication compared to solid oral and irregular dose schedules. Evening nursing shift compared to night shift (OR 0.77 95% CI 0.70-0.85) and parenteral (OR 0.50, 95% CI 0.46-0.54) were negative predictors, The commonest reasons for relevant MAO were patient preference, unspecified reason, administration access issues, drug not available or patient condition. Assessment of MAO by review of computer records provides a greater scope and sample size than directly observed medication administration assessments without "observer" effect. We found that MAO of antimicrobials in inpatients were uncommon but were seen more frequently with orally administered antimicrobials which may have significance to antimicrobial stewardship initiatives.PLoS ONE 04/2015; 10(4):e0122422. DOI:10.1371/journal.pone.0122422 · 3.53 Impact Factor
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ABSTRACT: The purpose of this study is to present a comprehensive and valid estimate of the problems that arise in the medication process in hospitals. Specifically the study aims to examine medication-related adverse outcomes and contributing factors of hospital patients, to study the associations between adverse outcomes and contributing factors, and to compare differences between the detection methods. This study was conducted in one university hospital in Finland. Three types of data sets were analysed statistically including retrospectively collected medication-related incident reports (n=671) from the year 2010, retrospectively collected randomly selected patients’ records (n=463) from the year 2011 using the Global Trigger Tool (GTT) method, and observations (n=1058) of medication administrations by nurses’ with record reviews (n=122) during April to May 2012. In addition, secondary analysis of medication administration errors (n=453) detected by three methods was conducted. A total of (n=1059) medication errors and (n=311) adverse drug events were detected. Harm to patients was caused in 48% of detected medication errors in GTT data, 18% in incident reports, and 3% in observational data. Most of the detected errors were administration or documenting errors. The most common types of medication errors were wrong dose, omission, and wrong administration technique. There were differences between the detection methods when the information of the medication errors stages, types, and severities were compared. The most important work environmental factors contributing to errors were rush, lack of training, problems in the communication systems, in the electronic records, or in the common policies and procedures. Omission of double-checking, problems in communication and flow of information were the most common among the team factors contributing to errors. Of the employee-related factors performance deficit, stress/high volume workload, miscalculation of dosage or infusion rate, and knowledge deficit were the most common. The most important patient-specific factors were the amount of drugs, length of hospital stay, coronary artery disease, and co-morbidity. The most common drug-related factors contributing to errors were other than p.o administration and specific drugs. This study demonstrated that medication-related adverse outcomes are common and incident reports, GTT, and observation methods produce different information about the problems in the medication process. Understanding the complex reality of the hospital environment and the medication process can be limited by using only one detection method, because each detection methods had its limitations. Thus, combining the methods revealed more diverse information regarding medication-related problems in hospital that can be used to increase safety in the medication process.12/2014; , ISBN: 978-952-61-1636-5