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Background: Look-alike, sound-alike (LASA) drug names are a cause of medication errors with resulting patient harm and healthcare costs. This study assessed to which extent the use of the generic drug name, therapeutic class, health problem, and the U.S. Food and Drug Administration (FDA)-approved indications might be used to differentiate LASA drug pairs., Research Design and Methods: We collected information about LASA drug pairs reported by the FDA to have look-alike sound-alike similarities. To assess potential for differentiating LASA drug pairs, we compared the following drug characteristics: generic name, therapeutic class, health problem, and FDA-approved indication., Results: For the 33 FDA reported LASA drug pairs we identified a total of 432 FDA-approved indications. Using the generic name, therapeutic class, health problem and drug indication we were able to differentiate 8 (24.2%), 24 (72.7%), 25 (75.8%) and 26 (78.8%), respectively of the 33 LASA drug pairs. Using the generic name, therapeutic class, and health problem we were able to distinguish 31 (7.2%), 212 (49.1%), and 269 (62.3%), respectively of the 432 FDA-approved indications for the LASA drug pairs., Conclusions: Including the FDA-approved indication in the drug prescription may be used to differentiate LASA drug pairs and thus, prevent wrong drug medication errors.

Registered nurses (RNs) play an important role in safe medication administration and patient safety. This study examined a total of 1276 medication error (ME) incident reports made by RNs in hospital inpatient settings in the southwestern region of the United States. The most common drug class associated with MEs was cardiovascular drugs (24.7%). Among this class, anticoagulants had the most errors (11.3%). The antimicrobials was the second most common drug class associated with errors (19.1%) and vancomycin was the most common antimicrobial that caused errors in this category (6.1%). MEs occurred more frequently in the medical-surgical and intensive care units than any other hospital units. Ten percent of MEs reached the patients with harm and 11% reached the patients with increased monitoring. Understanding the contributing factors related to MEs, addressing and eliminating risk of errors across hospital units, and providing education and resources for nurses may help reduce MEs., (Copyright © 2016 Elsevier Inc. All rights reserved.)

There are many reports regarding various medical institutions' attempts at the prevention of dispensing errors. However, the relationship between occurrence timing of dispensing errors and subsequent danger to patients has not been studied under the situation according to the classification of drugs by efficacy. Therefore, we analyzed the relationship between position and time regarding the occurrence of dispensing errors. Furthermore, we investigated the relationship between occurrence timing of them and danger to patients. In this study, dispensing errors and incidents in three categories (drug name errors, drug strength errors, drug count errors) were classified into two groups in terms of its drug efficacy (efficacy similarity (-) group, efficacy similarity (+) group), into three classes in terms of the occurrence timing of dispensing errors (initial phase errors, middle phase errors, final phase errors). Then, the rates of damage shifting from "dispensing errors" to "damage to patients" were compared as an index of danger between two groups and among three classes. Consequently, the rate of damage in "efficacy similarity (-) group" was significantly higher than that in "efficacy similarity (+) group". Furthermore, the rate of damage is the highest in "initial phase errors", the lowest in "final phase errors" among three classes. From the results of this study, it became clear that the earlier the timing of dispensing errors occurs, the more severe the damage to patients becomes.

Background: Confusion between look-alike and sound-alike (LASA) medication names (such as mercaptamine and mercaptopurine) accounts for up to one in four medication errors, threatening patient safety. Error reduction strategies include computerized physician order entry interventions, and 'Tall Man' lettering. The purpose of this study is to explore the medication name designation process, to elucidate properties that may prime the risk of confusion., Methods and Findings: We analysed the formal and semantic properties of 7,987 International Non-proprietary Names (INNs), in relation to naming guidelines of the World Health Organization (WHO) INN programme, and have identified potential for errors. We explored: their linguistic properties, the underlying taxonomy of stems to indicate pharmacological interrelationships, and similarities between INNs. We used Microsoft Excel for analysis, including calculation of Levenshtein edit distance (LED). Compliance with WHO naming guidelines was inconsistent. Since the 1970s there has been a trend towards compliance in formal properties, such as word length, but longer names published in the 1950s and 1960s are still in use. The stems used to show pharmacological interrelationships are not spelled consistently and the guidelines do not impose an unequivocal order on them, making the meanings of INNs difficult to understand. Pairs of INNs sharing a stem (appropriately or not) often have high levels of similarity (<5 LED), and thus have greater potential for confusion., Conclusions: We have revealed a tension between WHO guidelines stipulating use of stems to denote meaning, and the aim of reducing similarities in nomenclature. To mitigate this tension and reduce the risk of confusion, the stem system should be made clear and well ordered, so as to avoid compounding the risk of confusion at the clinical level. The interplay between the different WHO INN naming principles should be further examined, to better understand their implications for the problem of LASA errors.

Purpose: A medication error (ME) is an error that causes damage or poses a threat of harm to a patient. Several studies have shown that only a minority of MEs actually causes harm, and this might explain why medication reviews at hospital admission reduce the number of MEs without showing an effect on length of hospital stay, readmissions, or death. The purpose of this study was to define drugs that actually cause serious MEs. We conducted a literature search of medication reviews and other preventive efforts., Methods: A systematic search in PubMed, Embase, Cochrane Reviews, Psycinfo, and SweMed+ was performed. Danish databases containing published patient complaints, patient compensation, and reported medication errors were also searched. Articles and case reports were included if they contained information of an ME causing a serious adverse reaction (AR) in a patient. Information concerning AR seriousness, causality, and preventability was required for inclusion., Results: This systematic literature review revealed that 47 % of all serious MEs were caused by seven drugs or drug classes: methotrexate, warfarin, nonsteroidal anti-inflammatory drugs (NSAIDS), digoxin, opioids, acetylic salicylic acid, and beta-blockers; 30 drugs or drug classes caused 82 % of all serious MEs. The top ten drugs involved in fatal events accounted for 73 % of all drugs identified., Conclusion: Increasing focus on seven drugs/drug classes can potentially reduce hospitalizations, extended hospitalizations, disability, life-threatening conditions, and death by almost 50 %.

Objective: To be eligible for incentives through the Electronic Health Record (EHR) Incentive Program, many providers using older or locally developed EHRs will be transitioning to new, commercial EHRs. We previously evaluated prescribing errors made by providers in the first year following transition from a locally developed EHR with minimal prescribing clinical decision support (CDS) to a commercial EHR with robust CDS. Following system refinements, we conducted this study to assess the rates and types of errors 2 years after transition and determine the evolution of errors., Materials and Methods: We conducted a mixed methods cross-sectional case study of 16 physicians at an academic-affiliated ambulatory clinic from April to June 2010. We utilized standardized prescription and chart review to identify errors. Fourteen providers also participated in interviews., Results: We analyzed 1905 prescriptions. The overall prescribing error rate was 3.8 per 100 prescriptions (95% CI 2.8 to 5.1). Error rates were significantly lower 2 years after transition (p<0.001 compared to pre-implementation, 12 weeks and 1 year after transition). Rates of near misses remained unchanged. Providers positively appreciated most system refinements, particularly reduced alert firing., Discussion: Our study suggests that over time and with system refinements, use of a commercial EHR with advanced CDS can lead to low prescribing error rates, although more serious errors may require targeted interventions to eliminate them. Reducing alert firing frequency appears particularly important. Our results provide support for federal efforts promoting meaningful use of EHRs., Conclusions: Ongoing error monitoring can allow CDS to be optimally tailored and help achieve maximal safety benefits., Clinical Trials Registration: ClinicalTrials.gov, Identifier: NCT00603070.

Questions Under Study/principles: Data regarding the prevalence and types of drug-related problems (DRPs) among neurology inpatients is sparse. The objective of this study was to characterise the types of DRPs seen among neurology inpatients and furthermore to study factors affecting the acceptance of clinical pharmacologists' and pharmacists' recommendations for improving drug safety., Methods: 1,263 consecutive inpatient cases in a Swiss university hospital neurology unit were assessed for the presence of DRPs over 12 months. Treating neurologists' acceptance of the resulting recommendations was also recorded. Primary outcome measures were types of DRP, recommendations made by clinical pharmacologists and number of recommendations accepted. Factors potentially associated with acceptance were studied using univariate and multivariate generalised estimating equation modelling., Results: Twenty-nine percent of cases demonstrated one or more DRPs. DRPs were the cause of admission in 10 cases (0.8%). In total 494 DRPs were identified and 467 recommendations given, of which 62% were accepted. Factors associated with an increased likelihood of acceptance were prescriptions involving regularly administered drugs (odds ratio [OR] 2.57 95% confidence interval [CI] 1.73-3.80), adverse drug events (OR 2.5; 95% CI 1.29-5.06), known drug side-effect (OR 1.85; 95% CI 1.06-3.22), high-risk drug-drug interactions (OR 3.22; 95% CI 1.07-9.69) and interventions involving changing a drug (OR 2.71; 95% CI 1.17-6.25)., Conclusion: Clinical pharmacologists and pharmacists can play an important role in identifying DRPs among neurology inpatients. Their recommendations for optimising medication-safety are most likely to be accepted for regular prescriptions, prescriptions associated with an adverse drug event and high-risk drug combinations.

Background: Medication errors can occur at any of the three steps of the medication use process: prescribing, dispensing and administration. We aimed to determine the incidence, type and clinical importance of drug administration errors and to identify risk factors., Methods: Prospective study based on disguised observation technique in four wards in a teaching hospital in Paris, France (800 beds). A pharmacist accompanied nurses and witnessed the preparation and administration of drugs to all patients during the three drug rounds on each of six days per ward. Main outcomes were number, type and clinical importance of errors and associated risk factors. Drug administration error rate was calculated with and without wrong time errors. Relationship between the occurrence of errors and potential risk factors were investigated using logistic regression models with random effects., Results: Twenty-eight nurses caring for 108 patients were observed. Among 1501 opportunities for error, 415 administrations (430 errors) with one or more errors were detected (27.6%). There were 312 wrong time errors, ten simultaneously with another type of error, resulting in an error rate without wrong time error of 7.5% (113/1501). The most frequently administered drugs were the cardiovascular drugs (425/1501, 28.3%). The highest risks of error in a drug administration were for dermatological drugs. No potentially life-threatening errors were witnessed and 6% of errors were classified as having a serious or significant impact on patients (mainly omission). In multivariate analysis, the occurrence of errors was associated with drug administration route, drug classification (ATC) and the number of patient under the nurse's care., Conclusion: Medication administration errors are frequent. The identification of its determinants helps to undertake designed interventions.

As expected, bar-code medication administration systems can prevent medication errors. However, health care organizations must be aware of identified failure points in bar coding that may contribute to errors.

Harmful pediatric medication errors are common in hospitals and health systems. Understanding what products are involved in these errors is important in the prevention of future errors. We used data from a voluntary medication error reporting system (MEDMARX) and identified 816 harmful outcomes involving 242 medications during a 5-year period. Eleven medications accounted for more than one third of reported errors (n = 261 or 34.5%). Wrong dosing and omission errors were common and were associated with therapeutic classes such as opioid analgesics (e.g., morphine and fentanyl), antimicrobial agents (e.g., vancomycin and gentamicin), and antidiabetic agents (e.g., insulin). Older commonly used agents still resulted in a substantial number of harmful pediatric medication errors and should be included in the focus of patient safety activities.

Due to the risk of medications errors from inadvertent interchange of drugs for which names look alike or sound alike, the Joint Commission on Accreditation of Healthcare Organizations now requires that accredited health care organizations develop and maintain programs to minimize these risks. This report lists drug names that can lead to such errors.

Certain medications are designed "high alert' because they could cause serious harm if used incorrectly. Which are the high-alert meds and how can errors be averted?

Investigating the incidence, type, and preventability of adverse drug events (ADEs) and medication errors is crucial to improving the quality of health care delivery. ADEs, potential ADEs, and medication errors can be collected by extraction from practice data, solicitation of incidents from health professionals, and patient surveys. Practice data include charts, laboratory, prescription data, and administrative databases, and can be reviewed manually or screened by computer systems to identify signals. Research nurses, pharmacists, or research assistants review these signals, and those that are likely to represent an ADE or medication error are presented to reviewers who independently categorize them into ADEs, potential ADEs, medication errors, or exclusions. These incidents are also classified according to preventability, ameliorability, disability, severity, stage, and responsible person. These classifications, as well as the initial selection of incidents, have been evaluated for agreement between reviewers and the level of agreement found ranged from satisfactory to excellent (kappa = 0.32-0.98). The method of ADE and medication error detection and classification described is feasible and has good reliability. It can be used in various clinical settings to measure and improve medication safety.

Objective: To provide an overview of and critically appraise classifications of drug-related problems (DRPs) for use during the pharmaceutical care process and research in pharmacy., Data Sources: A literature search was conducted using MEDLINE and Yahoo (January 2003) and manually. The search terms included DRP, drug-related problem, drug-therapy problem, and medicine-related problem., Study Selection and Data Extraction: English- and German-language articles on pharmaceutical care and DRPs were reviewed., Data Synthesis: Most classifications of DRPs were identified through searching publications on pharmaceutical care and DRPs. Fourteen classifications with different focuses were found. Some classifications were hierarchical, categorized into main groups and subgroups. Various terminologies and definitions for DRPs were revealed, as well as guidelines for an optimal DRP classification. Classifications were assessed according to a clear definition, published validation method, and results reflecting process and outcomes, usability in pharmaceutical care practice, and a hierarchical structure with main groups and subgroups., Conclusions: Finding DRP classifications by computerized search of the biomedical literature with the help of PubMed proved to be difficult. No classification could be found that met all of our criteria for an optimal system. Few classifications have been validated. Three have been tested as to their usability in practice and internal consistency. The Pharmaceutical Care Network Europe system Version 4 comes closest to the defined requirements.

Medication errors contribute substantially to patient injury and death, with 25% of these errors attributed to drug names that look or sound alike. This article was written to heighten the awareness of dermatologists and related health care professionals of confusing dermatologic drug names and includes a table of 166 look- and sound-alike drug names. Measures to decrease medication errors due to confusing drug nomenclature in dermatology are suggested in order to maximize patient safety.

To minimize drug name confusion errors, regulators, drug companies, and clinicians need tools that help them predict which names are most likely to be involved in confusions. Two experiments, carried out in the United States, examined the effects of stimulus frequency (i.e., how frequently a target name is prescribed), neighborhood frequency (i.e., how frequently prescribed are the "neighbors" of the target name), and neighborhood density (how many names are within a fixed distance of the target name) on the probability of pharmacists making an error in a visual perceptual identification task. In both experiments, the task was to correctly identify a series of blurry drug names after a 3s presentation on a computer monitor. In the first experiment, 45 pharmacists viewed 160 typewritten names, incorrectly identifying 60.6% of them. Random effects regression revealed a significant beneficial effect of stimulus frequency and a detrimental effect of neighborhood density. Significant two-way interactions were observed between stimulus frequency and neighborhood density and neighborhood frequency and neighborhood density. In the second experiment, 37 pharmacists viewed 156 handwritten drug names, incorrectly identifying 45.7%. Random effects regression revealed significant main effects of stimulus frequency and neighborhood density. These were contained within a significant three-way interaction: The interaction between stimulus frequency and neighborhood density was present at high but not low neighborhood frequency. Objectively measurable frequency and neighborhood characteristics have predictable effects on errors in pharmacists' visual perception. Organizations that coin and evaluate drug names, as well as hospitals, pharmacies, and health systems, should consider these characteristics when assessing visually confusing names.

A literature review was conducted to identify the drug classes, types of errors, and types of adverse outcomes related to preventable adverse drug events (pADEs). Studies were identified by keyword search of MEDLINE and International Pharmaceutical Abstracts and by a manual search. The search was limited to peer-reviewed literature reporting pADEs in hospitalized patients and the frequencies of at least one pADE characteristic. The frequencies of pADEs and their characteristics were summarized using median and range. Ten studies published between 1994 and 2001 were included in the review. The reported median frequency of pADEs was 1.8% (range, 1.3-7.8%), and the median preventability rate of ADEs in the hospitals was 35.2% (range, 18.7-73.2%). Cardiovascular drugs were implicated for 17.9% of pADEs (range, 4.3-28.1%). Most pADEs occurred in the prescribing stage of the medication-use process and were dose related. Inappropriate prescribing decisions and patient monitoring were the most frequently identified causes of pADEs. The most common adverse outcomes were allergic reactions, hepatic or renal problems, cardiovascular problems, hematologic problems and bleeding, and central nervous system problems. Frequently reported examples of pADEs included antihypertensive overdose associated with bradycardia or hypotension, antiinfectives prescribed despite a history of allergy, warfarin overdose and inappropriate monitoring resulting in hemorrhage, and opioid overdose or underdose associated with respiratory depression or poor pain control, respectively. Despite the heterogeneity of pADEs, the results of this literature review suggest that a few types of drugs, errors, and adverse outcomes constitute a substantial proportion of pADEs. Targeting these high-priority areas could significantly reduce the overall frequency of pADEs.

Objective: To describe the drugs and types of medicine management problems most frequently associated with preventable drug related admissions to an acute medical admissions unit., Design: Observation study., Setting: Medical admissions unit in a teaching hospital in Nottingham, UK., Participants: 4093 patients seen by pharmacists on the medical admissions unit between 1 January and 30 June 2001., Main Outcome Measures: Proportion of admissions that were drug related and preventable, classification of the underlying causes of preventable drug related admissions, and identification of drugs most commonly associated with preventable drug related admissions., Results: Of the admissions seen by pharmacists, 265 (6.5%) were judged to be drug related and 178 (67%) of these were judged to be preventable. Preventable admissions were mainly due to problems with prescribing (63 cases (35%)), monitoring (46 cases (26%)), and adherence to medication (53 cases (30%)). The drugs most commonly implicated were NSAIDs, antiplatelets, antiepileptics, hypoglycaemics, diuretics, inhaled corticosteroids, cardiac glycosides, and beta-blockers., Conclusions: Potentially preventable drug related morbidity was associated with 4.3% of admissions to a medical admissions unit. In 91% of cases these admissions were related to problems with either prescribing, monitoring, or adherence.

Medication errors are pervasive in America's health care system. MEDMARX is an Internet-accessible, anonymous medication error reporting program designed for hospitals and health systems to systematically collect, analyze, and report medication errors. This study examined 154,816 medication error reports that were submitted to MEDMARX between January 1, 1999, and December 31, 2001. Data fields analyzed were error category (based on the National Coordinating Council for Medication Error Reporting and Prevention's Error Category Index), type(s) of error, cause(s) of error, contributing factor(s), and product(s) involved. Approximately two-thirds of the errors reported reached the patient, with relatively few causing harm. Death was reported in 19 occurrences. Errors of omission and improper dose/quantity were the most commonly reported. Performance deficit and procedure/protocol not followed were consistently identified as causes of error. Distractions and workload increase were often cited as contributing factors. There was a similar pattern of products reported in each of the years. Implications for quality assurance, clinical practice, and health policy are presented.

Objectives: Medication errors in pediatric inpatients occur at similar rates as in adults but have 3 times the potential to cause harm. Error prevention strategies in this setting remain largely untested. The objective of this study was to classify the major types of medication errors in pediatric inpatients and to determine which strategies might most effectively prevent them., Methods: A prospective cohort study was conducted of 1020 patients who were admitted to 2 academic medical centers during a 6-week period in April and May 1999. Medication errors were characterized by subtype. Physician raters evaluated error prevention strategies and identified those that might be most effective in preventing errors., Results: Of 10 778 medication orders reviewed, 616 contained errors. Of these, 120 (19.5%) were classified as potentially harmful, including 115 potential adverse drug events (18.7%) and 5 preventable adverse drug events (0.8%). Most errors occurred at the ordering stage (74%) and involved errors in dosing (28%), route (18%), or frequency (9%). Three interventions might have prevented most potentially harmful errors: 1) computerized physician order entry with clinical decision support systems (76%); 2) ward-based clinical pharmacists (81%); and 3) improved communication among physicians, nurses, and pharmacists (86%). Interrater reliability of error prevention strategy assignment was good (agreement: 0.92; kappa: 0.82)., Conclusions: Of the assessed interventions, computerized physician order entry with clinical decision support systems; ward-based clinical pharmacists; and improved communication among physicians, nurses, and pharmacists had the greatest potential to reduce medication errors in pediatric inpatients. Development, implementation, and assessment of such interventions in the pediatric inpatient setting are needed.

Many drug names can look or sound like other drug names, which leads to confusion and potentially harmful medication errors. While various types of drug names exist, brand (proprietary) names are most commonly confused. Examples of the numerous drug names that have been confused because they look and/or sound similar include Celebrex (celecoxib), Cerebyx (fosphenytoin), and Celexa (citalopram). Factors such as poor handwriting and clinical similarity may exacerbate the problem. This problem can be alleviated through actions by regulatory agencies, pharmaceutical manufacturers, healthcare professionals, and patients. To address the problem, significant changes in the pharmaceutical regulatory process have occurred in the US and Europe.

Objectives: The objectives were to determine the incidence of drug-related deaths in a university hospital and to find out which drugs are most commonly involved in these cases., Methods: The files of 1511 death cases (97.7% of all death cases in the Helsinki University Central Hospital during the year 2000) were scrutinised. In the cases of suspected drug-related deaths excluding suicides, the medication, its duration and indications, the route of drug administration, and the type of the adverse reactions were determined. The probability of a fatal adverse drug reaction was classified according to WHO's classification. In addition, the incidence of drug-related deaths was calculated from the death certificates., Results: Scrutiny of the patients' files showed that 75 of the death cases (5.0% of all deaths) were certainly or probably drug-related. This corresponds to about 0.05% of all hospital admissions. The most common adverse reactions were neutropenia caused by antineoplastic agents and gastrointestinal or intracranial haemorrhage due to anticoagulants or nonsteroidal anti-inflammatory drugs (NSAIDs). The incidence of drug-related deaths is only 0.5% when based on the International Classification of Diseases (ICD) codes in death certificates., Conclusions: Adverse drug reaction is a significant cause of death. Most of the deaths occurred in seriously ill patients with high-risk medication and they are seldom preventable. Incidence figures based on death certificates only may seriously underestimate the true incidence of fatal adverse reactions.

Health professionals and patients tend to confuse drugs with similar names, thereby threatening patient safety. One out of four medication errors voluntarily reported in the US involves this type of drug name confusion. Cognitive psychology offers insight into how and why these errors occur. The objective of this investigation was to examine the effect of orthographic (i.e., spelling) and phonological (i.e., sound) similarity on the probability of making recognition memory errors (i.e., false recognitions). Prospective, computer-based, recognition memory experiments on 30 pharmacists and 66 college students were conducted. Participants viewed a study list of drug names and then a test list. The test list was twice as long as the study list and contained distractor names at progressively increasing levels of similarity to the study words. The task was to identify which test names were on study list and which were new. The main outcome measure was probability of making a false recognition error (i.e., of saying a new name was on the study list). Among pharmacists and college students, there was a strong and significant effect of similarity on the probability of making a false recognition error. It was concluded that both orthographic (i.e., spelling) and phonological (i.e., sound) similarity increase the probability that experts and novices will make false recognition errors when trying to remember drug names. Similarity is easily and cheaply measured, and therefore, steps should be taken to monitor and reduce similarity as a means of reducing the likelihood of drug name confusions.

A model for predicting medication name confusion is described. Many medication errors are caused by look-alike and sound-alike medication names, yet few procedures exist to ensure the safety of new drug nomenclature or to identify confusingly similar names from within existing databases. In this study, three automated, quantitative measures of orthographic similarity (i.e., similarity in spelling) were identified (bigram similarity, trigram similarity, and Levenshtein distance). The relationship between orthographic similarity and the likelihood of a medication error was examined. For each measure of similarity, the frequency distribution of similarity scores for pairs of drug names previously reported to cause confusion (error pairs) was compared with the distribution of similarity scores for control pairs randomly selected from the general index of USP DI-Volume I: Drug Information for the Health Care Professional. Then, three parallel, unmatched case-control studies were conducted to discover whether similarity was a significant risk factor for medication errors. Finally, on the basis of the three similarity measures, tests for predicting confusion were developed and evaluated. For each similarity measure, the frequency distribution of error pairs was significantly different from that for control pairs, and orthographic similarity was a significant risk factor for medication errors. Pairs of names whose measures of similarity exceeded present thresholds were between 25 and 523 times more likely to be involved in a medication error than pairs whose similarity did not exceed these thresholds. A prognostic test that correctly identified 91% of all pairs as either errors or controls was developed. This test had a sensitivity of 84% and a specificity of 99%. Automated measures of similarities between medication names can form the basis of highly accurate, sensitive, and specific tests of the potential for errors with look-alike and sound-alike medication names.