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Importance: The National Action Plan for Adverse Drug Event (ADE) Prevention identified 3 high-priority, high-risk drug classes as targets for reducing the risk of drug-related injuries: anticoagulants, diabetes agents, and opioids., Objective: To determine whether a multifaceted clinical pharmacist intervention improves medication safety for patients who are discharged from the hospital and prescribed medications within 1 or more of these high-risk drug classes., Design, Setting, and Participants: This randomized clinical trial was conducted at a large multidisciplinary group practice in Massachusetts and included patients 50 years or older who were discharged from the hospital and prescribed at least 1 high-risk medication. Participants were enrolled into the trial from June 2016 through September 2018., Interventions: The pharmacist-directed intervention included an in-home assessment by a clinical pharmacist, evidence-based educational resources, communication with the primary care team, and telephone follow-up. Participants in the control group were provided educational materials via mail., Main Outcomes and Measures: The study assessed 2 outcomes over a 45-day posthospital discharge period: (1) adverse drug-related incidents and (2) a subset defined as clinically important medication errors, which included preventable or ameliorable ADEs and potential ADEs (ie, medication-related errors that may not yet have caused injury to a patient, but have the potential to cause future harm if not addressed). Clinically important medication errors were the primary study outcome., Results: There were 361 participants (mean [SD] age, 68.7 [9.3] years; 177 women [49.0%]; 319 White [88.4%] and 8 Black individuals [2.2%]). Of these, 180 (49.9%) were randomly assigned to the intervention group and 181 (50.1%) to the control group. Among all participants, 100 (27.7%) experienced 1 or more adverse drug-related incidents, and 65 (18%) experienced 1 or more clinically important medication errors. There were 81 adverse drug-related incidents identified in the intervention group and 72 in the control group. There were 44 clinically important medication errors in the intervention group and 45 in the control group. The intervention did not significantly alter the per-patient rate of adverse drug-related incidents (unadjusted incidence rate ratio, 1.13; 95% CI, 0.83-1.56) or clinically important medication errors (unadjusted incidence rate ratio, 0.99; 95% CI, 0.65-1.49)., Conclusions and Relevance: In this randomized clinical trial, there was not an observed lower rate of adverse drug-related incidents or clinically important medication errors during the posthospitalization period that was associated with a clinical pharmacist intervention. However, there were study recruitment challenges and lower than expected numbers of events among the study population., Trial Registration: ClinicalTrials.gov Identifier: NCT02781662.

Background: Most residents in elderly care homes in Sri Lanka do not receive formal, on-site, patient care services., Objective: To evaluate the appropriateness of prescribing, dispensing, administration, and storage practices of medication used by residents in selected elderly care homes in Colombo District, Sri Lanka., Methodology: This was a prospective, cross-sectional, multi-center study of 100 residents with chronic, non-communicable diseases, who resided in nine selected elderly care homes in Sri Lanka. Medication histories were obtained from each resident/caregiver and the appropriateness of medications in their current prescription was reviewed using standard treatment guidelines. Prescriptions were cross-checked against respective dispensing labels to identify dispensing errors. Medication administration was directly observed on two separate occasions per resident for accuracy of administration, and matched against the relevant prescription instructions. Medication storage was also observed in terms of exposure to temperature and sunlight, the suitability of container, and adequacy of separation if using multiple medications., Results: The mean age of residents was 70±10.5 years and the majority were women (72%). A total of 168 errors out of 446 prescriptions were identified. The mean number of prescribing errors per resident was 1.68±1.23 [median, 2.00 (1.00-3.00)]. Inappropriate dosing frequencies were the highest (37.5%;63/168), followed by missing or inappropriate medications (31.5%;53/168). The mean number of dispensing errors per resident was 15.9±13.1 [median, 14.0 (6.00-22.75)] with 3.6 dispensing errors per every medication dispensed. Mean administration errors per resident was 0.95±1.5 [median, 0.00 (0.00-1.00)], with medication omissions being the predominant error (50.5%;48/95). Another lapse was incorrect storage of medications (143 storage errors), and included 83 medications not properly separated from each other (58.0%)., Conclusion: Multiple errors related to prescribing, dispensing, administration, and storage were identified amongst those using medication in elderly care homes. Services of a dedicated consultant pharmacist could improve the quality of medication use in elderly care homes in Sri Lanka., Competing Interests: The authors have declared that no competing interests exist.

Objectives: Failure mode effect analysis (FMEA) improves safety in the drug life cycle. As the drug dispensation by hospital's pharmacy can be at risk, the FMEA tool has been used to evaluate and enhance the process., Methods: After detailing the process, a first FMEA has been run in 2015. Corrective actions were implemented every time criticality indexes (CI) were above 15. One year later, we have evaluated potential impacts of these actions by running a new FMEA., Results: In 2015, 11 failure modes were prioritized (CI>15) and the total CI for the overall process was 397. Corrective actions were implemented and one year later this amount has decreased by 14% (340) with 6 failure modes still prioritized. Thus, thanks to the FMEA, risks could be identified in year "y", they were taken into account and corrected and then effectively reassessed in year "y+1"., Conclusion: This study showed us the interest of performing FMEA analysis in the drug dispensation process by hospital. The renewal of this risk analysis after a year helped us to monitor corrective actions, to evaluate their effectiveness and to improve safety. Finally, FMEA seems to be an effective way to steer the drug dispensation process., (Copyright © 2019 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.)

Background: Healthcare organizations have long been dependent on the vigilance of nurses to identify and intercept medication errors before they can adversely affect patients. New technologies have been implemented in an effort to reduce medication errors; however, few studies have evaluated the long-term effects of technology-based interventions in reducing medication errors., Aim: The aim of this study was to evaluate the effects of barcode medication administration (BCMA) and the closed-loop medication system (CLMS) interventions on medication errors and adverse drug event (ADE) rates., Methods: An autoregressive integrated moving average model for interrupted time series design was used to evaluate the impact of the BCMA and CLMS interventions on the monthly reported medication error and ADE rates at Humber River Hospital between September 2013 and August 2018. Descriptive statistics were generated to evaluate the types of error and their gravity., Results: A total of 1,712 medication errors and ADEs were reported in the five-year study period. The results of the interrupted time series indicated that the introduction of the BCMA intervention was associated with a statistically significant gradual decrease in reported medication error and ADE rates at 0.002 percentage points per month (p = 0.003). The introduction of the CLMS intervention was associated with an immediate absolute decrease in reported medication error and ADE rates of 0.010% (p = 0.020)., Conclusions: The findings from this study support the adoption of both BCMA and CLMS interventions to prevent medication errors. Staged implementation of CLMS allows time for learning and incorporating barcode scanning. Interprofessional and cross-functional collaboration is necessary to successfully integrate the requirements of each respective discipline and service in the CLMS., (Copyright © 2019 Longwoods Publishing.)

This study developed the Automated Medical Error Risk Assessment System (Auto-MERAS), which was incorporated into the electronic health record system. The system itself maintained high predictive validity for medication errors at the area under the receiver operating characteristic curves of above 0.80 at the time of development and validation. This study has found possibilities to predict the risk of medication errors that are sensitive to situational and environmental risks without additional data entry from nurses.

Using data obtained through 2 multidisciplinary studies focused on medication safety effectiveness, this article provides nursing recommendations to decrease medication delivery errors. Strategies to minimize and address interruptions/distractions are proposed for the 3 most problematic time frames in which medication errors typically arise: medication acquisition, transportation, and bedside delivery. With planned interventions such as programmed scripts and hospital-based protocols to manage interruptions and distractions, patient safety can be maintained in the inpatient setting.

Gamification is used in clinical context in the health care education. Furthermore, it has shown great promises to improve the performance of the health care staff in their daily routine. In this work we focus on the medication sorting task, which is performed manually in hospitals. This task is very error prone and needs to be performed daily. Nevertheless, errors in the medication are crucial and lead to serious complications. In this work we present a real world gamification approach of the medication sorting task in a patient's daily pill organizer. The player of the game needs to sort the correct medication into the correct dispenser slots and is rewarded or punished in real time. At the end of the game, a score is given and the user can register in a leaderboard.

The purpose of this study was to examine the number and types of discrepancy errors present after discharge from home healthcare in older adults at risk for medication management problems following an episode of home healthcare. More than half of the 414 participants had at least one medication discrepancy error (53.2%, n = 219) with the participant's omission of a prescribed medication (n = 118, 30.17%) occurring most frequently. The results of this study support the need for home healthcare clinicians to perform frequent assessments of medication regimens to ensure that the older adults are aware of the regimen they are prescribed, and have systems in place to support them in managing their medications.

Introduction: Automated dose dispensing (ADD) is being introduced in several countries and the use of this technology is expected to increase as a growing number of elderly people need to manage their medication at home. ADD aims to improve medication safety and treatment adherence, but it may introduce new safety issues. This descriptive study provides insight into the nature and consequences of medication incidents related to ADD, as reported by healthcare professionals in community pharmacies and hospitals., Methods: The medication incidents that were submitted to the Dutch Central Medication incidents Registration (CMR) reporting system were selected and characterized independently by two researchers., Main Outcome Measures: Person discovering the incident, phase of the medication process in which the incident occurred, immediate cause of the incident, nature of incident from the healthcare provider's perspective, nature of incident from the patient's perspective, and consequent harm to the patient caused by the incident., Results: From January 2012 to February 2013 the CMR received 15,113 incidents: 3,685 (24.4%) incidents from community pharmacies and 11,428 (75.6%) incidents from hospitals. Eventually 1 of 50 reported incidents (268/15,113 = 1.8%) were related to ADD; in community pharmacies more incidents (227/3,685 = 6.2%) were related to ADD than in hospitals (41/11,428 = 0.4%). The immediate cause of an incident was often a change in the patient's medicine regimen or relocation. Most reported incidents occurred in two phases: entering the prescription into the pharmacy information system and filling the ADD bag., Conclusion: A proportion of incidents was related to ADD and is reported regularly, especially by community pharmacies. In two phases, entering the prescription into the pharmacy information system and filling the ADD bag, most incidents occurred. A change in the patient's medicine regimen or relocation was the immediate causes of an incident.

Purpose: Clinical decision support systems (CDSS) may potentially improve prescribing quality, but are subject to poor user acceptance. Reasons for alert overriding have been identified and counterstrategies have been suggested; however, poor alert specificity, a prominent reason of alert overriding, has not been well addressed. This paper aims at structuring modulators that determine alert specificity and estimating their quantitative impact on alert burden., Methods: We developed and summarized optimizing strategies to guarantee the specificity of alerts and applied them to a set of 100 critical and frequent drug interaction (DDI) alerts. Hence, DDI alerts were classified as dynamic, i.e. potentially sensitive to prescription-, co-medication-, or patient-related factors that would change alert severity or render the alert inappropriate compared to static, i.e. always applicable alerts not modulated by cofactors., Results: Within the subset of 100 critical DDI alerts, only 10 alerts were considered as static and for 7 alerts, relevant factors are not generally available in today's patient charts or their consideration would not impact alert severity. The vast majority, i.e. 83 alerts, might require a decrease in alert severity due to factors related to the prescription (N=13), the co-medication (N=11), individual patient data (N=36), or combinations of them (N=23). Patient-related factors consisted mainly of three lab values, i.e. renal function, potassium, and therapeutic drug monitoring results., Conclusion: This paper outlines how promising the refinement of knowledge bases is in order to increase specificity and decrease alert burden and suggests how to structure knowledge bases to refine DDI alerting., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Objective: This study examined the opinions of nurses about the introduction of enrolled nurse medication administration and analyzed its impact on the medication error rate., Methods: Data were collected using a survey and examination of incident reports regarding nursing medication errors. Nurses (registered nurse, enrolled nurse with medication endorsement, enrolled nurse) responded to survey items regarding the introduction of enrolled nurse medication administration. Data analysis included descriptive statistics, Fischer's exact test, and chi-square analysis where appropriate., Results: The majority of nurses (75.2%) supported enrolled nurse medication administration. However, differences in opinion were observed between registered nurse (RN) and enrolled nurse with medication endorsement (ENME) regarding clear understanding of responsibility and accountability (RN: 47.2% vs. ENME: 77.8%; p =.033), and whether suitable education was provided (RN: 34.7% vs. ENME: 73.7%; p =.012). Moreover, less than one-third of RNs agreed that the assessment process for EN medication endorsement clearly identified the competence of the ENME to administer medications. Nonetheless, nursing medication errors did not increase in the 12-month period after the introduction of enrolled nurse medication administration (pre: 314, post: 302)., Conclusions: The findings of this study suggest areas that should be addressed in the future, including assessment of competence and focused education about accountability and responsibility., (© 2012 Wiley Periodicals, Inc.)

Background and Objective: Many dispensing errors occur in hospital pharmacies and can harm patients if they are not intercepted. The aim of this study was to determine the incidence and the primary types of medication dispensing errors at a French military hospital., Method: The check of unit dose medication cassettes was performed by nurses. From February 2007 to April 2007, detected dispensing errors were systematically recorded and classified into 6 categories: unauthorized drug, wrong dosage-form, improper dose, omission, wrong time, and deteriorated drug errors. The overall error rate was calculated., Results: During the study, 5112 medication cassettes were checked. 106 dispensing errors have been detected by nurses for a total of 45,573 filled (n=45,518) and omitted (n=55) unit doses. An overall error rate of 0.23% was found. There were approximately 0.02 detected dispensing errors per medication cassette. The most common error types were omission errors (n=55, 51.88%) and improper dose errors (n=30, 28.30%)., Discussion-Conclusion: The results of this study showed that a check performed by nurses after the dispensing process is necessary to detect the dispensing errors. Many causes may explain the occurrence of dispensing errors and must be corrected. Because some dispensing errors may remain undetected, there is a requirement to develop strategies in order to reduce or eliminate these errors, such as the implementation of a computerized prescribing system. The pharmacy staff is widely involved in this duty.

Clinical pharmacologists are all dedicated to improving the use of medications and decreasing medication errors and adverse drug reactions. However, quality improvement requires that some significant parameters of quality be categorized, measured, and tracked to provide benchmarks to which future data (performance) can be compared. One of the best ways to accumulate data on medication errors and adverse drug reactions is to look at medical malpractice data compiled by the insurance industry. Using data from PHICO insurance company, PHICO's Closed Claims Data, and PHICO's Event Reporting Trending System (PERTS), this article examines the significance and trends of the claims and events reported between 1996 and 1998. Those who misread history are doomed to repeat the mistakes of the past. From a quality improvement perspective, the categorization of the claims and events is useful for reengineering integrated medication delivery, particularly in a hospital setting, and for redesigning drug administration protocols on low therapeutic index medications and "high-risk" drugs. Demonstrable evidence of quality improvement is being required by state laws and by accreditation agencies. The state of Florida requires that quality improvement data be posted quarterly on the Web sites of the health care facilities. Other states have followed suit. The insurance industry is concerned with costs, and medication errors cost money. Even excluding costs of litigation, an adverse drug reaction may cost up to $2500 in hospital resources, and a preventable medication error may cost almost $4700. To monitor costs and assess risk, insurance companies want to know what errors are made and where the system has broken down, permitting the error to occur. Recording and evaluating reliable data on adverse drug events is the first step in improving the quality of pharmacotherapy and increasing patient safety. Cost savings and quality improvement evolve on parallel paths. The PHICO data provide an excellent opportunity to review information that typically would not be in the public domain. The events captured by PHICO are similar to the errors and "high-risk" drugs described in the literature, the U.S. Pharmacopeia's MedMARx Reporting System, and the Sentinel Event reporting system maintained by the Joint Commission for the Accreditation of Healthcare Organizations. The information in this report serves to alert clinicians to the possibility of adverse events when treating patients with the reported drugs, thus allowing for greater care in their use and closer monitoring. Moreover, when using high-risk drugs, patients should be well informed of known risks, dosage should be titrated slowly, and therapeutic drug monitoring and laboratory monitoring should be employed to optimize therapy and minimize adverse effects.

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.

Background: Medication errors are a national concern., Objective: To identify the prevalence of medication errors (doses administered differently than ordered)., Design: A prospective cohort study., Setting: Hospitals accredited by the Joint Commission on Accreditation of Healthcare Organizations, nonaccredited hospitals, and skilled nursing facilities in Georgia and Colorado., Participants: A stratified random sample of 36 institutions. Twenty-six declined, with random replacement. Medication doses given (or omitted) during at least 1 medication pass during a 1- to 4-day period by nurses on high medication-volume nursing units. The target sample was 50 day-shift doses per nursing unit or until all doses for that medication pass were administered., Methods: Medication errors were witnessed by observation, and verified by a research pharmacist (E.A.F.). Clinical significance was judged by an expert panel of physicians., Main Outcome Measure: Medication errors reaching patients., Results: In the 36 institutions, 19% of the doses (605/3216) were in error. The most frequent errors by category were wrong time (43%), omission (30%), wrong dose (17%), and unauthorized drug (4%). Seven percent of the errors were judged potential adverse drug events. There was no significant difference between error rates in the 3 settings (P =.82) or by size (P =.39). Error rates were higher in Colorado than in Georgia (P =.04), Conclusions: Medication errors were common (nearly 1 of every 5 doses in the typical hospital and skilled nursing facility). The percentage of errors rated potentially harmful was 7%, or more than 40 per day in a typical 300-patient facility. The problem of defective medication administration systems, although varied, is widespread.

This prospective single-blinded study aimed to compare the types of medication errors and medication error rates of two medication delivery systems. The setting was a 30 bed surgical ward that was divided into two identical areas. In one area medications were stored and issued in a ward bay workstation immediately outside the patients' rooms. The alternate area used a medication trolley at the patients' bedside. Three hundred and forty opportunities for errors were observed using five nurse educators. Twenty administration errors (5.8% error rate) and two dispensing errors (0.6% error rate) were detected. A statistically significant difference was found between the two systems, where four errors occurred from the medication trolley (2.6% error rate), and fifteen errors occurred from the ward bay (9.2% error rate). These results suggest that medications were less likely to be omitted and more likely to be given on time when they were issued at the patient's bedside using the medication trolley.

The implementation and impact of an automated check-and-sortation system in a correctional health care system are described. In February 1998 the Managed Health Care Division of the University of Houston College of Pharmacy submitted a proposal to the Texas State Board of Pharmacy for installing an automated check-and-sortation device in its distributive system serving Texas Department of Criminal Justice offenders. The new system would eliminate final visual verification of medication orders by pharmacists and thereby give them more time for in-depth reviews of patient profiles and for recommending clinical interventions. A vendor interested in developing a prototypic automated system was identified, and a disease management training course was developed to enable staff pharmacists to provide evidence-based pharmacotherapy recommendations. Twelve months of data before automation (February 1997 to January 1998) were compared with 16 months of postautomation data (June 1998 to September 1999). The number of clinical interventions increased from 396 per 100,000 medication orders filled before automation to 1075 per 100,000 orders after automation. Dispensing errors decreased from 6.3 to 4.1 per 100,000 medication orders filled. Identified filling errors increased from 224 to 256 per 100,000 orders. The reliability of the automated system was evidenced by a dispensing error rate of 0.6 per 100,000 orders. Implementation of an automated check-and-sortation device in a correctional health care system appeared to reduce dispensing errors and give pharmacists more time to review patient profiles and recommend clinical interventions.