Search

Medication errors are one of the causes of iatrogenic medication use in children. The POPI tool for detecting inappropriate drug prescriptions and prescription omissions in paediatrics was the first tool to be published in this field in 2014. Our aim was to update the POPI tool for French use based on current recommendations and practice. Criteria were removed, updated or added based on recommendations from learned societies and national bodies. The two-round Delphi method was used to reach a consensus of experts. The level of agreement of the healthcare professionals' proposals was rated on a 9-point Likert scale. In the first round, only proposals with a median agreement of 7 to 9 and an agreement of more than 65% were retained. In the second round, only those with a median agreement of 7 to 9 and over 75% agreement were retained. The POPI tool now includes eight categories (various, infectiology, gastroenterology, pneumonology, dermatology, neurology/pedopsychiatry, haematology and excipients). All the criteria were supported by bibliographical references. They were submitted to 20 French healthcare professionals: 9 pharmacists and 11 doctors (17 hospital-based and 3 self-employed). After two rounds of Delphi testing, 166 criteria were retained and validated (111 inappropriate prescriptions and 55 omissions). In conclusion, this study made it possible to update the POPI tool, which is still available for assessing paediatric prescriptions., (Copyright © 2024 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.)

Objective: To identify the frequency and types of prescription errors, assess adherence to WHO prescribing indicators, and highlight the gaps in current prescribing practices of Junior dental practitioners in a tertiary care hospital in Karachi, Pakistan., Methods: This cross-sectional study was conducted from January 2021 to March 2021. The study included the prescriptions by house surgeons and junior postgraduate medical trainees for walk-in patients visiting the dental outpatient department. A total of 466 prescriptions were evaluated for WHO core drug prescribing indicators. The prescription error parameters were prepared by studying the WHO practical manual on guide to good prescribing and previous studies. Prescription errors, including errors of omission related to the physician and the patients, along with errors of omission related to the drug, were also noted. The statistical analysis was performed with SPSS version 25. Descriptive analysis was performed for qualitative variables in the study., Results: The average number of drugs per encounter was found to be 3.378 drugs per prescription. The percentage of encounters with antibiotics was 96.99%. Strikingly, only 16.95% of the drugs were prescribed by generic names and 23.55% of drugs belonged to the essential drug list. The majority lacked valuable information related to the prescriber, patient, and drugs. Such as contact details 419 (89.9%), date 261 (56%), medical license number 466 (100%), diagnosis 409 (87.8%), age and address of patient 453 (97.2%), form and route of drug 14 (3%), missing drug strength 69 (14.8%), missing frequency 126 (27%) and duration of treatment 72 (15.4%). Moreover, the wrong drug dosage was prescribed by 89 (19%) prescribers followed by the wrong drug in 52 (11.1%), wrong strength in 43 (9.2%) and wrong form in 9 (1.9%). Out of 1575 medicines prescribed in 466 prescriptions, 426 (27.04%) drug interactions were found and 299 (64%) had illegible handwriting., Conclusion: The study revealed that the prescription writing practices among junior dental practitioners are below optimum standards. The average number of drugs per encounter was high, with a significant percentage of encounters involving antibiotics. However, a low percentage of drugs were prescribed by generic name and from the essential drug list. Numerous prescription errors, both omissions and commissions, were identified, highlighting the need for improved training and adherence to WHO guidelines on good prescribing practices. Implementing targeted educational programs and stricter regulatory measures could enhance the quality of prescriptions and overall patient safety., (© 2024. The Author(s).)

Introduction: Prescription is the node of medication management and use that most frequently presents medication errors, according to various studies. This study aims to analyze prescriptions before and after the incorporation of a multidisciplinary round in the pediatric intensive care area and its implication in the occurrence of adverse drug events., Methods: This is an uncontrolled before and after study., Results: 100 patients were studied before and 100 after, range 1-17 years, mean age: 6.4 SD: 8.7. 55.5% (n = 111) were men. A prescription error was detected before the intervention of 12% (n = 12) and after 0% of the intervention, 0%, p = 0.001. A total of 45 adverse events were detected, that is, 45 adverse events per 100 admissions and 38, that is, 38 events per 100 admissions, before and after the intervention respectively (p > 0.05)., Conclusion: The intervention was useful to reduce prescription error in this sample of patients.

What Is Known and Objective: Prescribing errors are prevalent in hospital settings, with provision of feedback recommended to support prescribing by doctors. To evaluate the impact of a pharmacist-led prescription intervention system on prescribing error rates and to measure intervention efficiency., Methods: All prescribers in Shandong Provincial Third Hospital received feedback from ward pharmacists using a pharmacist-led prescription intervention system. The prescribing error rate was calculated from Oct 2019 to December 2020. After the intervention was applied, the rates of PASS 1 (System pass), PASS 2 (Pharmacist pass) and PASS 3 (Pharmacist-doctor pass) events and the feedback time were calculated each month., Results and Discussion: Irrational use of drugs was reduced and the prescription rate increased significantly. The error rate reduced from 6.94% to 1.96%, representing an estimated 71.76% decrease overall (p < 0.05). The PASS 1 rate gradually increased from 88% to 96% (p < 0.05), the PASS 2 rate gradually decreased from 5.06% to 2.04% (p < 0.05), the PASS 3 rate gradually decreased from 6.94% to 1.96% (p < 0.05)., What Is New and Conclusion: The pharmacist-led prescription intervention system has the potential to reduce prescribing errors and improve prescribing outcomes and patient safety., (© 2021 John Wiley & Sons Ltd.)

Prescription errors in high alert drugs (HAD), a group of drugs that have a high risk of complications and potential negative consequences, are a major and serious problem in medicine. Standardized hospital interventions, protocols, or guidelines were implemented to reduce the errors but were not found to be highly effective. Machine learning driven clinical decision support systems (CDSS) show a potential solution to address this problem. We developed a HAD screening protocol with a machine learning model using Gradient Boosting Classifier and screening parameters to identify the events of HAD prescription errors from the drug prescriptions of out and inpatients at Maharaj Nakhon Chiang Mai hospital in 2018. The machine learning algorithm was able to screen drug prescription events with a risk of HAD inappropriate use and identify over 98% of actual HAD mismatches in the test set and 99% in the evaluation set. This study demonstrates that machine learning plays an important role and has potential benefit to screen and reduce errors in HAD prescriptions., (© 2021. The Author(s).)

Background: Clinical pharmacists are contributing to safe medication use by providing comprehensive management to patients and medical staff. The aim of this study is to document and evaluate the role of clinical pharmacy services in oncology department., Patients and Methods: A prospective, descriptive, observational study was carried out from July 2018 through June 2019 at the Department of Medical Oncology at the National Institute of Oncology, Morocco. Medication reviews concerning hospitalized adult cancer patients were performed every day by the clinical pharmacist assigned to the department., Results: A total of 3542 prescriptions of 526 adult cancer patients were analyzed. The pharmacist identified 450 drug-related problems (12.7% of the prescriptions) primarily related to the analgesics (31.5%). Medication problems included mostly untreated indications (31.3%), overdosing (17.1%), drug-drug interactions (12.4%), underdosing (11.1%), administration omissions (6.7%), drug not indicated (6.0%), and contraindication (5.3%). Interventions ( n  = 450) led to drug additions (30.7%), drug dosing adjustments (27.1%), treatment discontinuations (20.0%), recall of the treatment (6.2%), replacement of a drug with another one (5.1%), administration optimization (4.0%), therapeutic drug monitoring (3.1%), alternate routes of administration (2.5%), and extension of treatment duration (1.3%). Most (98%) of the interventions were accepted and implemented by the medical staff-172 (38.2%) having a significant clinical impact on the patient, 88 (19.6%) as having a very significant clinical impact, and 71(15.8%) as having a potential vital impact., Conclusion: This work highlights the positive clinical relevance of pharmacists' interventions in oncology and the importance of medicopharmaceutical collaboration to prevent medication error.

Aims: To enumerate and classify errors in physicians' orders of antiseizure medications (ASMs) to people with epilepsy presenting to neurology clinic., Methods: This cross-sectional study was conducted in the neurology clinic of a teaching hospital catering to a predominantly rural population. People in whom a diagnosis of epilepsy was confirmed and who presented for the first time with a prior prescription for antiseizure medication/s were included. Their immediate previous prescriptions were assessed for errors, enumerated and classified according to WHO guidelines for prescription writing., Results: Hundred prescriptions of 334 patients screened were analyzed. The number of ASMs prescribed to a participant was 2 ± 0.6 (mean ± SD). We identified a mean of 5 ± 4 (median: 3; range: 1-7) errors in each order. These included superscription errors, e.g., missing information on seizure control and frequency (n = 90, 90%), generic name (n = 62, 62%), patient identifiers (n = 57, 57%), prescribers' identifiers (n = 29, 29%) and diagnosis or indication for prescribing the medication/s (n = 55, 55%). The most common inscription and subscription errors were dosing errors (22%) and pharmaceutical form errors (20%) followed by omission (13%), duplication (13%), substitution (12%), commission (9%) and frequency errors (8%). Errors were more common among prescriptions provided by primary-care and Ayurvedic, Yoga and Naturopathy, Unani, Siddha and Homeopathy (AYUSH) physicians compared to specialists (P < 0.05)., Conclusions: Errors are common among medication orders provided by non-specialist and specialist physicians. Primary care and AYUSH are more liable to make errors underscoring the need to educate them in basic epilepsy treatment., Competing Interests: Declaration of competing interest There is no conflict of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Introduction: Prescribing errors are a principal cause of preventable harm in healthcare. This study aims to establish a systematic approach to analysing prescribing-related adverse incident reports, in order to elucidate the characteristics and contributing factors of common prescribing errors and target multifaceted quality improvement initiatives., Methods: All prescribing-related adverse incident reports submitted across one NHS board over 12 months were selected. Incidents involving commonly implicated drugs (involved in ≥10 incidents) underwent analysis to establish likely underlying causes using Reason's Model of Accident Causation., Results: 330 prescribing-related adverse incident reports were identified. Commonly implicated drugs were insulin (10% of incidents), gentamicin (7%), co-amoxiclav (5%) and amoxicillin (5%). The most prevalent error types were prescribing amoxicillin when contraindicated due to allergy (5%); prescribing co-amoxiclav when contraindicated due to allergy (5%); prescribing the incorrect type of insulin (3%); and omitting to prescribe insulin (3%). Error-producing factors were identified in 86% of incidents involving commonly implicated drugs. 53% of incidents involved error-producing factors related to the working environment; 38% involved factors related to the healthcare team; and 37% involved factors related to the prescriber., Discussion: This study establishes that systematic analysis of adverse incident reports can efficiently identify the characteristics and contributing factors of common prescribing errors, in a manner useful for targeting quality improvement. Furthermore, this study produced a number of salient findings. First, a narrow range of drugs were implicated in the majority of incidents. Second, a small number of error types were highly recurrent. Lastly, a range of contributing factors were evident, with those related to the working environment contributing to the majority of prescribing errors analysed., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background Prescribing errors in children are common due to individualization of dosage regimen. It potentially has a great impact especially in this vulnerable population. Objective To determine the prevalence and common types of prescribing errors in a Malaysian pediatric outpatient department and to determine the factors contributing to prescribing errors. Setting Pediatric Outpatient Department and Outpatient Pharmacy at a tertiary care hospital in Malaysia. Method This is a prospective, cross sectional observational study where all new prescriptions received by the outpatient pharmacy from patients attending pediatric out-patient clinic were included for analysis. Descriptive statistics and logistic regression were used to analyze the data. Main outcome measure Frequency, types, potential clinical consequences and contributing factors of prescribing errors. Results Two hundred and fifty new prescriptions with 493 items were analyzed. There were 13 per 100 prescriptions with at least one prescribing error and 7.3% of the total items were prescribed incorrectly. The most common types of prescribing error were, an ambiguous prescription (61.1%) followed by an unrecommended dose regimen (13.9%). Logistic regression analysis showed that the risk of a prescribing error significantly increased when the prescription was written by a house officer (OR 4.72, p = 0.029). Errors were judged to be potentially non-significant (33.3%), significant (36.1%), or serious (30.6%). Conclusion The experience of prescribers is an important factor that contributes to prescribing errors in pediatrics. Many of the errors made were potentially serious and may impact on the patients' well-being.

Objectives: To compare the transcribing error rates of discharge prescriptions between pharmacy technicians and doctors in an acute hospital setting., Methods: Pharmacy technicians were trained in the transcribing of discharge medications from inpatient to discharge medication charts. Prospective prescribing audits were undertaken over 5 days on eight hospital medical wards by ward pharmacists to compare pharmacy technician (on four wards) and doctor (on four wards) discharge transcribing error rates. Transcribed discharge medications were compared with the inpatient medication list by ward pharmacists to identify any transcription errors. Transcribing data for each technician and doctor, and number of items and errors, were input into SPSS and analysed using relevant statistical tests., Results: Doctors (n=12) transcribed 77 discharge prescriptions, and 678 items with 127 errors recorded (18.7% error rate). Pharmacy technicians (n=8) transcribed 63 discharge prescriptions, and 654 items with 25 errors recorded (3.8% error rate), a significant difference between groups in error frequency (χ 2 (1)=58.6, p=<0.005) with a 14.9% difference between groups., Conclusions: Pharmacy technicians have significantly lower discharge transcribing error rates compared with doctors. This service intervention has the potential to improve patient safety and minimise inefficiencies from correcting errors. Further work is needed to explore the views and opinions of service users of the intervention, and why technician-transcribing error rates are significantly lower than doctors., Competing Interests: Competing interests: None declared., (© European Association of Hospital Pharmacists 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Medical doctors are required to prescribe drugs safely and effectively upon qualification, a skill that many feel poorly prepared to undertake. To better prepare doctors, a whole-task approach that develops knowledge and skills, but that also considers the effect of the complex clinical workplace on prescribing, is optimal. We describe an evaluation of an experiential learning programme that allows senior medical students to gain experience with inpatient prescribing during their hospital assistantship., Methods: A standard operating procedure (SOP) for medical student transcribing was implemented by the teaching hospitals associated with a single medical school. This included medical student prescriptions being written in purple ink. The evaluation consisted of an audit of transcribing activity and a student survey. We evaluated the usage of the initiative, adherence to the SOP and the propensity for error., Results: The survey was completed by 38 out of a possible 108 fifth-year students. All respondents agreed that the programme was helpful in aiding them to learn about prescribing. A total of 247 prescriptions for 50 patients were audited: 25.1% of the prescriptions written by students required some form of amendment by the supervising doctor or pharmacist; three (1.2%) prescription errors remained unidentified; and none presented a patient safety risk., Conclusions: The purple-pen scheme affords medical students the opportunity to prescribe in the workplace, where they face authentic challenges when safely contributing to patient care. The identification of prescribing errors, feedback and the learners' own reflections helped the learners to focus on areas for improvement in prescribing prior to qualification., (© 2019 John Wiley & Sons Ltd and The Association for the Study of Medical Education.)

Aims: To assess whether hospitalization may assist in correcting errors in anticoagulant therapy among patients with atrial fibrillation (AF)., Methods: Our cohort included patients admitted to our institution with a history of AF between 2016 and 2018. We categorized patient's treatment upon admission and discharge as lacking (no treatment despite indication), inadequate (according to individual characteristics) or adequate. We assessed adequacy of treatment upon discharge and determined factors associated with correcting admission errors., Results: Of 4427 patients admitted with a history of AF, the categorization to lacking, inadequate and adequate treatment was 1746 (39.4%), 1237 (27.9%) and 1444 (32.6%) patients, respectively. Of those with inadequate treatment, the most common types of errors were direct oral anticoagulant (DOAC) underdosing (n = 578; 46.7%), vitamin-K antagonists when DOAC was indicated (n = 258; 20.9%), DOAC despite contraindication to DOAC (n = 166; 13.4%) and DOAC overdosing (n = 124; 10%). Upon discharge 688 (18.6%, out of n = 3694) corrections but also 316 (8.6%) new mistakes were found. On multivariate logistic regression, the factors associated with correction of an error on admission were hospitalization due to AF (odds ratio [OR] 2.94 [2.39-3.61]), hospitalization in the neurologic or geriatric wards (OR 2.79 [2.04-3.80]), female sex (OR 1.34 [1.10-1.63]) and a history of stroke (OR 1.47 [1.17-1.86]), while the presence of a contraindication to DOAC decreased the chance of correction (OR 0.10 [0.06-0.18])., Conclusion: Hospitalization for any reason may contribute to correction of errors in AC treatment in patients with AF. Unfortunately, a significant portion of patients remains inadequately treated by both outpatient and inpatient providers., (© 2019 The British Pharmacological Society.)

We describe an ongoing quality improvement project focusing on paediatric prescribing and medication safety for medical, surgical and oncology patients in a district general hospital. The project is called STAMP-Safe Treatment and Administration of Medicine in Paediatrics. The project has been running continuously for 24 months. No one factor has been identified to sustain a reduction in prescribing error rates. However, we have improved the quality and frequency of feedback to prescribers following errors. We believe that this ongoing project is changing the local prescribing culture, and with further Plan-Do-Study-Act cycles we hope to see improvement in prescribing error rates., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: The scope of selected emergency physiotherapy practitioners (EPP) in this Australian non-tertiary ED has recently extended to include the prescription of a limited drug formulary, including paracetamol, some NSAIDs and opioids, an anti-emetic, a benzodiazepine and nitrous oxide. Although there are large-scale studies investigating prescription errors made by doctors, there is a lack of data on prescribing practices of physiotherapists in the ED setting. The aim of present study is to compare the prescribing practices of EPP to their medical and nursing colleagues within the setting of treating musculoskeletal injuries in the ED., Methods: One hundred retrospective National Inpatient Medication Chart (NIMC) audits of adult patients presenting primarily with musculoskeletal complaints were undertaken using the standardised NIMC audit tool, with patient demographics, and NIMC audit results compared between groups., Results: Fifty medication charts were audited for each group, with a total of 212 drug orders. EPP demonstrated higher completion rates for patient identification, patient weight and medication history compared to medical and nursing staff. Legibility of drug names and route of administration appeared equivalent, whereas EPP had higher completion rates for legible drug doses and signatures compared to medical and nursing staff., Conclusion: In the management of ED patients with musculoskeletal complaints, prescription-trained EPP appear to perform similarly if not better than their medical and nursing colleagues with regards to NIMC audit tool results., (© 2019 Australasian College for Emergency Medicine.)

Objective: To explore the factors contributing to prescribing error in paediatric intensive care units (PICUs) using a human factors approach based on Reason's theory of error causation to support planning of interventions to mitigate slips and lapses, rules-based mistakes and knowledge-based mistakes., Methods: A hierarchical task analysis (HTA) of prescribing was conducted using documentary analysis. Eleven semistructured interviews with prescribers were conducted using vignettes and were analysed using template analysis. Contributory factors were identified through the interviews and were related to tasks in the HTA by an expert panel involving a PICU clinician, nurse and pharmacist., Results: Prescribing in PICU is composed of 30 subtasks. Our findings indicate that cognitive burden was the main contributory factor of prescribing error. This manifested in two ways: physical, associated with fatigue, distraction and interruption, and poor information transfer; and psychological, related to inexperience, changing workload and insufficient decision support information. Physical burden was associated with errors of omission or selection; psychological burden was linked to errors related to a lack of knowledge and/or awareness. Social control through nursing staff was the only identified control step. This control was dysfunctional at times as nurses were part of an informal mechanism to support decision making, was ineffective., Conclusions: Cognitive burden on prescribers is the principal latent factor contributing to prescribing error. This research suggests that interventions relating to skill mix, and communication and presentation of information may be effective at mitigating rule and knowledge-based mistakes. Mitigating fatigue and standardising procedures may minimise slips and lapses., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To assess the proportion of all medication error reports in hospitals and primary care that involved an anticoagulant. Secondary objectives were the anticoagulant involved, phase of the medication process in which the error occurred, causes and consequences of 1000 anticoagulant medication errors. Additional secondary objectives were the total number of anticoagulant medication error reports per month, divided by the total number of medication error reports per month and the proportion of causes of 1000 anticoagulant medication errors (comparing the pre- and post-guideline phase)., Design: A cross-sectional study., Setting: Medication errors reported to the Central Medication incidents Registration reporting system., Participants: Between December 2012 and May 2015, 42 962 medication errors were reported to the CMR., Intervention: N/A., Main Outcome Measure: Proportion of all medication error reports that involved an anticoagulant. Phase of the medication process in which the error occurred, causes and consequences of 1000 anticoagulant medication errors. The total number of anticoagulant medication error reports per month, divided by the total number of medication error reports per month (comparing the pre- and post-guideline phase) and the total number of causes of 1000 anticoagulant medication errors before and after introduction of the LSKA 2.0 guideline., Results: Anticoagulants were involved in 8.3% of the medication error reports. A random selection of 1000 anticoagulant medication error reports revealed that low-molecular weight heparins were most often involved in the error reports (56.2%). Most reports concerned the prescribing phase of the medication process (37.1%) and human factors were the leading cause of medication errors mentioned in the reports (53.4%). Publication of the national guideline on integrated antithrombotic care had no effect on the proportion of anticoagulant medication error reports. Human factors were the leading cause of medication errors before and after publication of the guideline., Conclusions: Anticoagulant medication errors occurred in 8.3% of all medication errors. Most error reports concerned the prescribing phase of the medication process. Leading cause was human factors. The publication of the guideline had no effect on the proportion of anticoagulant medication errors., (© The Author(s) 2018. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Medication-related errors are among the most common medical errors, and studies have shown that the paediatric population is particularly vulnerable. Errors can occur during any step in the medication process. This review article seeks to highlight new advancements in the field of paediatric medication safety at each stage of the medication process, from ordering and transcribing to medication dispensing and administration. We will focus on interventions that are increasingly widely used, such as computerised provider order entry with clinical decision support, barcoding technologies and safe medication administration through technologies pumps (SMART pumps), as well as innovative mobile application devices and workflow management systems that are being piloted at single institutions. By highlighting what is new in paediatric medication safety, as well as the gaps that remain, we hope to continue to foster focus on this critically important area in order to create the safest possible environment for children., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The success of interprofessional collaboration in healthcare services requires a paradigm shift in the training of future health profession practitioners. This study aimed to develop and validate an instrument to measure Student Acceptance of Interprofessional Learning (SAIL) in Malaysia, and to assess this attribute among medical and pharmacy students using a prescribing skills training workshop., Methods: The study consisted of two phases. In Phase 1, a 10-item instrument (SAIL-10) was developed and tested on a cohort of medical and pharmacy students who attended the workshop. In Phase 2, different cohorts of medical and pharmacy students completed SAIL-10 before and after participating in the workshop., Results: Factor analysis showed that SAIL-10 has two domains: "facilitators of interprofessional learning" and "acceptance to learning in groups". The overall SAIL-10 and the two domains have adequate internal consistency and stable reliability. The total score and scores for the two domains were significantly higher after students attended the prescribing skills workshop., Conclusions: This study produced a valid and reliable instrument, SAIL-10 which was used to demonstrate that the prescribing skills workshop, where medical and pharmacy students were placed in an authentic context, was a promising activity to promote interprofessional learning among future healthcare professionals.

Introduction: Order validation is an important component of pharmacy services, where pharmacists review orders with a focus on error prevention. Interruptions are frequent and may contribute to a reduction in error detection, thus potential medication errors. However, studying such errors in practice is difficult. Simulation has potential to study these events., Methods: This was a pilot, simulation study. The primary objective was to determine the rate of medication error detection and the effect of interruptions on error detection during simulated validation. Secondary objectives included determining time to complete each prescription page. The scenario consisted of validating three handwritten medication order pages containing 12 orders and 17 errors, interrupted by three phone calls timed during one order for each page. Participants were categorized in groups: seniors and juniors (including residents). Simulation sessions were videotaped and eye tracking was used to assist in analysis., Results: Eight senior and five junior pharmacists were included in the analysis. There was a significant association between interruption and error detection (odds ratio = 0.149, 95% confidence interval = 0.042-0.525, P = 0.005). This association did not vary significantly between groups (P = 0.832). Juniors took more time to validate the first page (10 minutes 56 seconds vs. 6 minutes 42 seconds) but detected more errors (95% vs. 69%). However, all major errors were detected by all participants., Conclusions: We observed an association between phone interruptions and a decrease in error detection during simulated validation. Simulation provides an opportunity to study order validation by pharmacists and may be a valuable teaching tool for pharmacists and pharmacy residents learning order validation.

Rationale, Aims and Objectives: Implementation of robotic systems in outpatient hospital pharmacies is uncommon. Other than cost, 1 of the barriers to widespread adoption is the lack of definitive evidence that this technology actually reduces dispensing errors and improves inventory management., Objective: To identify the frequency of medication dispensing errors before and after the implementation of a robotic original pack dispensing system in an outpatient hospital pharmacy and to analyse the impact of this system on the quality of stock management and staff satisfaction., Methods: A prospective before-and-after medication error study was performed using a disguised observation technique. Several indicators of stock management and staff satisfaction were monitored. Drugs were dispensed manually by technicians using a barcode-controlled system (preimplementation phase) or the dispensing robot ROWA Vmax (ARX) (postimplementation phase). As not all drugs could be handled by the robot, residual manual dispensing was also used., Results: The dispensing error rate was reduced from 1.31% of prescriptions (43/3284) to 0.63% (19/3004) (relative risk reduction [RRR], 51.7%; 95% CI, 17.3% to 71.8%). The error rate decreased up to 0.12% (3/2496) (RRR, 90.8%; 95% CI, 70.4% to 97.1%) if errors during residual manual dispensing were excluded. The stock-out ratio was reduced from 0.85% to 0.17% (RRR, 80.5%; 95% CI, 49.5% to 92.5%). Daily staff time (median) in stock management was reduced by 59.3% (from 1 hour 36 minutes to 39 minutes). High level of staff satisfaction with this technology was achieved, although it was slightly higher in the group of pharmacists compared to technicians (8.63 ± 0.7 vs 7.78 ± 0.7, P = .046)., Conclusion: The implementation of a robotic original pack dispensing system substantially decreased the rate of dispensing errors and optimized stock management. Minimizing the number of drugs out of the dispensing robot is critical when attempting to maximize the benefits of its implementation., (© 2018 John Wiley & Sons, Ltd.)

Background The computerization of prescriptions with a computerized physician order entry contributes to securing the error-free drug supply, but is not risk-free. Objective: To determine the impact of a computerized physician order entry system on prescribing errors immediately after its implementation and 1 year later. Setting The Cardiology and Diabetology Departments at Toulouse University Hospital, France. Method The prescriptions were analysed by pharmacists over three 30-day periods for 3 consecutive years (N: computerization period, N - 1, N + 1). For each identified error, the prescriber was informed by a pharmaceutical intervention. The pharmaceutical interventions were counted and arranged according to the classification by the French Society of Clinical Pharmacy. Their average numbers and clinical impacts were compared for each period using t-tests and Kruskal-Wallis tests. Main outcome measure The average numbers of pharmaceutical interventions. Results In total, 12.1 pharmaceutical interventions per 100 patient days were done during the N - 1 period, 14.1 during N and 9.6 during N + 1. Among those, 3.6 (N) and 2.1 (N + 1) were related to the computerization itself, and 10.5 (N) and 7.5 (N + 1) were not. The average number of computerization-related pharmaceutical interventions significantly decreased from N to N + 1 (p = 0.04). The average number of classic interventions decreased from N - 1 to N + 1 (p = 0.02). The clinical impacts of the computerization related errors were similar to those of other errors. Conclusion The implementation of the computerized physician order entry induced the appearance of specific computerized-related errors, but the number of classic errors decreased. The entry-system related errors were not more severe than other errors, and the number decreased after 1 year.

Background: There has been an increasing need to examine undergraduate dental education in prescribing to confirm whether it is establishing the goal of producing safe and rational prescribers. Prescribing by dental doctors after graduation is influenced by a variety of factors: the different teaching approaches of the professors at the clinics and in the pharmacology course, fellow colleagues and even the information provided by the pharmaceutical industry., Objective: The aim of this study was to assess the prescription knowledge, attitude, preference and common errors made by junior resident dental doctors in the dental department of two medical colleges and hospitals in India., Methods: Dental graduates (n = 70) who served as junior resident doctors at dental departments and graduated from various dental colleges in India, participated in the study. A survey was conducted among 70 junior resident dental doctors in the dental department, applying a previously validated questionnaire consisting of open-ended questions. The knowledge, attitude and practice preference of resident doctors regarding drug prescription and common errors made by them were analyzed and reviewed., Results: The most frequent response to each question was considered the most significant. The most common reason for prescribing medication was infection (n = 33, 47.14%) and the most widely prescribed antibiotic was amoxicillin (n = 29, 41.42%). The most frequent error reported by resident doctors was lack of knowledge about drug posology (n = 31, 44.28%). Maximum number of junior doctors acquired the information for prescribing drugs from their faculty (n = 33, 47.14%). Around 45.71% dental doctors had no knowledge about the WHO Guide to Good Prescribing. About 50- 60% doctors had knowledge about the dose, frequency, duration and route of administration of the drug prescribed. While prescribing drugs to the patient, 25.71% doctors explain the disease and treatment properly to the patient; 24.28% doctors do not criticize other doctors, and 10% doctors address the patient by name., Conclusion: The results of this study indicate that resident dental doctors' knowledge, attitudes and behavior about the drug prescription need to be improved. More studies are needed to determine whether this issue affects the quality of patient care and the effectiveness and safety of treatments.

Objective: Junior doctors have the highest rates of prescribing errors, yet no study has set out to understand the differences between completely novice prescribers (Foundation year one (FY1) doctors) and those who have gained some experience (Foundation year two (FY2) doctors). The objective of this study was to uncover the causes of prescribing errors made by FY2 doctors and compare them with previously collected data of the causes of errors made by FY1 doctors., Design: Qualitative interviews, using the critical incident technique, conducted with 19 FY2 doctors on the causes of their prescribing errors and compared with interviews previously conducted with 30 FY1 doctors. Data were analysed using a constant comparison approach after categorisation of the data using Reason's model of accident causation and the London protocol., Results: Common contributory factors in both FY1 and FY2 doctors' prescribing errors included working on call, tiredness and complex patients. Yet, important differences were revealed in terms of application of prescribing knowledge, with FY1 doctors lacking knowledge and FY2 misplacing their knowledge. Due to the rotation of foundation doctors, both groups are faced with novel prescribing contexts, yet the previous experience that FY2 doctors gained led to misplaced confidence when caution would have been expedient., Conclusions: Differences in the contributory factors of prescribing errors should be taken into account when designing interventions to improve the prescribing of foundation doctors. Furthermore, careful consideration should be taken when inferring expertise in FY2 doctors, who are likely to prescribe in contexts in which their experience is little different to an FY1 doctor., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Results of a study to estimate the prevalence of look-alike/sound-alike (LASA) medication errors through analysis of Veterans Affairs (VA) administrative data are reported., Methods: Veterans with at least 2 filled prescriptions for 1 medication in 20 LASA drug pairs during the period April 2014-March 2015 and no history of use of both medications in the preceding 6 months were identified. First occurrences of potential LASA errors were identified by analyzing dispensing patterns and documented diagnoses. For 7 LASA drug pairs, potential errors were evaluated via chart review to determine if an actual error occurred., Results: Among LASA drug pairs with overlapping indications, the pairs associated with the highest potential-error rates, by percentage of treated patients, were tamsulosin and terazosin (3.05%), glipizide and glyburide (2.91%), extended- and sustained-release formulations of bupropion (1.53%), and metoprolol tartrate and metoprolol succinate (1.48%). Among pairs with distinct indications, the pairs associated with the highest potential-error rates were tramadol and trazodone (2.20%) and bupropion and buspirone (1.31%). For LASA drug pairs found to be associated with actual errors, the estimated error rates were as follows: lamivudine and lamotrigine, 0.003% (95% confidence interval [CI], 0-0.01%); carbamazepine and oxcarbazepine, 0.03% (95% CI, 0-0.09%); and morphine and hydromorphone, 0.02% (95% CI, 0-0.05%)., Conclusion: Through the use of administrative databases, potential LASA errors that could be reviewed for an actual error via chart review were identified. While a high rate of potential LASA errors was detected, the number of actual errors identified was low., Competing Interests: DisclosuresThe authors have declared no potential conflicts of interest., (Copyright © 2018 by the American Society of Health-System Pharmacists, Inc. All rights reserved.)

Competing Interests: DisclosuresThe authors have declared no potential conflicts of interest. These guidelines supersede the ASHP guidelines on preventing medication errors dated June 23, 1993.

Background: To evaluate the effectiveness of a structured prescription review and prescriber feedback program in reducing prescribing errors in government primary care clinics within an administrative region in Malaysia., Methods: This was a three group, pragmatic, cluster randomised trial. In phase 1, we randomised 51 clinics to a full intervention group (prescription review and league tables plus authorised feedback letter), a partial intervention group (prescription review and league tables), and a control group (prescription review only). Prescribers in these clinics were the target of our intervention. Prescription reviews were performed by pharmacists; 20 handwritten prescriptions per prescriber were consecutively screened on a random day each month, and errors identified were recorded in a standardised data collection form. Prescribing performance feedback was conducted at the completion of each prescription review cycle. League tables benchmark prescribing errors across clinics and individual prescribers, while the authorised feedback letter detailed prescribing performance based on a rating scale. In phase 2, all clinics received the full intervention. Pharmacists were trained on data collection, and all data were audited by researchers as an implementation fidelity strategy. The primary outcome, percentage of prescriptions with at least one error, was displayed in p-charts to enable group comparison., Results: A total of 32,200 prescriptions were reviewed. In the full intervention group, error reduction occurred gradually and was sustained throughout the 8-month study period. The process mean error rate of 40.7% (95% CI 27.4, 29.5%) in phase 1 reduced to 28.4% (95% CI 27.4, 29.5%) in phase 2. In the partial intervention group, error reduction was not well sustained and showed a seasonal pattern with larger process variability. The phase 1 error rate averaging 57.9% (95% CI 56.5, 59.3%) reduced to 44.8% (95% CI 43.3, 46.4%) in phase 2. There was no evidence of improvement in the control group, with phase 1 and phase 2 error rates averaging 41.1% (95% CI 39.6, 42.6%) and 39.3% (95% CI 37.8, 40.9%) respectively., Conclusions: The rate of prescribing errors in primary care settings is high, and routine prescriber feedback comprising league tables and a feedback letter can effectively reduce prescribing errors., Trial Registration: National Medical Research Register: NMRR-12-108-11,289 (5th March 2012).

Objective: Lack of awareness of the risks associated with the use of medical  gases amongst health professionals and health organizations is concerning. The  objective of this study is to redefine the use process of medical gases in a  hospital setting., Method: A sentinel event took place in a clinical unit, the incorrect administration of a medical gas to an inpatient. A multidisciplinary  causeroot analysis of the sentinel event was carried out. Different improvement points were identified for each error detected and so we defined a  good strategy to ensure the safe use of these drugs., Results: 9 errors were identified and the following improvement actions were  defined: storage (gases of clinical use were separated from those of industrial  use and proper identification signs were placed), prescription (6 protocols were  included in the hospital´s Computerized Physician Order Entry software),  validation (pharmacist validation of the prescription to ensure appropriate use of  these), dispensation (a new protocol for medical gases dispensation and  transportation was designed and implemented) and administration (information  on the pressure gauges used for each type of gas was collected and reviewed).  72 Signs with recommendations for medical gases identification and  administration were placed in all the clinical units. Specific training on the safe  use of medical gases and general safety training was imparted., Conclusions: The implementation of a process that integrates all phases of use  of medical gases and applies to all professionals involved is presented here as a  strategy to increase safety in the use of these medicines., (Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.)

Introduction: To prevent errors, health care professional and safety organizations recommend using milliliters (mL) alone for oral liquid medication dosing instructions and devices. In 2018, for federal incentives under the Quality Payment Program, one requirement is for electronic health records to automatically use mL alone whenever oral liquid medications are prescribed. Current perceptions and practices of primary care providers (PCPs) regarding dosing units for oral liquid medications were assessed., Methods: Pediatricians, family practitioners, nurse practitioners, and internists participating in the 2015 DocStyles Web-based survey were asked about their perceptions and practices regarding dosing units for oral liquid medications., Results: Three fifths of PCPs (59.0%) reported that using mL alone is safest for dosing oral liquid medications; however, nearly three quarters (72.0%) thought that patients/caregivers prefer instructions that include spoon-based units. Within each specialty, fewer PCPs reported they would prescribe using mL alone than reported that using mL alone is safest (P < .0001 for all). Among PCPs who think milliliter-only dosing is safest, those who perceived patients/caregivers prefer including spoon-based units were less likely to prescribe using mL alone (odds ratio 0.45, 95% confidence interval 0.34-0.59). Pediatricians were more likely than other PCPs to report that it is safest to use mL alone (80.8% vs 54.7%) and that they would use mL alone when prescribing (56.8% vs 30.9%) (P < .0001 for both)., Conclusions: Because less than two thirds of pediatricians and one third of other PCPs would use mL alone in dosing instructions, additional education to encourage prescribing and communicating with patients/caregivers using mL alone may be needed., (Published by Elsevier Inc.)

Although chemotherapy is a well established treatment modality, chemotherapy errors represent a potentially serious risk of patient harm. We reviewed published research from 1980 to 2017 to understand the extent and nature of medication errors in cancer chemotherapy, and to identify effective interventions to help prevent mistakes. Chemotherapy errors occur at a rate of about one to four per 1000 orders, affect at least 1-3% of adult and paediatric oncology patients, and occur at all stages of the medication use process. Oral chemotherapy use is a particular area of growing risk. Our knowledge of chemotherapy errors is drawn primarily from single-institution studies at university hospitals and referral centres, with a particular focus on prescription orders and pharmacy practices. Although the heterogeneity of research methods and measures used in these studies limits our understanding of this issue, the rate of chemotherapy error-related injuries is generally lower than those seen in comparable studies of general medical patients. Although many interventions show promise in reducing chemotherapy errors, most have little empirical support. Additional research is needed to understand and to mitigate the risk of chemotherapy medication errors., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objective: To analyze the results of sentinel patient program to monitoring the  quality pharmacoterapeutic process in the hospitalized patient through  medication errors., Method: Design: Observational, prospective and transversal study. Ambit: General hospital of 1,000 beds., Period: From May 2011 to June 2016.  Sample: Patients with treatment prescribe within 24 hours of being admitted  with 4 or more medications., Variables: Medication error, drugs prescribed,  medications and doses dispensing, drugs administered. Safety indicators were  defined based on medication errors at each stage of the pharmacotherapeutic  process., Results: Of the 746 patients studied, 334 had at least 1 medication error  (44.8%; IC95%: 41.7-47.8). In the 746 treatments, 564 medication errors were  detected (0.75 errors by patient; IC95%: 0.7-0.8). The safety indicators  (medication error by stage) were: 5.1% (38/746 patients) for omission of  allergy record; 2.3% (156/6 724 drugs) for prescription; 0.6% (38/6 724 drugs)  for validation, 2.6% for dispensing (142/5 465 drugs) y 3.7% (190/5  111 administered drugs observed) for administration. The temporal evolution of  the indicators, with graphs of statistical control showed stable processes, except  for the administration. The proposed improvement actions were of a training,  standardization and organizational type., Conclusions: The sentinel patient program provides an overview of the quality  of the pharmacotherapeutic process and promotes the safety culture at the  center. Statistical control charts have been a useful tool for monitoring  medication errors. The analysis of medication errors has served to propose  improvement actions in each stage of the pharmacotherapeutic process., (Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.)

Prescriptions comprising multi-drug therapy mostly illustrate the prescribing error. The phenomenon of error is bonded with human inaccuracy. The erroneous practice is observed in under developed countries like Pakistan, Bangladesh and also in developed ones. Consequently drug-drug interaction is one of the most common error associated with potentially serious adverse response even death. Accordingly the present study was conducted to assess the prevalence of prescribing errors and drug-drug interactions in out-patients receiving angiotensin receptor blockers. The study was done with population size one hundred fifty prescriptions obtained from different out-patient settings in Karachi. The prescriptions were screened for prescribing errors and risk factors for drug-drug interactions. Drug-drug interactions were recognized by Micromedex.2.0.Drug-Reax®database. The most common type of error was omission error. These errors were patient's age, weight and diagnosis found in 51.3%, 97.3% and 74% of prescriptions, respectively. The prevalence of drug-drug interaction was 38%. A total of 746 drugs were prescribed with an average of 5 drugs per prescription and 450 medication errors were detected. Majority of the interaction were moderate (19.33%), others were minor (14%) and major (6%) in severity. Patients who prescribed many drugs (more than 5 drugs in a while) had a higher risk of developing drug-drug interactions (OR=4.76; 95% CI=2.30-9.64; p=0.0001*).The study data reports the occurrence of prescribing errors in Karachi and also necessitate the need of clinical pharmacist's services in health care system. The step will help to minimize the risk factors by having the drug prescriptions reviewed by the pharmacists.

Objective: The aim of this study was to investigate the completeness and legibility of prescriptions dispensed in community pharmacies located in Sana'a, Yemen., Materials and Methods: A cross-sectional study was conducted at 23 randomly selected community pharmacies throughout the capital city of Sana'a, Yemen, from May 2015 to January 2016. A total of 2,178 prescriptions were analyzed for the essential elements of a complete prescription using a validated checklist., Results: Of the 2,178 prescriptions, 19 (0.87%) were considered to be of good quality. The remaining 2,159 (99.12%) were considered as being of very poor quality. Writing errors relating to patients and prescribed medications were the most common errors., Conclusion: In this study, the quality of prescription writing was found to be very poor. Hence, continuous professional development programs are recommended to improve the quality of prescription writing among physicians. Future studies in other cities and investigation of the impact of continuous educational programs on the quality of prescription writing are strongly recommended., (© 2018 The Author(s) Published by S. Karger AG, Basel.)

Purpose: The study aimed to test the hypothesis that hospital electronic prescribing and medicine administration system (HEPMA) implementation impacted patient discharge letter quality, nature and frequency of prescribing errors., Method: A quasi experimental before and after retrospective case note review was conducted in one United Kingdom district general hospital. The total sample size was 318 (random samples of 159 before and after implementation), calculated to achieve a 10% error reduction with a power of 80% and p < 0.05. Adult patients discharged after ≥24-h inpatient stay were assessed for discharge information documentation quality using a modified validated discharge document template. Prescribing errors were classified as medicine omissions, commissions, incorrect dose/frequency/duration, drug interactions, therapeutic duplications or missing/inaccurate allergy information. Post-implementation assessments were undertaken 4 months following HEPMA implementation. Error severity was determined by a multidisciplinary panel consensus using the Medications at Transitions and Clinical Handoffs (MATCH) study validated scoring system., Results: There were no statistically significant differences in patient demographics between the pre- and post-implementation groups. Discharge information documentation quality improved; allergy documentation increased from 11 to 159/159 (p < 0.0001). The number of patients with prescribing errors reduced significantly from 158 to 37/159 (p < 0.001). Prescribing error category incidence identified in pre-implementation patients was reduced (e.g. omission incidence from 66 to 18/159 (p < 0.001)), although a new error type (sociotechnical [errors caused by the system]) was identified post-implementation (n = 8 patients). Post-implementation prescribing errors severity rating identified 8/37 as likely to cause potential patient harm., Conclusion: HEPMA implementation was associated with improved discharge documentation quality, statistically significant prescribing error reduction and prescribing error type alteration. There remains a need to be alert for potential prescribing errors.

Background Prescribing errors are prevalent in hospital settings with feedback identified as one potential error reduction strategy. Hospital pharmacists work alongside prescribers at ward level and are credible facilitators of prescribing error feedback. A formalised programme of pharmacist-led prescribing error feedback was designed and implemented Objective To determine the impact of the feedback intervention on prescribing error rates. Method Prospective prescribing audits were undertaken at baseline for control (n = 11) and intervention group (n = 10) prescribers. The intervention group received pharmacist-led, individualised constructive feedback on their prescribing, whilst the control group continued with existing practice. Prescribing was re-audited following 3-months of the intervention. Data were analysed using chi-squared and independent t-tests. Results Error frequency (123/641 intervention and 121/649 control) was comparable between groups at baseline (p = 0.819) with significant differences (90/1677 intervention and 236/984 control) post intervention (p = <0.005). Prescribing error rates were lower in the intervention group (mean change of -11.5%) and higher in the control group (mean change of +5.9%) following the intervention, with a mean significant difference of 17.4% (SD 4.7, 95% CI, -27.3 to -7.6), t = -3.694, p < 0.05, between groups. Conclusion Pharmacist-led prescribing error feedback positively influences prescribing. This intervention shows promise for wider application in hospital settings to optimise patient safety.

Background: Whereas one of the predominant causes of medication errors is a drug administration error, a previous study related to our investigations and reviews estimated that the incidences of medication errors constituted 6.7 out of 100 administrated medication doses. Therefore, we aimed by using six sigma approach to propose a way that reduces these errors to become less than 1 out of 100 administrated medication doses by improving healthcare professional education and clearer handwritten prescriptions., Methods: The study was held in a General Government Hospital. First, we systematically studied the current medication use process. Second, we used six sigma approach by utilizing the five-step DMAIC process (Define, Measure, Analyze, Implement, Control) to find out the real reasons behind such errors. This was to figure out a useful solution to avoid medication error incidences in daily healthcare professional practice. Data sheet was used in Data tool and Pareto diagrams were used in Analyzing tool., Results: In our investigation, we reached out the real cause behind administrated medication errors. As Pareto diagrams used in our study showed that the fault percentage in administrated phase was 24.8%, while the percentage of errors related to prescribing phase was 42.8%, 1.7 folds. This means that the mistakes in prescribing phase, especially because of the poor handwritten prescriptions whose percentage in this phase was 17.6%, are responsible for the consequent) mistakes in this treatment process later on. Therefore, we proposed in this study an effective low cost strategy based on the behavior of healthcare workers as Guideline Recommendations to be followed by the physicians. This method can be a prior caution to decrease errors in prescribing phase which may lead to decrease the administrated medication error incidences to less than 1%., Conclusion: This improvement way of behavior can be efficient to improve hand written prescriptions and decrease the consequent errors related to administrated medication doses to less than the global standard; as a result, it enhances patient safety. However, we hope other studies will be made later in hospitals to practically evaluate how much effective our proposed systematic strategy really is in comparison with other suggested remedies in this field.

Background: Prescribing error may result in adverse clinical outcomes leading to increased patient morbidity, mortality and increased economic burden. Many errors occur during transitional care as patients move between different stages and settings of care., Aim: To conduct a review of medication information and identify prescribing error among an adult population in an urban hospital., Methods: Retrospective review of medication information was conducted. Part 1: an audit of discharge prescriptions which assessed: legibility, compliance with legal requirements, therapeutic errors (strength, dose and frequency) and drug interactions. Part 2: A review of all sources of medication information (namely pre-admission medication list, drug Kardex, discharge prescription, discharge letter) for 15 inpatients to identify unintentional prescription discrepancies, defined as: "undocumented and/or unjustified medication alteration" throughout the hospital stay., Results: Part 1: of the 5910 prescribed items; 53 (0.9%) were deemed illegible. Of the controlled drug prescriptions 11.1% (n = 167) met all the legal requirements. Therapeutic errors occurred in 41% of prescriptions (n = 479) More than 1 in 5 patients (21.9%) received a prescription containing a drug interaction. Part 2: 175 discrepancies were identified across all sources of medication information; of which 78 were deemed unintentional. Of these: 10.2% (n = 8) occurred at the point of admission, whereby 76.9% (n = 60) occurred at the point of discharge., Conclusions: The study identified the time of discharge as a point at which prescribing errors are likely to occur. This has implications for patient safety and provider work load in both primary and secondary care.

Background Errors in discharge prescriptions are problematic. When hospital pharmacists write discharge prescriptions improvements are seen in the quality and efficiency of discharge. There is limited information on the incidence of errors in pharmacists' medication orders. Objective To investigate the extent and clinical significance of errors in pharmacist-written discharge medication orders. Setting 1000-bed teaching hospital in London, UK. Method Pharmacists in this London hospital routinely write discharge medication orders as part of the clinical pharmacy service. Convenient days, based on researcher availability, between October 2013 and January 2014 were selected. Pre-registration pharmacists reviewed all discharge medication orders written by pharmacists on these days and identified discrepancies between the medication history, inpatient chart, patient records and discharge summary. A senior clinical pharmacist confirmed the presence of an error. Each error was assigned a potential clinical significance rating (based on the NCCMERP scale) by a physician and an independent senior clinical pharmacist, working separately. Main outcome measure Incidence of errors in pharmacist-written discharge medication orders. Results 509 prescriptions, written by 51 pharmacists, containing 4258 discharge medication orders were assessed (8.4 orders per prescription). Ten prescriptions (2%), contained a total of ten erroneous orders (order error rate-0.2%). The pharmacist considered that one error had the potential to cause temporary harm (0.02% of all orders). The physician did not rate any of the errors with the potential to cause harm. Conclusion The incidence of errors in pharmacists' discharge medication orders was low. The quality, safety and policy implications of pharmacists routinely writing discharge medication orders should be further explored.

Introduction: Medication errors are common, with studies reporting at least one error per patient encounter. At hospital discharge, medication errors vary from 15%-38%. However, studies assessing the effect of an internally developed electronic (E)-prescription system at discharge from an emergency department (ED) are comparatively minimal. Additionally, commercially available electronic solutions are cost-prohibitive in many resource-limited settings. We assessed the impact of introducing an internally developed, low-cost E-prescription system, with a list of commonly prescribed medications, on prescription error rates at discharge from the ED, compared to handwritten prescriptions., Methods: We conducted a pre- and post-intervention study comparing error rates in a randomly selected sample of discharge prescriptions (handwritten versus electronic) five months pre and four months post the introduction of the E-prescription. The internally developed, E-prescription system included a list of 166 commonly prescribed medications with the generic name, strength, dose, frequency and duration. We included a total of 2,883 prescriptions in this study: 1,475 in the pre-intervention phase were handwritten (HW) and 1,408 in the post-intervention phase were electronic. We calculated rates of 14 different errors and compared them between the pre- and post-intervention period., Results: Overall, E-prescriptions included fewer prescription errors as compared to HW-prescriptions. Specifically, E-prescriptions reduced missing dose (11.3% to 4.3%, p <0.0001), missing frequency (3.5% to 2.2%, p=0.04), missing strength errors (32.4% to 10.2%, p <0.0001) and legibility (0.7% to 0.2%, p=0.005). E-prescriptions, however, were associated with a significant increase in duplication errors, specifically with home medication (1.7% to 3%, p=0.02)., Conclusion: A basic, internally developed E-prescription system, featuring commonly used medications, effectively reduced medication errors in a low-resource setting where the costs of sophisticated commercial electronic solutions are prohibitive., Competing Interests: Conflicts of Interest: By the WestJEM article submission agreement, all authors are required to disclose all affiliations, funding sources and financial or management relationships that could be perceived as potential sources of bias. No author has professional or financial relationships with any companies that are relevant to this study. There are no conflicts of interest or sources of funding to declare.

Objectives: To evaluate the nature and frequency of medication errors resulting from the use of a computerized provider order-entry (CPOE) system in a pediatric department., Methods: We conducted a retrospective study to examine errors related to computerized orders using the software Pharma ® (Computer Engineering, France) in pediatric department between 31/05/2015 to 01/12/2015. These errors were signaled by pharmacists who examine CPOEs daily., Results: A total of 302 pharmacist interventions (PharmInt) were carried out by clinical pharmacists during the study period. Of the 302 PharmInts, a total of 95 (31.5%) contained no data on the patient's bodyweight, which should have been provided by the prescriber (Table 1). After the PharmInt, information on bodyweight was then provided in 47 of these cases (15.6%). Incomplete information about administration frequency accounted for 19.9% of total PharmInts. Prescribing an excessive dose occurred in 17.6% of PharmInts, inappropriate modifications of prescription unit accounted for 9.9% of PharmInts, and incorrect dosage was prescribed in 8.3% of PharmInts. Of the 302 PharmInts, 255 concerned prescription errors and bodyweight missing not provided after PharmInt. Paracetamol, in its different forms (injectable, solid or liquid oral forms) accounted for 35.7% of total PharmInts. Noted errors for paracetamol included an incorrect dosage form, co-administration of two paracetamol-containing drugs, modification of the prescription unit, incorrect frequency of administrations, and absence of the patient's bodyweight. Inconsistent use of a contradicted or a non-used drug for pediatric patients was noted along with prescriptions for inadequate dosages., Discussion and Conclusion: Our work revealed several error types in prescribing for pediatric patients, mainly absence of bodyweight, incorrect frequency of administration and excessive doses. Information on bodyweight is crucial in pediatric patients: our study highlights the need to make it mandatory to complete prescriptions via CPOE systems. The role of better software design is pivotal to avoiding these errors. In addition to optimizing the quality of CPOE-entries, well-designed software, better-trained users, and improved communication among healthcare will reduce errors., (Copyright © 2017. Published by Elsevier B.V.)

Objectives: Transmucosal fentanyl is used to treat transient exacerbations of cancer pain. Several immediate release products are available, presented as intranasal sprays, sublingual and buccal tablets, or lozenges. These are not interchangeable, creating potential for medication errors. We compared the incidence of medication errors in a simulated scenario using handwritten drug charts and charts labelled with preprinted self-adhesive stickers with full pictorial fentanyl prescriptions., Methods: 54 nurses were shown 5 handwritten drug charts and 5 with self-adhesive pictorial labels. Nurses indicated which preparation and dose they would administer from boxes of Instanyl, Abstral, Effentora and Actiq (Nycomed, ProStrakan, Cephalon and Teva, respectively). We measured the frequency of drug administration errors and asked them to rate the prescriptions for clarity on four-point Likert items., Results: The use of pictorial self-adhesive prescriptions significantly reduced errors in choice of preparation, from 20 with traditional handwritten charts to 6 with self-adhesive labels (OR 3.52, 95% CI 1.39 to 8.90, p=0.006), but the incidence of dose error was not significantly different (OR 1.47, 95% CI 0.80 to 2.70, p=0.281). Analysis of Likert items showed using pictorial printed labels significantly improved nurses' understanding of choice of preparation, dose and maximum four hourly dose (p<0.0001, p=0.006 and p=0.028, respectively)., Conclusions: The use of pictorial prescribing appears to be a promising strategy that could reduce medication errors in choice of fentanyl preparations. There may be a wider use for pictorial prescribing where non-interchangeable preparations of the same drug exist., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Purpose: The variations in how drug names are displayed in computerized prescriber-order-entry (CPOE) systems were analyzed to determine their contribution to potential medication errors., Methods: A diverse set of 10 inpatient and outpatient CPOE system vendors and self-developed CPOE systems in 6 U.S. healthcare institutions was evaluated. A team of pharmacists, physicians, patient-safety experts, and informatics experts created a CPOE assessment tool to standardize the assessment of CPOE features across the systems studied. Hypothetical scenarios were conducted with test patients to study the medication ordering workflow and ways in which medications were displayed in each system. Brand versus generic drug name ordering was studied at 1 large outpatient system to understand why prescribers ordered both brand and generic forms of the same drug., Results: Widespread variations in the display of drug names were observed both within and across the 6 study sites and 10 systems, including the inconsistent display of brand and generic names. Some displayed drugs differently even on the same screen. Combination products were often displayed inconsistently, and some systems required prescribers to know the first drug listed in the combination in order for the correct product to appear in a search. It also appeared that prescribers may have prescribed both brand and generic forms of the same medication, creating the potential for drug duplication errors., Conclusion: A review of 10 CPOE systems revealed that medication names were displayed inconsistently, which can result in confusion or errors in reviewing, selecting, and ordering medications., (Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.)

Objectives: The purpose was to explore pharmacists' opinions regarding the impacts of electronic prescriptions (ePrescriptions) on medication safety in Finnish community pharmacies. Further objectives were to explore how often and what kinds of ambiguities or errors pharmacists have perceived in ePrescriptions., Method: A survey of randomly selected dispensers (n=1004) and pharmacists (n=228) was conducted in 2014., Results: Altogether 778 questionnaires were returned, yielding response rates of 64% (n=635) for dispensers and 65% (n=143) for pharmacists. The respondents felt that ePrescriptions improve medication safety in many areas: they lower the number of prescription forgeries, reduce the risk of dispensing errors, promote better management of the patient's overall medication, facilitate monitoring of duplicative therapy and drug interactions, and lessen the risk of incorrect interpretation of prescriptions. Many respondents (32%) reported that they had weekly found ambiguities or errors in ePrescriptions that required clarification during the dispensing process. Of the respondents, 18.6% had found such ambiguities or errors daily or almost daily. The three most common ambiguities or errors in ePrescriptions were incorrect total amount of medication (79.0%), missing notation of exceptional dosage instructions or exceptional purpose of use (SIC!) (69.0%), and unclear or incorrect dosage instructions (65.4%). Incorrect strength (14.9%) and incorrect pharmaceutical form (14.2%) were also commonly experienced problems., Conclusions: According to Finnish community pharmacists, the introduction of ePrescriptions has promoted medication safety in many areas. However, ambiguities and errors are common in ePrescriptions. Some of these can delay dispensing of the medicine, whereas others can cause serious risks to medication safety., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: The transfer of patients to and from the Intensive Care Unit (ICU) is prone to medication errors. The aim of the present study is to determine whether the number of medication errors at ICU admission and discharge and the associated potential harm and costs are reduced by using the Transfer ICU and Medication reconciliation (TIM) program., Methods: This prospective 8-month observational study with a pre- and post-design will assess the effects of the TIM program compared with usual care in two Dutch hospitals. Patients will be included if they are using at least one drug before hospital admission and will stay in the ICU for at least 24 h. They are excluded if they are transferred to another hospital, admitted and discharged in the same weekend or unable to communicate in Dutch or English. In the TIM program, a clinical pharmacist reconciles patient's medication history within 24 h after ICU admission, resulting in a "best possible" medication history and presents it to the ICU doctor. At ICU discharge the clinical pharmacist reconciles the prescribed ICU medication and the medication history with the ICU doctor, resulting in an ICU discharge medication list with medication prescription recommendations for the general ward doctor. Primary outcome measures are the proportions of patients with one or more medication transfer errors 24 h after ICU admission and 24 h after ICU discharge. Secondary outcome measures are the proportion of patients with potential adverse drug events, the severity of potential adverse drug events and the associated costs. For the primary outcome relative risks and 95% confidence intervals will be calculated., Discussion: Strengths of this study are the tailor-made design of the TIM program and two participating hospitals. This study also has some limitations: A potential selection bias since this program is not performed during the weekends, collecting of potential rather than actual adverse drug events and finally a relatively short study period. Nevertheless, the findings of this study will provide valuable information on a crucial safety intervention in the ICU., Trial Registration: Dutch trial register: NTR4159 , 5 September 2013.

Objective: To determine opioid-prescribing patterns and rate of three types of errors, discrepancies, and variation from ideal practice., Design: Retrospective review of opioid prescriptions processed at an outpatient pharmacy., Setting: Tertiary institutional medical center., Patients: We examined 510 consecutive opioid medication prescriptions for adult patients processed at an institutional outpatient pharmacy in June 2016 for patient, provider, and prescription characteristics., Main Outcome Measure(s): We analyzed prescriptions for deviation from best practice guidelines, lack of two patient identifiers, and noncompliance with Drug Enforcement Agency (DEA) rules., Results: Mean patient age (standard deviation) was 47.5 years (17.4). The most commonly prescribed opioid was oxycodone (71 percent), usually not combined with acetaminophen. Practitioners prescribed tablet formulation to 92 percent of the sample, averaging 57 (47) pills. We identified at least one error on 42 percent of prescriptions. Among all prescriptions, 9 percent deviated from best practice guidelines, 21 percent failed to include two patient identifiers and 41 percent were noncompliant with DEA rules. Errors occurred in 89 percent of handwritten prescriptions, 0 percent of electronic health record (EHR) computer-generated prescriptions, and 12 percent of non-EHR computer-generated prescriptions. Interrater reliability by κ was 0.993., Conclusions: Inconsistencies in opioid prescribing remain common. Handwritten prescriptions continue to demonstrate higher associations of errors, discrepancies, and variation from ideal practice and government regulations. All computer-generated prescriptions adhered to best practice guidelines and contained two patient identifiers, and all EHR prescriptions were fully compliant with DEA rules.

Background Computerized provider order entry (CPOE) has been developed and implemented within cancer center hospitals nationwide in Japan. To ensure that high-quality services are routinely provided by oncology pharmacists, this study was designed to evaluate the interventions through reviewing the orders that are generated by CPOE. Methods The objective of this retrospective chart review was to evaluate how pharmacists contributed to safe cancer treatment using paper-based pharmacy records. Data were collected from a total of 35,062 chemotherapy regimens for 18,515 outpatients between January and December 2013. Results Of these 35,062 chemotherapy regimens, the rate of pharmacists' interventions was 1.1% ( n = 408). Among them, 53.1% (217/408) of the chemotherapy prescriptions were modified due to pharmacist interventions. The reasons for interventions included "changes in the chemotherapy regimen were unclear" in 49.5%, "physicians' prescription errors" (22.0%), "pharmacist suggestions to improve chemotherapy" (15.1%), and "finding differences between physicians' chemotherapy records and their chemotherapy prescriptions" (13.2%). The top three reasons for the 217 prescription modifications due to pharmacist interventions were "finding prescription errors" (34.5%), "reasons for change in the chemotherapy regimen were unclear" (32.7%), and "finding differences between physicians' chemotherapy records and their chemotherapy prescriptions" (28.5%). Conclusion The computer could not evaluate chemotherapy protocols or adjust doses of anticancer medicines according to patients' conditions. Therefore, oncology pharmacists should continue to ensure safe and appropriate administration of cancer chemotherapy.