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According to their framework, the challenge for such research is to reconcile theoretical grounding (which favours abstraction and methodological rigour in order to isolate the critical mechanisms at play in a given situation) with an orientation towards practical problems (which favours consideration of healthcare concerns and representation of the typical actors, tasks and environments in order to demonstrate applicability). Or, looking to a design solution, might Tallman lettering, which appears to have equivocal support as a solution to medication errors,5 be of most benefit when distinguishing between unfamiliar drug names, as previously suggested by DeHenau et al9? Another implication from Lambert et al’s findings is to consider minimising word length (and possibly also to avoid uncommon letter pairings) when devising drug names at the outset, which would add to the guidance currently available on name design.10 11 Incidentally, it would have been helpful to see the partial regression coefficients that the authors obtained from their analysis to tease out any direct but subtle effect of drug name composition and familiarity on real-world error rates (insofar as the error data collected for this study reflect the actual occurrence of errors; an assumption that, as the authors themselves acknowledge, comes with the caveats of a restricted sampling frame and the inherent limitations of self-reported error data). Community pharmacy, the immediate context for their study, is a key component of primary care medication supply but also a challenging setting in which to work, requiring the coordination of various system elements in order to meet multiple and interacting goals.12 13 As a result, there are other matters to consider with regard to LASA errors. Should a human-centred approach to product design and evaluation be adopted within the supply chain?

The objective of this study was to use a prospective error analysis method to examine the process of dispensing medication in community pharmacy settings and identify remedial solutions to avoid potential errors, categorising them as strong, intermediate, or weak based on an established patient safety action hierarchy tool. Focus group discussions and non-participant observations were undertaken to develop a Hierarchical Task Analysis (HTA), and subsequent focus group discussions applied the Systematic Human Error Reduction and Prediction Approach (SHERPA) focusing on the task of dispensing medication in community pharmacies. Remedial measures identified through the SHERPA analysis were then categorised as strong, intermediate, or weak based on the Veteran Affairs National Centre for Patient Safety action hierarchy. Non-participant observations were conducted at 3 pharmacies, totalling 12 hours, based in England. Additionally, 7 community pharmacists, with experience ranging from 8 to 38 years, participated in a total of 4 focus groups, each lasting between 57 to 85 minutes, with one focus group discussing the HTA and three applying SHERPA. A HTA was produced consisting of 10 sub-tasks, with further levels of sub-tasks within each of them. Overall, 88 potential errors were identified, with a total of 35 remedial solutions proposed to avoid these errors in practice. Sixteen (46%) of these remedial measures were categorised as weak, 14 (40%) as intermediate and 5 (14%) as strong according to the Veteran Affairs National Centre for Patient Safety action hierarchy. Sub-tasks with the most potential errors were identified, which included 'producing medication labels' and 'final checking of medicines'. The most common type of error determined from the SHERPA analysis related to omitting a check during the dispensing process which accounted for 19 potential errors. This work applies both HTA and SHERPA for the first time to the task of dispensing medication in community pharmacies, detailing the complexity of the task and highlighting potential errors and remedial measures specific to this task. Future research should examine the effectiveness of the proposed remedial solutions to improve patient safety.

AbstractObjectiveTo systematically quantify the prevalence, severity, and nature of preventable patient harm across a range of medical settings globally.DesignSystematic review and meta-analysis.Data sourcesMedline, PubMed, PsycINFO, Cinahl and Embase, WHOLIS, Google Scholar, and SIGLE from January 2000 to January 2019. The reference lists of eligible studies and other relevant systematic reviews were also searched.Review methodsObservational studies reporting preventable patient harm in medical care. The core outcomes were the prevalence, severity, and types of preventable patient harm reported as percentages and their 95% confidence intervals. Data extraction and critical appraisal were undertaken by two reviewers working independently. Random effects meta-analysis was employed followed by univariable and multivariable meta regression. Heterogeneity was quantified by using the I2 statistic, and publication bias was evaluated.ResultsOf the 7313 records identified, 70 studies involving 337 025 patients were included in the meta-analysis. The pooled prevalence for preventable patient harm was 6% (95% confidence interval 5% to 7%). A pooled proportion of 12% (9% to 15%) of preventable patient harm was severe or led to death. Incidents related to drugs (25%, 95% confidence interval 16% to 34%) and other treatments (24%, 21% to 30%) accounted for the largest proportion of preventable patient harm. Compared with general hospitals (where most evidence originated), preventable patient harm was more prevalent in advanced specialties (intensive care or surgery; regression coefficient b=0.07, 95% confidence interval 0.04 to 0.10).ConclusionsAround one in 20 patients are exposed to preventable harm in medical care. Although a focus on preventable patient harm has been encouraged by the international patient safety policy agenda, there are limited quality improvement practices specifically targeting incidents of preventable patient harm rather than overall patient harm (preventable and non-preventable). Developing and implementing evidence-based mitigation strategies specifically targeting preventable patient harm could lead to major service quality improvements in medical care which could also be more cost effective.

ObjectiveTo 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.MethodsA 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.ResultsPrescribing 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.ConclusionsCognitive 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.

BackgroundStandardisation, a widely accepted concept for risk management, entails designing and implementing task-specific operating procedures. In community pharmacies, Standardised Operating Procedures (SOPs) are a mandatory requirement and are recognised as essential for upholding safety and quality.AimThis study aimed to investigate community pharmacists’ (CPs) compliance with SOPs when checking prescriptions, and the reasons for variations between standardised protocols and practice.MethodEight sets of SOPs underwent hierarchical task analysis (HTA) to generate a normative description of clinical checking execution as per protocols. Subsequently, twelve CPs were engaged in a simulated clinical checking exercise, verbalising their thoughts while checking virtual prescriptions. Transcribed data underwent content analysis, aligned with a descriptive model to uncover engagement patterns, and disparities between SOPs and CPs’ practices. Finally, a focus group discussion took place to contextualise the observed variations.ResultsHTA aided in constructing a clinical checking model with six primary subtasks and 28 lower subtasks. CPs often omitted subtasks during checks, diverging from prescribed protocols. These deviations, observed in controlled environment, reveal an ingrained aspect within the professional culture of pharmacists, where there may be a tendency not to strictly adhere to protocols, despite variations in work conditions. Contributing factors to this culture include the exercise of professional judgment, reliance on others, and prioritisation of patient preferences.ConclusionThis study highlights ongoing deviations from SOPs during clinical prescription checks in community pharmacies, suggesting a cultural tendency. Future research should delve into risk management strategies for these deviations and address the delicate balance between flexibility and stringent compliance.

We evaluated the impact of the pharmacist-led Safety Medication dASHboard (SMASH) intervention on medication safety in primary care. SMASH comprised (1) training of clinical pharmacists to deliver the intervention; (2) a web-based dashboard providing actionable, patient-level feedback; and (3) pharmacists reviewing individual at-risk patients, and initiating remedial actions or advising general practitioners on doing so. It was implemented in 43 general practices covering a population of 235,595 people in Salford (Greater Manchester), UK. All practices started receiving the intervention between 18 April 2016 and 26 September 2017. We used an interrupted time series analysis of rates (prevalence) of potentially hazardous prescribing and inadequate blood-test monitoring, comparing observed rates post-intervention to extrapolations from a 24-month pre-intervention trend. The number of people registered to participating practices and having 1 or more risk factors for being exposed to hazardous prescribing or inadequate blood-test monitoring at the start of the intervention was 47,413 (males: 23,073 [48.7%]; mean age: 60 years [standard deviation: 21]). At baseline, 95% of practices had rates of potentially hazardous prescribing (composite of 10 indicators) between 0.88% and 6.19%. The prevalence of potentially hazardous prescribing reduced by 27.9% (95% CI 20.3% to 36.8%, p < 0.001) at 24 weeks and by 40.7% (95% CI 29.1% to 54.2%, p < 0.001) at 12 months after introduction of SMASH. The rate of inadequate blood-test monitoring (composite of 2 indicators) reduced by 22.0% (95% CI 0.2% to 50.7%, p = 0.046) at 24 weeks; the change at 12 months (23.5%) was no longer significant (95% CI -4.5% to 61.6%, p = 0.127). After 12 months, 95% of practices had rates of potentially hazardous prescribing between 0.74% and 3.02%. Study limitations include the fact that practices were not randomised, and therefore unmeasured confounding may have influenced our findings. The SMASH intervention was associated with reduced rates of potentially hazardous prescribing and inadequate blood-test monitoring in general practices. This reduction was sustained over 12 months after the start of the intervention for prescribing but not for monitoring of medication. There was a marked reduction in the variation in rates of hazardous prescribing between practices.

Background Mitigating or reducing the risk of medication harm is a global policy priority. But evidence reflecting preventable medication harm in medical care and the factors that derive this harm remain unknown. Therefore, we aimed to quantify the prevalence, severity and type of preventable medication harm across medical care settings. Methods We performed a systematic review and meta-analysis of observational studies to compare the prevalence of preventable medication harm. Searches were carried out in Medline, Cochrane library, CINAHL, Embase and PsycINFO from 2000 to 27 January 2020. Data extraction and critical appraisal was undertaken by two independent reviewers. Random-effects meta-analysis was employed followed by univariable and multivariable meta-regression. Heterogeneity was quantified using the I 2 statistic, and publication bias was evaluated. PROSPERO: CRD42020164156. Results Of the 7780 articles, 81 studies involving 285,687 patients were included. The pooled prevalence for preventable medication harm was 3% (95% confidence interval (CI) 2 to 4%, I 2  = 99%) and for overall medication harm was 9% (95% CI 7 to 11%, I 2  = 99.5%) of all patient incidence records. The highest rates of preventable medication harm were seen in elderly patient care settings (11%, 95% 7 to 15%, n  = 7), intensive care (7%, 4 to 12%, n  = 6), highly specialised or surgical care (6%, 3 to 11%, n  = 13) and emergency medicine (5%, 2 to 12%, n  = 12). The proportion of mild preventable medication harm was 39% (28 to 51%, n  = 20, I 2  = 96.4%), moderate preventable harm 40% (31 to 49%, n  = 22, I 2  = 93.6%) and clinically severe or life-threatening preventable harm 26% (15 to 37%, n  = 28, I 2  = 97%). The source of the highest prevalence rates of preventable harm were at the prescribing (58%, 42 to 73%, n  = 9, I 2  = 94%) and monitoring (47%, 21 to 73%, n  = 8, I 2  = 99%) stages of medication use. Preventable harm was greatest in medicines affecting the ‘central nervous system’ and ‘cardiovascular system’. Conclusions This is the largest meta-analysis to assess preventable medication harm. We conclude that around one in 30 patients are exposed to preventable medication harm in medical care, and more than a quarter of this harm is considered severe or life-threatening. Our results support the World Health Organisation’s push for the detection and mitigation of medication-related harm as being a top priority, whilst highlighting other key potential targets for remedial intervention that should be a priority focus for future research.

Background Problems arising from medicines usage are recognised as a key patient safety issue. Children are a particular concern, given that they are more likely than adults to experience medication-related harm. While previous reviews have provided an estimate of prevalence in this population, these predate recent developments in the delivery of paediatric care. Hence, there is a need for an updated, focussed and critical review of the prevalence and nature of drug-related problems in hospitalised children in the UK, in order to support the development and targeting of interventions to improve medication safety. Methods Nine electronic databases (Medline, Embase, CINAHL, PsychInfo, IPA, Scopus, HMIC, BNI, The Cochrane library and clinical trial databases) were searched from January 1999 to April 2019. Studies were included if they were based in the UK, reported on the frequency of adverse drug reactions (ADRs), adverse drug events (ADEs) or medication errors (MEs) affecting hospitalised children. Quality appraisal of the studies was also conducted. Results In all, 26 studies were included. There were no studies which specifically reported prevalence of adverse drug events. Two adverse drug reaction studies reported a median prevalence of 25.6% of patients (IQR 21.8–29.9); 79.2% of reactions warranted withdrawal of medication. Sixteen studies reported on prescribing errors (median prevalence 6.5%; IQR 4.7–13.3); of which, the median rate of dose prescribing errors was 11.1% (IQR 2.9–13). Ten studies reported on administration errors with a median prevalence of 16.3% (IQR 6.4–23). Administration technique errors represented 53% (IQR 52.7–67.4) of these errors. Errors detected during medicines reconciliation at hospital admission affected 43% of patients, 23% (Range 20.1–46) of prescribed medication; 70.3% (Range 50–78) were classified as potentially harmful. Medication errors detected during reconciliation on discharge from hospital affected 33% of patients and 19.7% of medicines, with 22% considered potentially harmful. No studies examined the prevalence of monitoring or dispensing errors. Conclusions Children are commonly affected by drug-related problems throughout their hospital journey. Given the high prevalence and risk of patient harm,, there is a need for a deeper theoretical understanding of paediatric medication systems to enable more effective interventions to be developed to improve patient safety.

Developments in information technology offer opportunities to enhance medication safety in primary care. We evaluated the implementation and adoption of a complex pharmacist-led intervention involving the use of an electronic audit and feedback surveillance dashboard to identify patients potentially at risk of hazardous prescribing or monitoring of medicines in general practices. The intervention aimed to create a rapid learning health system for medication safety in primary care. This study aimed to explore how the intervention was implemented, adopted and embedded into practice using a qualitative process evaluation. Twenty two participants were purposively recruited from eighteen out of forty-three general practices receiving the intervention as well as clinical commissioning group staff across Salford UK, which reflected the range of contexts in which the intervention was implemented. Interviews explored how pharmacists and GP staff implemented the intervention and how this affected care practice. Data analysis was thematic with emerging themes developed into coding frameworks based on Normalisation Process Theory (NPT). Engagement with the dashboard involved a process of sense-making in which pharmacists considered it added value to their work. The intervention helped to build respect, improve trust and develop relationships between pharmacists and GPs. Collaboration and communication between pharmacists and clinicians was primarily initiated by pharmacists and was important for establishing the intervention. The intervention operated as a rapid learning health system as it allowed for the evidence in the dashboard to be translated into changes in work practices and into transformations in care. Our study highlighted the importance of the combined use of information technology and the role of pharmacists working in general practice settings. Medicine optimisation activities in primary care may be enhanced by the implementation of a pharmacist-led electronic audit and feedback system. This intervention established a rapid learning health system that swiftly translated data from electronic health records into changes in practice to improve patient care. Using NPT provided valuable insights into the ways in which developing relationships, collaborations and communication between health professionals could lead to the implementation, adoption and sustainability of the intervention.

ObjectiveTo understand the sociotechnical factors affecting medication safety when intensive care patients are transferred to a hospital ward. Consideration of these medication safety factors would provide a theoretical basis, on which future interventions can be developed and evaluated to improve patient care.DesignQualitative study using semistructured interviews of intensive care and hospital ward-based healthcare professionals. Transcripts were anonymised prior to thematic analysis using the London Protocol and Systems Engineering in Patient Safety V.3.0 model frameworks.SettingFour north of England National Health Service hospitals. All hospitals used electronic prescribing in intensive care and hospital ward settings.ParticipantsIntensive care and hospital ward healthcare professionals (intensive care medical staff, advanced practitioners, pharmacists and outreach team members; ward-based medical staff and clinical pharmacists).ResultsTwenty-two healthcare professionals were interviewed. We identified 13 factors within five broad themes, describing the interactions that most strongly influenced the performance of the intensive care to hospital ward system interface. The themes were: Complexity of process performance and interactions; Time pressures and considerations; Communication processes and challenges; Technology and systems and Beliefs about consequences for the patient and organisation.ConclusionsThe complexity of the interactions on the system performance and time dependency was clear. We make several recommendations for policy change and further research based on improving: availability of hospital-wide integrated and functional electronic prescribing systems, patient flow systems, sufficient multiprofessional critical care staffing, knowledge and skills of staff, team performance, communication and collaboration and patient and family engagement.