ObjectiveTo investigate the epidemiology of medication errors and error-related adverse events in adults in primary care, ambulatory care and patients’ homes.DesignSystematic review.Data sourceSix international databases were searched for publications between 1 January 2006 and 31 December 2015.Data extraction and analysisTwo researchers independently extracted data from eligible studies and assessed the quality of these using established instruments. Synthesis of data was informed by an appreciation of the medicines’ management process and the conceptual framework from the International Classification for Patient Safety.Results60 studies met the inclusion criteria, of which 53 studies focused on medication errors, 3 on error-related adverse events and 4 on risk factors only. The prevalence of prescribing errors was reported in 46 studies: prevalence estimates ranged widely from 2% to 94%. Inappropriate prescribing was the most common type of error reported. Only one study reported the prevalence of monitoring errors, finding that incomplete therapeutic/safety laboratory-test monitoring occurred in 73% of patients. The incidence of preventable adverse drug events (ADEs) was estimated as 15/1000 person-years, the prevalence of drug–drug interaction-related adverse drug reactions as 7% and the prevalence of preventable ADE as 0.4%. A number of patient, healthcare professional and medication-related risk factors were identified, including the number of medications used by the patient, increased patient age, the number of comorbidities, use of anticoagulants, cases where more than one physician was involved in patients’ care and care being provided by family physicians/general practitioners.ConclusionA very wide variation in the medication error and error-related adverse events rates is reported in the studies, this reflecting heterogeneity in the populations studied, study designs employed and outcomes evaluated. This review has identified important limitations and discrepancies in the methodologies used and gaps in the literature on the epidemiology and outcomes of medication errors in community settings.

Aim To compare the prevalence and causes of prescribing errors in newly written medication orders and how quickly they were rectified, in three NHS organisations. Methods Errors in newly written inpatient and discharge medication orders were recorded in Spring/Summer 2009 by ward pharmacists on medical admissions and surgical wards, as well as the number of erroneous doses administered (or omitted) before errors were corrected. Logistic regression analysis was used to explore the effects of ward (nested within organisation) and clinical specialty, and whether the pharmacist had checked the patient's medication history during data collection. Causes were explored using semistructured interviews with key informants. Results Overall, 1025 prescribing errors were identified in 974 of 6605 medication orders (14.7%, 95% confidence interval (CI) 13.8% to 15.6%). A mean of 0.9 doses were administered (or omitted) before each error was corrected (range 0e11), with differences between specialties and organisations. The error rate on medical admissions wards (16.3%) was significantly higher than that on surgical wards (12.2%), but this was accounted for by the higher proportion of prescribing being on admission, where omission of patients' usual medication was often identified. There were significant differences among wards (and organisations). Contributing factors included lack of feedback on errors, poor documentation and communication of prescribing decisions, and lack of information about patients' medication histories from primary care. Conclusions There were variations among wards, organisations and specialties in error rates and how quickly they were rectified. Exploring reasons for differences between organisations may be useful in identifying best practice and potential solutions.

Failure mode and effect analysis is a useful tool to aid multidisciplinary groups in understanding a process of care and identifying errors that may occur. However, the results of this study call into question the reliability of the FMEA process that was tested. The 2 groups identified similar steps in the process of care but different potential failures with very different risk priority numbers. Such discrepancies make it impossible to identify reliably those failures that should be prioritized and thus where money, time, and effort should be allocated to avoid these failures. Health care organizations should not solely depend on FMEA findings to improve patient safety.

Failure mode and effects analysis (FMEA) is a structured prospective risk assessment method that is widely used within healthcare. FMEA involves a multidisciplinary team mapping out a high-risk process of care, identifying the failures that can occur, and then characterising each of these in terms of probability of occurrence, severity of effects and detectability, to give a risk priority number used to identify failures most in need of attention. One might assume that such a widely used tool would have an established evidence base. This paper considers whether or not this is the case, examining the evidence for the reliability and validity of its outputs, the mathematical principles behind the calculation of a risk prioirty number, and variation in how it is used in practice. We also consider the likely advantages of this approach, together with the disadvantages in terms of the healthcare professionals' time involved. We conclude that although FMEA is popular and many published studies have reported its use within healthcare, there is little evidence to support its use for the quantitative prioritisation of process failures. It lacks both reliability and validity, and is very time consuming. We would not recommend its use as a quantitative technique to prioritise, promote or study patient safety interventions. However, the stage of FMEA involving multidisciplinary mapping process seems valuable and work is now needed to identify the best way of converting this into plans for action.

Background Failure Mode and Effects Analysis (FMEA) is a prospective risk assessment tool that has been widely used within the aerospace and automotive industries and has been utilised within healthcare since the early 1990s. The aim of this study was to explore the validity of FMEA outputs within a hospital setting in the United Kingdom. Methods Two multidisciplinary teams each conducted an FMEA for the use of vancomycin and gentamicin. Four different validity tests were conducted: · Face validity: by comparing the FMEA participants’ mapped processes with observational work. · Content validity: by presenting the FMEA findings to other healthcare professionals. · Criterion validity: by comparing the FMEA findings with data reported on the trust’s incident report database. · Construct validity: by exploring the relevant mathematical theories involved in calculating the FMEA risk priority number. Results Face validity was positive as the researcher documented the same processes of care as mapped by the FMEA participants. However, other healthcare professionals identified potential failures missed by the FMEA teams. Furthermore, the FMEA groups failed to include failures related to omitted doses; yet these were the failures most commonly reported in the trust’s incident database. Calculating the RPN by multiplying severity, probability and detectability scores was deemed invalid because it is based on calculations that breach the mathematical properties of the scales used. Conclusion There are significant methodological challenges in validating FMEA. It is a useful tool to aid multidisciplinary groups in mapping and understanding a process of care; however, the results of our study cast doubt on its validity. FMEA teams are likely to need different sources of information, besides their personal experience and knowledge, to identify potential failures. As for FMEA’s methodology for scoring failures, there were discrepancies between the teams’ estimates and similar incidents reported on the trust’s incident database. Furthermore, the concept of multiplying ordinal scales to prioritise failures is mathematically flawed. Until FMEA’s validity is further explored, healthcare organisations should not solely depend on their FMEA results to prioritise patient safety issues.

The growing problem of antimicrobial resistance (AMR) has led to calls for antimicrobial stewardship programs (ASP) to control antibiotic use in healthcare settings. Key strategies include prospective audit with feedback and intervention, and formulary restriction and preauthorization. Education, guidelines, clinical pathways, de-escalation, and intravenous to oral conversion are also part of some programs. Impact and quality of ASP can be assessed using process or outcome measures. Outcome measures are categorized as microbiological, patient or financial outcomes. The objective of this review was to provide an overview of quality measures for assessing ASP and the reported impact of ASP in peer-reviewed studies, focusing particularly on patient outcomes. A literature search of papers published in English between 1990 and June 2015 was conducted in five databases using a combination of search terms. Primary studies of any design were included. A total of 63 studies were included in this review. Four studies defined quality metrics for evaluating ASP. Twenty-one studies assessed the impact of ASP on antimicrobial utilization and cost, 25 studies evaluated impact on resistance patterns and/or rate of Clostridium difficile infection (CDI). Thirteen studies assessed impact on patient outcomes including mortality, length of stay (LOS) and readmission rates. Six of these 13 studies reported non-significant difference in mortality between pre- and post-ASP intervention, and five reported reductions in mortality rate. On LOS, six studies reported shorter LOS post intervention; a significant reduction was reported in one of these studies. Of note, this latter study reported significantly (p < 0.001) higher unplanned readmissions related to infections post-ASP. Patient outcomes need to be a key component of ASP evaluation. The choice of metrics is influenced by data and resource availability. Controlling for confounders must be considered in the design of evaluation studies to adequately capture the impact of ASP and it is important for unintended consequences to be considered. This review provides a starting point toward compiling standard outcome metrics for assessing ASP.

CDSS could be a powerful tool to improve clinical care and patient outcomes. It presents a promising future for optimising antibiotic use. However, it is difficult to generalise as most studies were conducted in the United States. Although RCT are the 'gold standard' in research, they may not be feasible to conduct. Realising that different study designs answer different questions would allow researchers to choose the most appropriate study design to evaluate CDSS in a specified setting.

Antimicrobial resistance is increasing at an alarming rate in the Gulf Cooperation Council (GCC) owing to the overuse and misuse of antimicrobials. Novel and rare multidrug-resistant strains can spread globally since the region is host to the largest expatriate population in the world as well as a pilgrimage destination for more than 4 million people annually. Adoption of antimicrobial stewardship programmes (ASPs) could improve the use of antimicrobials and reduce antimicrobial resistance in the region. However, despite the established benefits of these interventions, little is known about the level of their adoption in the region and the impact of these programmes on antimicrobial use and resistance. This study aimed to review existing evidence on the level of adoption of ASPs, the facilitators and barriers to their adoption, and outcomes of their adoption in GCC hospitals.