Search

Background: There is a need to identify approaches to reduce medication errors. Interest has converged on ePrescribing systems that incorporate computerised provider order entry and clinical decision support functionality. Objectives: We sought to describe the procurement, implementation and adoption of basic and advanced ePrescribing systems; to estimate their effectiveness and cost-effectiveness; and to develop a toolkit for system integration into hospitals incorporating implications for practice from our research. Design: We undertook a theoretically informed, mixed-methods, context-rich, naturalistic evaluation. Setting: We undertook six longitudinal case studies in four hospitals (sites C, E, J and K) that did not have ePrescribing systems at the start of the programme (three of which went live and one that never went live) and two hospitals (sites A and D) with embedded systems. In the three hospitals that implemented systems, we conducted interviews pre implementation, shortly after roll-out and at 1 year post implementation. In the hospitals that had embedded systems, we conducted two rounds of interviews, 18 months apart. We undertook a three-round eDelphi exercise involving 20 experts to identify 80 clinically important prescribing errors, which were developed into the Investigate Medication Prescribing Accuracy for Critical error Types (IMPACT) tool. We elicited the cost of an ePrescribing system at one (non-study) site and compared this with the calculated ‘headroom’ (the upper limit that the decision-maker should pay) for the systems (sites J, K and S) for which effectiveness estimates were available. We organised four national conferences and five expert round-table discussions to contextualise and disseminate our findings. Intervention: The implementation of ePrescribing systems with either computerised provider order entry or clinical decision support functionality. Main outcome measures: Error rates were calculated using the IMPACT tool, with changes over time represented as ratios of error rates (as a proportion of opportunities for errors) using Poisson regression analyses. Results: We conducted 242 interviews and 32.5 hours of observations and collected 55 documents across six case studies. Implementation was difficult, particularly in relation to integration and interfacing between systems. Much of the clinical decision support functionality in embedded sites remained switched off because of concerns about over alerting. Getting systems operational meant that little attention was devoted to system optimisation or secondary uses of data. The prescriptions of 1244 patients were audited pre computerised provider order entry and 1178 post computerised provider order entry implementation of system A at sites J and K, and system B at site S. A total of 21,138 opportunities for error were identified from 28,526 prescriptions. Across the three sites, for those prescriptions for which opportunities for error were identified, the error rate was found to reduce significantly post computerised provider order entry implementation, from 5.0% to 4.0% (p

Abstract Background Cluster randomised trials with unequal sized clusters often have lower precision than with clusters of equal size. To allow for this, sample sizes are inflated by a modified version of the design effect for clustering. These inflation factors are valid under the assumption that randomisation is stratified by cluster size. We investigate the impact of unequal cluster size when that constraint is relaxed, with particular focus on the stepped-wedge cluster randomised trial, where this is more difficult to achieve. Methods Assuming a multi-level mixed effect model with exchangeable correlation structure for a cross-sectional design, we use simulation methods to compare the precision for a trial with clusters of unequal size to a trial with clusters of equal size (relative efficiency). For a range of scenarios we illustrate the impact of various design features (the cluster-mean correlation – a function of the intracluster correlation and the cluster size, the number of clusters, number of randomisation sequences) on the average and distribution of the relative efficiency. Results Simulations confirm that the average reduction in precision, due to varying cluster sizes, is smaller in a stepped-wedge trial compared to the parallel trial. However, the variance of the distribution of the relative efficiency is large; and is larger under the stepped-wedge design compared to the parallel design. This can result in large variations in actual power, depending on the allocation of clusters to sequences. Designs with larger variations in cluster sizes, smaller number of clusters and studies with smaller cluster-mean correlations (smaller cluster sizes or smaller intra-cluster correlation) are particularly at risk. Conclusion The actual realised power in a stepped-wedge trial might be substantially higher or lower than that estimated. This is particularly important when there are a small number of clusters or the variability in cluster sizes is large. Constraining the randomisation on cluster size, where feasible, might mitigate this effect.

Background: NHS England’s 7-day services policy comprised 10 standards to improve access to quality health care across all days of the week. Six standards targeted hospital specialists on the assumption that their absence caused the higher mortality associated with weekend hospital admission: the ‘weekend effect’. The High-intensity Specialist-Led Acute Care (HiSLAC) collaboration investigated this using the implementation of 7-day services as a ‘natural experiment’. Objectives: The objectives were to determine whether or not increasing specialist intensity at weekends improves outcomes for patients undergoing emergency hospital admission, and to explore mechanisms and cost-effectiveness. Design: This was a two-phase mixed-methods observational study. Year 1 focused on developing the methodology. Years 2–5 included longitudinal research using quantitative and qualitative methods, and health economics. Methods: A Bayesian systematic literature review from 2000 to 2017 quantified the weekend effect. Specialist intensity measured over 5 years used self-reported annual point prevalence surveys of all specialists in English acute hospital trusts, expressed as the weekend-to-weekday ratio of specialist hours per 10 emergency admissions. Hospital Episode Statistics from 2007 to 2018 provided trends in weekend-to-weekday mortality ratios. Mechanisms for the weekend effect were explored qualitatively through focus groups and on-site observations by qualitative researchers, and a two-epoch case record review across 20 trusts. Case-mix differences were examined in a single trust. Health economics modelling estimated costs and outcomes associated with increased specialist provision. Results: Of 141 acute trusts, 115 submitted data to the survey, and 20 contributed 4000 case records for review and participated in qualitative research (involving interviews, and observations using elements of an ethnographic approach). Emergency department attendances and admissions have increased every year, outstripping the increase in specialist numbers; numbers of beds and lengths of stay have decreased. The reduction in mortality has plateaued; the proportion of patients dying after discharge from hospital has increased. Specialist hours increased between 2012/13 and 2017/18. Weekend specialist intensity is half that of weekdays, but there is no relationship with admission mortality. Patients admitted on weekends are sicker (they have more comorbid disease and more of them require palliative care); adjustment for severity of acute illness annuls the weekend effect. In-hospital care processes are slightly more efficient at weekends; care quality (errors, adverse events, global quality) is as good at weekends as on weekdays and has improved with time. Qualitative researcher assessments of hospital weekend quality concurred with case record reviewers at trust level. General practitioner referrals at weekends are one-third of those during weekdays and have declined further with time. Limitations: Observational research, variable survey response rates and subjective assessments of care quality were compensated for by using a difference-in-difference analysis over time. Conclusions: Hospital care is improving. The weekend effect is associated with factors in the community that precede hospital admission. Post-discharge mortality is increasing. Policy-makers should focus their efforts on improving acute and emergency care on a ‘whole-system’ 7-day approach that integrates social, community and secondary health care. Future work: Future work should evaluate the role of doctors in hospital and community emergency care and investigate pathways to emergency admission and quality of care following hospital discharge. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 13. See the NIHR Journals Library website for further project information.

ObjectivesTo explore the effect of introducing 24/7 resident labour ward consultant presence on neonatal and maternal outcomes in a large obstetric unit in England.DesignRetrospective time sequence analysis of routinely collected data.SettingObstetric unit of large teaching hospital in England.ParticipantsWomen and babies delivered between1 July 2011 and 30 June 2017. Births Main outcome measuresThe primary composite outcome comprised intrapartum stillbirth, neonatal death, babies requiring therapeutic hypothermia, or admission to neonatal intensive care within three hours of birth. Secondary outcomes included markers of neonatal and maternal morbidity. Planned subgroup analyses investigated gestation (Results17324 babies delivered before and 16110 after 24/7 consultant presence. The prevalence of the primary outcome increased by 0.65%, from 2.07% (359/17324) before 24/7 consultant presence to 2.72% (438/16110, P < 0.001) after 24/7 consultant presence which was consistent with an upward trend over time already well established before 24/7 consultant presence began (OR 1.09 p.a.; CI 1.04 to 1.13). Overall, there was no change in this trend associated with the transition to 24/7. However, in babies born ≥37 weeks gestation, the upward trend was reversed after implementation of 24/7 (OR 0.67 p.a.; CI 0.49 to 0.93; P = 0.017). No substantial differences were shown in other outcomes or subgroups.ConclusionsOverall, resident consultant obstetrician presence 24/7 on labour ward was not associated with a change in a pre-existing trend of increasing adverse infant outcomes. However, 24/7 presence was associated with a reversal in increasing adverse outcomes for term babies.

Abstract Background Quality of cardiopulmonary resuscitation (CPR) is associated with survival, but recommended guidelines are often not met, and less than half the children with an in-hospital arrest will survive to discharge. A single-center before-and-after study demonstrated that outcomes may be improved with a novel training program in which all pediatric intensive care unit staff are encouraged to participate in frequent CPR refresher training and regular, structured resuscitation debriefings focused on patient-centric physiology. Methods/design This ongoing trial will assess whether a program of structured debriefings and point-of-care bedside practice that emphasizes physiologic resuscitation targets improves the rate of survival to hospital discharge with favorable neurologic outcome in children receiving CPR in the intensive care unit. This study is designed as a hybrid stepped-wedge trial in which two of ten participating hospitals are randomly assigned to enroll in the intervention group and two are assigned to enroll in the control group for the duration of the trial. The remaining six hospitals enroll initially in the control group but will transition to enrolling in the intervention group at randomly assigned staggered times during the enrollment period. Discussion To our knowledge, this is the first implementation of a hybrid stepped-wedge design. It was chosen over a traditional stepped-wedge design because the resulting improvement in statistical power reduces the required enrollment by 9 months (14%). However, this design comes with additional challenges, including logistics of implementing an intervention prior to the start of enrollment. Nevertheless, if results from the single-center pilot are confirmed in this trial, it will have a profound effect on CPR training and quality improvement initiatives. Trial registration ClinicalTrials.gov, NCT02837497. Registered on July 19, 2016.

Background: Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. Objectives: The objectives were to assess whether or not the QI programme improves 90-day survival after emergency abdominal surgery; to assess effects on 180-day survival, hospital stay and hospital readmission; and to better understand these findings through an integrated process evaluation, ethnographic study and cost-effectiveness analysis. Design: This was a stepped-wedge cluster randomised trial. Hospitals were organised into 15 geographical clusters, and commenced the QI programme in random order over 85 weeks. Analyses were performed on an intention-to-treat basis. The primary outcome was analysed using a mixed-effects parametric survival model, adjusting for time-related effects. Ethnographic and economics data were collected in six hospitals. The process evaluation included all hospitals. Setting: The trial was set in acute surgical services of 93 NHS hospitals. Participants: Patients aged ≥ 40 years who were undergoing emergency abdominal surgery were eligible. Intervention: The intervention was a QI programme to implement an evidence-based care pathway. Main outcome measures: The primary outcome measure was mortality within 90 days of surgery. Secondary outcomes were mortality within 180 days, length of hospital stay and hospital readmission within 180 days. The main economic measure was the quality-adjusted life-years. Data sources: Data were obtained from the National Emergency Laparotomy Audit database; qualitative interviews and ethnographic observations; quality-of-life and NHS resource use data were collected via questionnaires. Results: Of 15,873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 participants in the usual care group and 7374 in the QI group. The primary outcome occurred in 1393 participants in the usual care group (16%), compared with 1210 patients in the QI group (16%) [QI vs. usual care hazard ratio (HR) 1.11, 95% confidence interval (CI) 0.96 to 1.28]. No differences were found in mortality at 180 days or hospital readmission; there was a small increase in hospital stay in the QI group (HR for discharge 0.90, 95% CI 0.83 to 0.97). There were only modest improvements in care processes following QI implementation. The ethnographic study revealed good QI engagement, but limited time and resources to implement change, affecting which processes teams addressed, the rate of change and eventual success. In some sites, there were challenges around prioritising the intervention in busy environments and in obtaining senior engagement. The intervention is unlikely to be cost-effective at standard cost-effectiveness thresholds, but may be cost-effective over the lifetime horizon. Limitations: Substantial delays were encountered in securing data access to national registries. Fewer patients than expected underwent surgery and the mortality rate was lower than anticipated. Conclusions: There was no survival benefit from a QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. The modest impact of the intervention on process measures, despite good clinician engagement, may have been limited by the time and resources needed to improve patient care. Future work: Future QI programmes must balance intervention complexity with the practical realities of NHS services to ensure that such programmes can be delivered with the resources available. Trial registration: Current Controlled Trials ISRCTN80682973 and The Lancet protocol 13PRT/7655. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 7, No. 32. See the NIHR Journals Library website for further project information.

The frequency of visits to Emergency Departments (ED) varies greatly between populations. This may reflect variation in patient behaviour, need, accessibility, and service configuration as well as the complex interactions between these factors. This study investigates the relationship between distance, socio-economic deprivation, and proximity to an alternative care setting (a Minor Injuries Unit (MIU)), with particular attention to the interaction between distance and deprivation. It is set in a population of approximately 5.4 million living in central England, which is highly heterogeneous in terms of ethnicity, socio-economics, and distance to hospital. The study data set captured 1,413,363 ED visits made by residents of the region to National Health Service (NHS) hospitals during the financial year 2007/8. Our units of analysis were small units of census geography having an average population of 1,545. Separate regression models were made for children and adults. For each additional kilometre of distance from a hospital, predicted child attendances fell by 2.2% (1.7%-2.6% p

BACKGROUND: We explored the use of routine blood tests and national early warning scores (NEWS) reported within ±24 hours of admission to predict in-hospital mortality in emergency admissions, using empirical decision Tree models because they are intuitive and may ultimately be used to support clinical decision making. METHODOLOGY: A retrospective analysis of adult emergency admissions to a large acute hospital during April 2009 to March 2010 in the West Midlands, England, with a full set of index blood tests results (albumin, creatinine, haemoglobin, potassium, sodium, urea, white cell count and an index NEWS undertaken within ±24 hours of admission). We developed a Tree model by randomly splitting the admissions into a training (50%) and validation dataset (50%) and assessed its accuracy using the concordance (c-) statistic. Emergency admissions (about 30%) did not have a full set of index blood tests and/or NEWS and so were not included in our analysis. RESULTS: There were 23248 emergency admissions with a full set of blood tests and NEWS with an in-hospital mortality of 5.69%. The Tree model identified age, NEWS, albumin, sodium, white cell count and urea as significant (p