BackgroundPatients with heart failure with preserved ejection fraction (HFpEF) are a complex and underserved group. They are commonly older patients with multiple comorbidities, who rely on multiple healthcare services. Regional variation in services and resourcing has been highlighted as a problem in heart failure care, with few teams bridging the interface between the community and secondary care. These reports conflict with policy goals to improve coordination of care and dissolve boundaries between specialist services and the community.AimTo explore how care is coordinated for patients with HFpEF, with a focus on the interface between primary care and specialist services in England.MethodsWe applied systems thinking methodology to examine the relationship between work-as-imagined and work-as-done for coordination of care for patients with HFpEF. We analysed clinical guidelines in conjunction with a secondary applied thematic analysis of semistructured interviews with healthcare professionals caring for patients with HFpEF including general practitioners, specialist nurses and cardiologists and patients with HFpEF themselves (n=41). Systems Thinking for Everyday Work principles provided a sensitising theoretical framework to facilitate a deeper understanding of how these data illustrate a complex health system and where opportunities for improvement interventions may lie.ResultsThree themes (working with complexity, information transfer and working relationships) were identified to explain variability between work-as-imagined and work-as-done. Participants raised educational needs, challenging work conditions, issues with information transfer systems and organisational structures poorly aligned with patient needs.ConclusionsThere are multiple challenges that affect coordination of care for patients with HFpEF. Findings from this study illuminate the complexity in coordination of care practices and have implications for future interventional work.

BackgroundAntiplatelet therapy (APT) can substantially reduce the risk of further vascular events in individuals with established atherosclerotic cardiovascular disease (ASCVD). However, knowledge regarding the extent and determinants of APT use is limited.ObjectivesEstimate the extent and identify patient groups at risk of suboptimal APT use at different stages of the treatment pathway.MethodsRetrospective cohort study using linked NHS Scotland administrative data of all adults hospitalised for an acute ASCVD event (n=150 728) from 2009 to 2017. Proportions of patients initiating, adhering to, discontinuing and re-initiating APT were calculated overall and separately for myocardial infarction (MI), ischaemic stroke and peripheral arterial disease (PAD). Multivariable logistic regression and Cox proportional hazards models were used to assess the contribution of patient characteristics in initiating and discontinuing APT.ResultsOf patients hospitalised with ASCVD, 84% initiated APT: 94% following an MI, 83% following an ischaemic stroke and 68% following a PAD event. Characteristics associated with lower odds of initiation included female sex (22% less likely than men), age below 50 years or above 70 years (aged <50 years 26% less likely, and aged 70–79, 80–89 and ≥90 years 21%, 39% and 51% less likely, respectively, than those aged 60–69 years) and history of mental health-related hospitalisation (45% less likely). Of all APT-treated individuals, 22% discontinued treatment. Characteristics associated with discontinuation were similar to those related to non-initiation.ConclusionsAPT use remains suboptimal for the secondary prevention of ASCVD, particularly among women and older patients, and following ischaemic stroke and PAD hospitalisations.

Missing data are frequently encountered in registries that are used to compare performance across hospitals. The most appropriate method for handling missing data when analysing differences in outcomes between hospitals with a generalised linear mixed model is unclear. We aimed to compare methods for handling missing data when comparing hospitals on ordinal and dichotomous outcomes. We performed a simulation study using data from the Multicentre Randomised Controlled Trial of Endovascular Treatment for Acute Ischaemic Stroke in the Netherlands (MR CLEAN) Registry, a prospective cohort study in 17 hospitals performing endovascular therapy for ischaemic stroke in the Netherlands. The investigated methods for handling missing data, both case-mix adjustment variables and outcomes, were complete case analysis, single imputation, multiple imputation, single imputation with deletion of imputed outcomes and multiple imputation with deletion of imputed outcomes. Data were generated as missing completely at random (MCAR), missing at random and missing not at random (MNAR) in three scenarios: (1) 10% missing data in case-mix and outcome; (2) 40% missing data in case-mix and outcome; and (3) 40% missing data in case-mix and outcome with varying degree of missing data among hospitals. Bias and reliability of the methods were compared on the mean squared error (MSE, a summary measure combining bias and reliability) relative to the hospital effect estimates from the complete reference data set. For both the ordinal outcome (ie, the modified Rankin Scale) and a common dichotomised version thereof, all methods of handling missing data were biased, likely due to shrinkage of the random effects. The MSE of all methods was on average lowest under MCAR and with fewer missing data, and highest with more missing data and under MNAR. The ‘multiple imputation, then deletion’ method had the lowest MSE for both outcomes under all simulated patterns of missing data. Thus, when estimating hospital effects on ordinal and dichotomous outcomes in the presence of missing data, the least biased and most reliable method to handle these missing data is ‘multiple imputation, then deletion’.

IntroductionThe WHO Surgical Safety Checklist (SSC) is a communication tool that improves teamwork and patient outcomes. SSC effectiveness is dependent on implementation fidelity. Administrative audits fail to capture most aspects of SSC implementation fidelity (ie, team communication and engagement). Existing research tools assess behaviours during checklist performance, but were not designed for routine quality assurance and improvement. We aimed to create a simple tool to assess SSC implementation fidelity, and to test its reliability using video simulations, and usability in clinical practice.MethodsThe Checklist Performance Observation for Improvement (CheckPOINT) tool underwent two rounds of face validity testing with surgical safety experts, clinicians and quality improvement specialists. Four categories were developed: checklist adherence, communication effectiveness, attitude and engagement. We created a 90 min training programme, and four trained raters independently scored 37 video simulations using the tool. We calculated intraclass correlation coefficients (ICC) to assess inter-rater reliability (ICC>0.75 indicating excellent reliability). We then trained two observers, who tested the tool in the operating room. We interviewed the observers to determine tool usability.ResultsThe CheckPOINT tool had excellent inter-rater reliability across SSC phases. The ICC was 0.83 (95% CI 0.67 to 0.98) for the sign-in, 0.77 (95% CI 0.63 to 0.92) for the time-out and 0.79 (95% CI 0.59 to 0.99) for the sign-out. During field testing, observers reported CheckPOINT was easy to use. In 98 operating room observations, the total median (IQR) score was 25 (23–28), checklist adherence was 7 (6–7), communication effectiveness was 6 (6–7), attitude was 6 (6–7) and engagement was 6 (5–7).ConclusionsCheckPOINT is a simple and reliable tool to assess SSC implementation fidelity and identify areas of focus for improvement efforts. Although CheckPOINT would benefit from further testing, it offers a low-resource alternative to existing research tools and captures elements of adherence and team behaviours.

BackgroundThe Safety Case is a regulatory technique that requires organisations to demonstrate to regulators that they have systematically identified hazards in their systems and reduced risks to being as low as reasonably practicable. It is used in several high-risk sectors, but only in a very limited way in healthcare. We examined the first documented attempt to apply the Safety Case methodology to clinical pathways.MethodsData are drawn from a mixed-methods evaluation of the Safer Clinical Systems programme. The development of a Safety Case for a defined clinical pathway was a centrepiece of the programme. We base our analysis on 143 interviews covering all aspects of the programme and on analysis of 13 Safety Cases produced by clinical teams.ResultsThe principles behind a proactive, systematic approach to identifying and controlling risk that could be curated in a single document were broadly welcomed by participants, but was not straightforward to deliver. Compiling Safety Cases helped teams to identify safety hazards in clinical pathways, some of which had been previously occluded. However, the work of compiling Safety Cases was demanding of scarce skill and resource. Not all problems identified through proactive methods were tractable to the efforts of front-line staff. Some persistent hazards, originating from institutional and organisational vulnerabilities, appeared also to be out of the scope of control of even the board level of organisations. A particular dilemma for organisational senior leadership was whether to prioritise fixing the risks proactively identified in Safety Cases over other pressing issues, including those that had already resulted in harm.ConclusionsThe Safety Case approach was recognised by those involved in the Safer Clinical Systems programme as having potential value. However, it is also fraught with challenge, highlighting the limitations of efforts to transfer safety management practices to healthcare from other sectors.

ObjectiveIn 2012, an ‘18-week referral to treatment standard’ was introduced in England. Among people on the list of those waiting for hospital treatment at a point in time, the standard states that at least ‘92% of patients should have been waiting for less than 18 weeks’. Targets can have unintended consequences, where patients are prioritised based on the target rather than clinical need. Such an effect will be evident as a spike in the number of hospital trusts at the target threshold, referred to as a threshold effect. This study examines for threshold effects across all non-specialist acute NHS England hospital trusts by financial year.MethodsA retrospective observational study of publicly available data examined waiting times for patients on the waiting list. We examined trust performance against the 92% target by financial year, from 2015/16 to 2021/22, using Cattaneo et al’s manipulation density test (test for discontinuity/spike in data around target threshold) for all patients and by type of treatment.ResultsThe proportion of NHS hospital trusts meeting the 92% target deteriorated over time. From 2015/16 to 2019/20, there was strong evidence of a threshold effect at the 92% target (p<0.001). There was no evidence of a threshold effect in 2020/21 (p=0.063) or 2021/22 (p=0.090). Threshold effects were present across most types of treatment in 2016/17 and fewer types from 2017/18 onwards.ConclusionWe observed striking evidence of a threshold effect suggesting that while targets change behaviour, they do so in a selective way, focusing on the threshold rather than a pervasive improvement in practice. However, at the height of the pandemic, as almost no trusts could reach the target, the threshold effect disappeared.