Recognising and managing eating disorders in the emergency department.

Compared with other mental health conditions or psychiatric presentations, such as self-harm, which may be seen in emergency departments, eating disorders can seem relatively rare. However, they have the highest mortality across the spectrum of mental health, with high rates of medical complications and risk, ranging from hypoglycaemia and electrolyte disturbances to cardiac abnormalities. People with eating disorders may not disclose their diagnosis when they see healthcare professionals. This can be due to denial of the condition itself, a wish to avoid treatment for a condition which may be valued, or because of the stigma attached to mental health. As a result their diagnosis can be easily missed by healthcare professionals and thus the prevalence is underappreciated. This article presents eating disorders to emergency and acute medicine practitioners from a new perspective using the combined emergency, psychiatric, nutrition and psychology lens. It focuses on the most serious acute pathology which can develop from the more common presentations; highlights indicators of hidden disease; discusses screening; suggests key acute management considerations and explores the challenge of mental capacity in a group of high-risk patients who, with the right treatment, can make a good recovery.

Recognising and managing eating disorders in the emergency department.

Compared with other mental health conditions or psychiatric presentations, such as self-harm, which may be seen in emergency departments, eating disorders can seem relatively rare. However, they have the highest mortality across the spectrum of mental health, with high rates of medical complications and risk, ranging from hypoglycaemia and electrolyte disturbances to cardiac abnormalities. People with eating disorders may not disclose their diagnosis when they see healthcare professionals. This can be due to denial of the condition itself, a wish to avoid treatment for a condition which may be valued, or because of the stigma attached to mental health. As a result their diagnosis can be easily missed by healthcare professionals and thus the prevalence is underappreciated. This article presents eating disorders to emergency and acute medicine practitioners from a new perspective using the combined emergency, psychiatric, nutrition and psychology lens. It focuses on the most serious acute pathology which can develop from the more common presentations; highlights indicators of hidden disease; discusses screening; suggests key acute management considerations and explores the challenge of mental capacity in a group of high-risk patients who, with the right treatment, can make a good recovery.

Cross-cultural adaptation and its impact on research in emergency care.

The perspective of patients is increasingly recognised as important to care improvement and innovation. Patient questionnaires such as patient-reported outcome measures may often require cross-cultural adaptation (CCA) to gather their intended information most effectively when used in cultures and languages different to those in which they were developed. The use of CCA could be seen as a practical step in addressing the known problems of inclusion, diversity and access in medical research.An example of the recent adaptation of a patient-reported outcome measure for use with ED patients is used to explore some key features of CCA, introduce the importance of CCA to emergency care practitioners and highlight the limitations of CCA.

What is the inter-rater agreement of injury classification using the WHO minimum data set for emergency medical teams?

BACKGROUND: In 2017, the WHO produced its first minimum data set (MDS) for emergency medical team (EMT) daily reporting during the sudden-onset disasters (SODs), following expert consensus. The MDS was deliberately designed to be simple in order to improve the rate of data capture; however, it is new and untested. This study assesses the inter-rater agreement between practitioners when performing the injury aspect of coding within the WHO EMT MDS. METHODS: 25 clinical case vignettes were developed, reflecting potential injuries encountered in an SOD. These were presented online from April to July 2018 to practitioners who have experience of/training in managing patients in SODs The practitioners were from UK-Med's members, Australian Medical Assistance Team's Northern Territory members and New Zealand Medical Assistance Team members. Practitioners were asked to code injuries according to WHO EMT MDS case classifications. Randolph's kappa statistic for free-marginal multirater data was calculated for the whole dataset as well as subgroups to ascertain inter-rater agreement. RESULTS: 86 practitioners responded (20.6% response rate), giving >2000 individual case responses. Overall agreement was moderate at 67.9% with a kappa of 0.59 (95% CI 0.49 to 0.69). Despite subgroups of paramedics (kappa 0.63, 95% CI 0.53 to 0.72), doctors (kappa 0.61, 95% CI 0.52 to 0.69) and those with disaster experience (kappa 0.62, 95% CI 0.52 to 0.71) suggesting slightly higher agreement, their CIs (and those of other subgroups) suggest overall similar and moderate levels of practitioner agreement in classifying injuries according to the MDS categories. CONCLUSIONS: An inter-rater agreement of 0.59 is moderate, at best, however, it gives ministries of health some sense of how tightly they may interpret injury data derived from daily reports using WHO EMT MDS. Furthermore, this kappa is similar to established but more complex (thus more contextually impractical) injury scores. Similar studies, with weighting for injury likelihood using sample data from SODs would further refine the level of expected inter-rater agreement.

Attacks on healthcare: what information is needed to understand their impact? - a Delphi study.

The scale of attacks on healthcare in emergencies has become better understood through data collection. But less well un\derstood are the consequences of attacks. The purpose of this study was to establish what information could improve our understanding of the impacts of attacks on healthcare. Using the three-round Delphi method, we sought consensus among experts in this field of study of attacks on healthcare to answer the study question. Seventeen experts agreed to take part. The experts generated a total of 222 unique statements identifying those data and information that would improve understanding of the impacts of attacks on healthcare, of which 162 reached consensus. All statements were categorized into 12 themes, each addressing different types of impacts. This Delphi study prepares the groundwork for a research agenda to explore the impacts of attacks on healthcare. These statements will be of use to academics working to expand the evidence base of attacks on healthcare. The study revealed disagreement on how widely the World Health Organization definition of an attack on healthcare should be interpreted and therefore what constitutes an impact of an attack. This is an important finding and further work is required to establish workable definitions for data collection.

A scoping review of the wider and long-term impacts of attacks on healthcare in conflict zones.

Attacks on health care in conflict zones are widespread and show no signs of relenting. Since 2011 several organizations have systemically collected data of these attacks and revealed their scale. However, little is known of the consequences of these attacks. The purpose of this scoping review was to explore the literature on attacks on health care in conflict zones to understand what is known of the wider and long-term impacts. Using the Arksey and O'Malley framework we identified 233 articles for inclusion. Extracting descriptions of impacts, we were able to categorize this information into 15 broad themes. However, there are limitations in the data collection on impacts. Firstly it is not systemically collected after every attack or in all regions where attacks take place. Secondly, this data stops short of working down the chain of impacts to describe the full range of consequences. Lastly, the literature does not often distinguish between the impacts of attacks on health care and the impact of conflict on health. Discussion is needed as to how we define and understand attacks on health care and therefore the impacts of these attacks. Systematic methods for data collection on the impacts of attacks on healthcare are also needed to produce comprehensive data sets.

What is positionality and should it be expressed in quantitative studies?

Although we are increasingly reaping the benefits of qualitative studies, their approach and that of quantitative studies remain rather separate. Emergency medicine practitioners thrive off research in context as we deal with such an undifferentiated population however quantitative 'hard-science' work is conspicuous for its absence of positionality. This contrasts strongly with the way in which qualitative research, within the domain of so-called soft-science literature, uses positionality as an integral element of the research process. Without contextualising the researcher and research environment in qualitative studies, often the meaning of any research output is lost. What follows is that positionality does not undermine the truth of such research, instead it defines the boundaries within which the research was produced. ​ The absence of positionality when considered alongside the notion of bias, may challenge the quantitative idea of validity.

A literature review of medical record keeping by foreign medical teams in sudden onset disasters.

BACKGROUND: Medical records are a tenet of good medical practice and provide one method of communicating individual follow-up arrangements, informing research data, and documenting medical intervention. METHODS: The objective of this review was to look at one source (the published literature) of medical records used by foreign medical teams (FMTs) in sudden onset disasters (SODs). The published literature was searched systematically for evidence of what medical records have been used by FMTs in SODs. Findings The style and content of medical records kept by FMTs in SODs varied widely according to the published literature. Similarly, there was great variability in practice as to what happens to the record and/or the data from the record following its use during a patient encounter. However, there was a paucity of published work comprehensively detailing the exact content of records used. Interpretation Without standardization of the content of medical records kept by FMTs in SODs, it is difficult to ensure robust follow-up arrangements are documented. This may hinder communication between different FMTs and local medical teams (LMTs)/other FMTs who may then need to provide follow-up care for an individual. Furthermore, without a standard method of reporting data, there is an inaccurate picture of the work carried out. Therefore, there is not a solid evidence base for improving the quality of future response to SODs. Further research targeting FMTs and LMTs directly is essential to inform any development of an internationally agreed minimum data set (MDS), for both recording and reporting, in order that FMTs can reach the World Health Organization (WHO) standards for FMT practice.

Long-term cardiovascular risk prediction in the emergency department: a mixed-methods study protocol.

INTRODUCTION: Cardiovascular disease (CVD) remains one of the leading causes of preventable death in Europe, therefore any opportunity to intervene and improve care should be maximised. Known CVD risk factors are routinely collected in the emergency department (ED), yet they are often not acted on. If the risk factors have prognostic value and a pathway can be created, then this would provide more holistic care for patients and reduce health system inefficiency. METHODS AND ANALYSIS: In this mixed-methods study, we will use quantitative methods to investigate the prognostic characteristics of routinely collected data for long-term CVD outcomes, and qualitative methods to investigate how to use and implement this knowledge. The quantitative arm will use a database of approximately 21 000 chest pain patient episodes with a mean follow-up of 7.3 years. We will use Cox regression to evaluate the prognostic characteristics of routinely collected ED data for long-term CVD outcomes. We will also use a series of semi-structured interviews to co-design a prototype care pathway with stakeholders via thematic analysis. To enable the development of prototypes, themes will be structured into a logic model consisting of situation, inputs, outputs and mechanism. ETHICS AND DISSEMINATION: This work has been approved by Research Ethics Committee (Wales REC7) and the Human Research Authority under reference 19/WA/0312 and 19/WA/0311. It has also been approved by the Confidentiality Advisory Group reference 19/CAG/0209. Dissent recorded in the NHS' opt-out scheme will be applied to the dataset by NHS Digital. This work will be disseminated through peer-review publication, conference presentation and a public dissemination strategy. TRIAL REGISTRATION NUMBER: ISRCTN41008456. PROTOCOL VERSION: V.1.0-7 June 2021.

Advanced cardiovascular risk prediction in the emergency department: updating a clinical prediction model - a large database study protocol.

BACKGROUND: Patients presenting with chest pain represent a large proportion of attendances to emergency departments. In these patients clinicians often consider the diagnosis of acute myocardial infarction (AMI), the timely recognition and treatment of which is clinically important. Clinical prediction models (CPMs) have been used to enhance early diagnosis of AMI. The Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid is currently in clinical use across Greater Manchester. CPMs have been shown to deteriorate over time through calibration drift. We aim to assess potential calibration drift with T-MACS and compare methods for updating the model. METHODS: We will use routinely collected electronic data from patients who were treated using TMACS at two large NHS hospitals. This is estimated to include approximately 14,000 patient episodes spanning June 2016 to October 2020. The primary outcome of acute myocardial infarction will be sourced from NHS Digital's admitted patient care dataset. We will assess the calibration drift of the existing model and the benefit of updating the CPM by model recalibration, model extension and dynamic updating. These models will be validated by bootstrapping and one step ahead prequential testing. We will evaluate predictive performance using calibrations plots and c-statistics. We will also examine the reclassification of predicted probability with the updated TMACS model. DISCUSSION: CPMs are widely used in modern medicine, but are vulnerable to deteriorating calibration over time. Ongoing refinement using routinely collected electronic data will inevitably be more efficient than deriving and validating new models. In this analysis we will seek to exemplify methods for updating CPMs to protect the initial investment of time and effort. If successful, the updating methods could be used to continually refine the algorithm used within TMACS, maintaining or even improving predictive performance over time. TRIAL REGISTRATION: ISRCTN number: ISRCTN41008456.