How could online NHS 111 reduce demand for the telephone NHS 111 service? Qualitative study of user and staff views.

BACKGROUND: Online NHS111 was introduced in 2018 in response to increasing and unsustainable demand for telephone NHS111. Despite high levels of use, there is little evidence of channel shift from the telephone to the online service. We explored user and staff perspectives of online NHS111 to understand how and why online NHS111 is used and whether there may be potential for shift from the telephone to online service. METHODS: As part of a wider mixed-methods study, we used qualitative semistructured interviews to explore perspectives of recent users of online 111 who had responded to a user survey (n=32) and NHS 111 staff (n=16) between November 2019 and June 2020. Interviews were recorded and transcribed verbatim. The data sets were analysed separately using framework analysis (user interviews) and thematic analysis (staff interviews). RESULTS: Telephone NHS111 health adviser skills in probing and obtaining 'soft information' were perceived as key to obtaining advice that was considered more appropriate and trusted than advice from online interactions, which relied on oversimplified or irrelevant questions.Online NHS111 was perceived to provide a useful and convenient adjunct to the telephone service and widened access to NHS111 services for some subgroups of users who would not otherwise access the telephone service (eg, communication barriers, social anxiety) or were concerned about 'bothering' a health professional. The nature of the online consultation meant that online NHS111 was perceived as more disposable and used more speculatively. CONCLUSION: Online 111 was perceived as a useful adjunct but not a replacement for telephone NHS 111 with potential for channel shift hindered by reduced confidence in the online service due to the lack of human interaction. Further development of OL111 algorithms will be required if it is to meet the needs of people with more complex health needs.

The Safety INdEx of Prehospital On Scene Triage (SINEPOST) study: The development and validation of a risk prediction model to support ambulance clinical transport decisions on-scene.

One of the main problems currently facing the delivery of safe and effective emergency care is excess demand, which causes congestion at different time points in a patient's journey. The modern case-mix of prehospital patients is broad and complex, diverging from the traditional 'time critical accident and emergency' patients. It now includes many low-acuity patients and those with social care and mental health needs. In the ambulance service, transport decisions are the hardest to make and paramedics decide to take more patients to the ED than would have a clinical benefit. As such, this study asked the following research questions: In adult patients attending the ED by ambulance, can prehospital information predict an avoidable attendance? What is the simulated transportability of the model derived from the primary outcome? A linked dataset of 101,522 ambulance service and ED ambulance incidents linked to their respective ED care record from the whole of Yorkshire between 1st July 2019 and 29th February 2020 was used as the sample for this study. A machine learning method known as XGBoost was applied to the data in a novel way called Internal-External Cross Validation (IECV) to build the model. The results showed great discrimination with a C-statistic of 0.81 (95%CI 0.79-0.83) and excellent calibration with an O:E ratio was 0.995 (95% CI 0.97-1.03), with the most important variables being a patient's mobility, their physiological observations and clinical impression with psychiatric problems, allergic reactions, cardiac chest pain, head injury, non-traumatic back pain, and minor cuts and bruising being the most important. This study has successfully developed a decision-support model that can be transformed into a tool that could help paramedics make better transport decisions on scene, known as the SINEPOST model. It is accurate, and spatially validated across multiple geographies including rural, urban, and coastal. It is a fair algorithm that does not discriminate new patients based on their age, gender, ethnicity, or decile of deprivation. It can be embedded into an electronic Patient Care Record system and automatically calculate the probability that a patient will have an avoidable attendance at the ED, if they were transported. This manuscript complies with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement (Moons KGM, 2015).

A History of Regulatory Animal Testing: What Can We Learn?

The contemporary pharmaceutical industry is voicing growing concerns about the translatability and reproducibility of animal models. In addition, the usefulness of certain of the required regulatory safety tests in animals is being increasingly questioned. It remains difficult, however, to make the move toward alternative testing methods, not least because of legislative demands. A historical analysis was performed, in order to study how the mandatory animal studies in legislative requirements came about. This article reflects on the role that specific public health disasters played in the creation of (more) regulatory requirements for animal testing. It will show how the regulatory changes prompted by the sulfanilamide elixir disaster in the 1930s and the thalidomide disaster in the early 1960s were based on the belief that extensive animal testing would prevent similar future human health tragedies. As scientists increasingly highlight issues with translatability between non-human animals and humans, the belief that current regulatory requirements ensure safety becomes more difficult to maintain. In addition, it means that some of the regulations now in place require animal tests that do not contribute to the safety of a drug, as shown in a third case study of the court case by Vanda industries against the FDA. We finally argue that regulations should be critically examined and altered where necessary, so that they are no longer a barrier in the transition toward animal-free testing and more human-relevant science.

Measuring the impact introducing NHS 111 online had on the NHS 111 telephone service and the wider NHS urgent care system: an observational study.

OBJECTIVES: To explore what impact introducing the National Health Service (NHS) 111 online service had on the number of phone calls to the NHS 111 telephone service and the NHS urgent care system. DESIGN: Observational study using a dose-response interrupted time series model and random-effects meta- analysis to estimate the average effect. SETTING AND PARTICIPANTS: NHS 111 telephone and online contacts for 18 NHS 111 area codes in England. NHS 111 telephone and online contacts data were collected between October 2010 to December 2019 and January 2018 to December 2019, respectively. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome: the number of triaged calls to the NHS 111 telephone service following the introduction of NHS 111 online. SECONDARY OUTCOMES: total calls to the NHS 111 telephone service, total number of emergency ambulance referrals or advice to contact 999, total number of advice to attend an emergency department or other urgent care treatment facility, and total number of advice to contact primary care. RESULTS: For triaged calls, the overall incidence rate ratio (IRR) per 1000 online contacts was 1.013 (95% CI: 0.996 to 1.029, p=0.127). For total calls, the overall IRR per 1000 online contacts was 1.008 (95% CI: 0.992 to 1.025, p=0.313). For emergency ambulance referrals or advice to contact 999, the overall IRR per 1000 online contacts was 1.067 (95% CI: 1.035 to 1.100, p<0.001). For advice to attend an emergency department or other urgent care treatment facility, the overall IRR per 1000 online contacts is 1.050 (95% CI: 1.010 to 1.092, p=0.014). And finally, for those advised to contact primary care, the overall IRR per 1000 online contacts is 1.051 (95% CI: 1.027 to 1.076, p<0.001). CONCLUSIONS: It was found that the NHS 111 online service has little impact on the number of triaged and total calls, suggesting that the workload for the NHS 111 telephone service has not increased or decreased as a result of introducing NHS 111 online. However, there was evidence to suggest an increase in the overall number of disposition recommendations (ambulance, emergency department and primary care) for NHS 111 telephone and online services combined following the introduction of the NHS 111 online service.

Accuracy of emergency medical service telephone triage of need for an ambulance response in suspected COVID-19: an observational cohort study.

OBJECTIVE: To assess accuracy of emergency medical service (EMS) telephone triage in identifying patients who need an EMS response and identify factors which affect triage accuracy. DESIGN: Observational cohort study. SETTING: Emergency telephone triage provided by Yorkshire Ambulance Service (YAS) National Health Service (NHS) Trust. PARTICIPANTS: 12 653 adults who contacted EMS telephone triage services provided by YAS between 2 April 2020 and 29 June 2020 assessed by COVID-19 telephone triage pathways were included. OUTCOME: Accuracy of call handler decision to dispatch an ambulance was assessed in terms of death or need for organ support at 30 days from first contact with the telephone triage service. RESULTS: Callers contacting EMS dispatch services had an 11.1% (1405/12 653) risk of death or needing organ support. In total, 2000/12 653 (16%) of callers did not receive an emergency response and they had a 70/2000 (3.5%) risk of death or organ support. Ambulances were dispatched to 4230 callers (33.4%) who were not conveyed to hospital and did not deteriorate. Multivariable modelling found variables of older age (1 year increase, OR: 1.05, 95% CI: 1.04 to 1.05) and presence of pre-existing respiratory disease (OR: 1.35, 95% CI: 1.13 to 1.60) to be predictors of false positive triage. CONCLUSION: Telephone triage can reduce ambulance responses but, with low specificity. A small but significant proportion of patients who do not receive an initial emergency response deteriorated. Research to improve accuracy of EMS telephone triage is needed and, due to limitations of routinely collected data, this is likely to require prospective data collection.

Accuracy of telephone triage for predicting adverse outcomes in suspected COVID-19: an observational cohort study.

OBJECTIVE: To assess accuracy of telephone triage in identifying need for emergency care among those with suspected COVID-19 infection and identify factors which affect triage accuracy. DESIGN: Observational cohort study. SETTING: Community telephone triage provided in the UK by Yorkshire Ambulance Service NHS Trust (YAS). PARTICIPANTS: 40 261 adults who contacted National Health Service (NHS) 111 telephone triage services provided by YAS between 18 March 2020 and 29 June 2020 with symptoms indicating COVID-19 infection were linked to Office for National Statistics death registrations and healthcare data collected by NHS Digital. OUTCOME: Accuracy of triage disposition was assessed in terms of death or need for organ support up to 30 days from first contact. RESULTS: Callers had a 3% (1200/40 261) risk of serious adverse outcomes (death or organ support). Telephone triage recommended self-care or non-urgent assessment for 60% (24 335/40 261), with a 1.3% (310/24 335) risk of adverse outcomes. Telephone triage had 74.2% sensitivity (95% CI: 71.6 to 76.6%) and 61.5% specificity (95% CI: 61% to 62%) for the primary outcome. Multivariable analysis suggested respiratory comorbidities may be overappreciated, and diabetes underappreciated as predictors of deterioration. Repeat contact with triage service appears to be an important under-recognised predictor of deterioration with 2 contacts (OR 1.77, 95% CI: 1.14 to 2.75) and 3 or more contacts (OR 4.02, 95% CI: 1.68 to 9.65) associated with false negative triage. CONCLUSION: Patients advised to self-care or receive non-urgent clinical assessment had a small but non-negligible risk of serious clinical deterioration. Repeat contact with telephone services needs recognition as an important predictor of subsequent adverse outcomes.

Prognostic accuracy of triage tools for adults with suspected COVID-19 in a prehospital setting: an observational cohort study.

BACKGROUND: Tools proposed to triage patient acuity in COVID-19 infection have only been validated in hospital populations. We estimated the accuracy of five risk-stratification tools recommended to predict severe illness and compared accuracy to existing clinical decision making in a prehospital setting. METHODS: An observational cohort study using linked ambulance service data for patients attended by Emergency Medical Service (EMS) crews in the Yorkshire and Humber region of England between 26 March 2020 and 25 June 2020 was conducted to assess performance of the Pandemic Respiratory Infection Emergency System Triage (PRIEST) tool, National Early Warning Score (NEWS2), WHO algorithm, CRB-65 and Pandemic Medical Early Warning Score (PMEWS) in patients with suspected COVID-19 infection. The primary outcome was death or need for organ support. RESULTS: Of the 7549 patients in our cohort, 17.6% (95% CI 16.8% to 18.5%) experienced the primary outcome. The NEWS2 (National Early Warning Score, version 2), PMEWS, PRIEST tool and WHO algorithm identified patients at risk of adverse outcomes with a high sensitivity (>0.95) and specificity ranging from 0.3 (NEWS2) to 0.41 (PRIEST tool). The high sensitivity of NEWS2 and PMEWS was achieved by using lower thresholds than previously recommended. On index assessment, 65% of patients were transported to hospital and EMS decision to transfer patients achieved a sensitivity of 0.84 (95% CI 0.83 to 0.85) and specificity of 0.39 (95% CI 0.39 to 0.40). CONCLUSION: Use of NEWS2, PMEWS, PRIEST tool and WHO algorithm could improve sensitivity of EMS triage of patients with suspected COVID-19 infection. Use of the PRIEST tool would improve sensitivity of triage without increasing the number of patients conveyed to hospital.

Injured patients who would benefit from expedited major trauma centre care: a consensus-based definition for the United Kingdom.

INTRODUCTION: Despite the importance of treating the 'right patient in the right place at the right time', there is no gold standard for defining which patients should receive expedited major trauma centre (MTC) care. This study aimed to define a reference standard applicable to the United Kingdom (UK) National Health Service major trauma networks. METHODS: A one-day facilitated roundtable expert consensus meeting was conducted at the University of Sheffield, UK, in September 2019. An expert panel of 17 clinicians was purposively sampled, representing all specialities relevant to major trauma management. A consultation process was subsequently held using focus groups with Public and Patient Involvement (PPI) representatives to review and confirm the proposed reference standard. RESULTS: Four reference standard domains were identified, comprising: need for critical interventions; presence of significant individual anatomical injuries; burden of multiple minor injuries; and important patient attributes. Specific criteria were defined for each domain. PPI consultation confirmed all aspects of the reference standard. A coding algorithm to allow operationalisation in Trauma Audit and Research Network data was also formulated, allowing classification of any case submitted to their database for future research. CONCLUSIONS: This reference standard defines which patients would benefit from expedited MTC care. It could be used as the target for future pre-hospital injury triage tools, for setting best practice tariffs for trauma care reimbursement and to evaluate trauma network performance. Future research is recommended to compare patient characteristics, management and outcomes of the proposed definition with previously established reference standards.

The Safety INdEx of Prehospital On Scene Triage (SINEPOST) study: the development and validation of a risk prediction model to support ambulance clinical transport decisions on-scene-a protocol.

BACKGROUND: Demand for both the ambulance service and the emergency department (ED) is rising every year and when this demand is excessive in both systems, ambulance crews queue at the ED waiting to hand patients over. Some transported ambulance patients are 'low-acuity' and do not require the treatment of the ED. However, paramedics can find it challenging to identify these patients accurately. Decision support tools have been developed using expert opinion to help identify these low acuity patients but have failed to show a benefit beyond regular decision-making. Predictive algorithms may be able to build accurate models, which can be used in the field to support the decision not to take a low-acuity patient to an ED. METHODS AND ANALYSIS: All patients in Yorkshire who were transported to the ED by ambulance between July 2019 and February 2020 will be included. Ambulance electronic patient care record (ePCR) clinical data will be used as candidate predictors for the model. These will then be linked to the corresponding ED record, which holds the outcome of a 'non-urgent attendance'. The estimated sample size is 52,958, with 4767 events and an EPP of 7.48. An XGBoost algorithm will be used for model development. Initially, a model will be derived using all the data and the apparent performance will be assessed. Then internal-external validation will use non-random nested cross-validation (CV) with test sets held out for each ED (spatial validation). After all models are created, a random-effects meta-analysis will be undertaken. This will pool performance measures such as goodness of fit, discrimination and calibration. It will also generate a prediction interval and measure heterogeneity between clusters. The performance of the full model will be updated with the pooled results. DISCUSSION: Creating a risk prediction model in this area will lead to further development of a clinical decision support tool that ensures every ambulance patient can get to the right place of care, first time. If this study is successful, it could help paramedics evaluate the benefit of transporting a patient to the ED before they leave the scene. It could also reduce congestion in the urgent and emergency care system. TRIAL REGISTRATION: This study was retrospectively registered with the ISRCTN: 12121281.

Towards More Predictive, Physiological and Animal-free In Vitro Models: Advances in Cell and Tissue Culture 2020 Conference Proceedings.

Experimental systems that faithfully replicate human physiology at cellular, tissue and organ level are crucial to the development of efficacious and safe therapies with high success rates and low cost. The development of such systems is challenging and requires skills, expertise and inputs from a diverse range of experts, such as biologists, physicists, engineers, clinicians and regulatory bodies. Kirkstall Limited, a biotechnology company based in York, UK, organised the annual conference, Advances in Cell and Tissue Culture (ACTC), which brought together people having a variety of expertise and interests, to present and discuss the latest developments in the field of cell and tissue culture and in vitro modelling. The conference has also been influential in engaging animal welfare organisations in the promotion of research, collaborative projects and funding opportunities. This report describes the proceedings of the latest ACTC conference, which was held virtually on 30th September and 1st October 2020, and included sessions on in vitro models in the following areas: advanced skin and respiratory models, neurological disease, cancer research, advanced models including 3-D, fluid flow and co-cultures, diabetes and other age-related disorders, and animal-free research. The roundtable session on the second day was very interactive and drew huge interest, with intriguing discussion taking place among all participants on the theme of replacement of animal models of disease.

Diagnostic accuracy of prehospital triage tools for identifying major trauma in elderly injured patients: A systematic review.

BACKGROUND: Older adults with major trauma are frequently undertriaged, increasing the risk of preventable morbidity and mortality. The aim of this systematic review was to evaluate the diagnostic performance of prehospital triage tools to identify suspected elderly trauma patients in need of specialized trauma care. METHODS: Several electronic databases (including MEDLINE, EMBASE, and the Cochrane Library) were searched from inception to February 2019. Prospective or retrospective diagnostic studies were eligible if they examined prehospital triage tools as index tests (either scored theoretically using observed patient variables or evaluated according to actual paramedic transport decisions) compared with a reference standard for major trauma in elderly adults who require transport by paramedics following injury. Selection of studies, data extraction, and risk of bias assessments using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool were undertaken independently by at least two reviewers. Narrative synthesis was used to summarize the findings. RESULTS: Fifteen studies met the inclusion criteria, with 11 studies examining theoretical accuracy, three evaluating real-life transport decisions, and one assessing both (of 21 individual index tests). Estimates for sensitivity and specificity were highly variable with sensitivity estimates ranging from 19.8% to 95.5% and 57.7% to 83.3% for theoretical accuracy and real life triage performance, respectively. Specificity results were similarly diverse ranging from 17.0% to 93.1% for theoretical accuracy and 46.3% to 78.9% for actual paramedic decisions. Most studies had unclear or high risk of bias and applicability concerns. There were no obvious differences between different triage tools, and findings did not appear to vary systematically with major trauma prevalence, age, alternative reference standards, study designs, or setting. CONCLUSION: Existing prehospital triage tools may not accurately identify elderly patients with serious injury. Future work should focus on more relevant reference standards, establishing the best trade-off between undertriage and overtriage, optimizing the role prehospital clinician judgment, and further developing geriatric specific triage variables and thresholds. LEVEL OF EVIDENCE: Systematic review, level III.

Using machine-learning risk prediction models to triage the acuity of undifferentiated patients entering the emergency care system: a systematic review.

BACKGROUND: The primary objective of this review is to assess the accuracy of machine learning methods in their application of triaging the acuity of patients presenting in the Emergency Care System (ECS). The population are patients that have contacted the ambulance service or turned up at the Emergency Department. The index test is a machine-learning algorithm that aims to stratify the acuity of incoming patients at initial triage. This is in comparison to either an existing decision support tool, clinical opinion or in the absence of these, no comparator. The outcome of this review is the calibration, discrimination and classification statistics. METHODS: Only derivation studies (with or without internal validation) were included. MEDLINE, CINAHL, PubMed and the grey literature were searched on the 14th December 2019. Risk of bias was assessed using the PROBAST tool and data was extracted using the CHARMS checklist. Discrimination (C-statistic) was a commonly reported model performance measure and therefore these statistics were represented as a range within each machine learning method. The majority of studies had poorly reported outcomes and thus a narrative synthesis of results was performed. RESULTS: There was a total of 92 models (from 25 studies) included in the review. There were two main triage outcomes: hospitalisation (56 models), and critical care need (25 models). For hospitalisation, neural networks and tree-based methods both had a median C-statistic of 0.81 (IQR 0.80-0.84, 0.79-0.82). Logistic regression had a median C-statistic of 0.80 (0.74-0.83). For critical care need, neural networks had a median C-statistic of 0.89 (0.86-0.91), tree based 0.85 (0.84-0.88), and logistic regression 0.83 (0.79-0.84). CONCLUSIONS: Machine-learning methods appear accurate in triaging undifferentiated patients entering the Emergency Care System. There was no clear benefit of using one technique over another; however, models derived by logistic regression were more transparent in reporting model performance. Future studies should adhere to reporting guidelines and use these at the protocol design stage. REGISTRATION AND FUNDING: This systematic review is registered on the International prospective register of systematic reviews (PROSPERO) and can be accessed online at the following URL: https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020168696This study was funded by the NIHR as part of a Clinical Doctoral Research Fellowship.

Harnessing inter-disciplinary collaboration to improve emergency care in low- and middle-income countries (LMICs): results of research prioritisation setting exercise.

BACKGROUND: More than half of deaths in low- and middle-income countries (LMICs) result from conditions that could be treated with emergency care - an integral component of universal health coverage (UHC) - through timely access to lifesaving interventions. METHODS: The World Health Organization (WHO) aims to extend UHC to a further 1 billion people by 2023, yet evidence supporting improved emergency care coverage is lacking. In this article, we explore four phases of a research prioritisation setting (RPS) exercise conducted by researchers and stakeholders from South Africa, Egypt, Nepal, Jamaica, Tanzania, Trinidad and Tobago, Tunisia, Colombia, Ethiopia, Iran, Jordan, Malaysia, South Korea and Phillipines, USA and UK as a key step in gathering evidence required by policy makers and practitioners for the strengthening of emergency care systems in limited-resource settings. RESULTS: The RPS proposed seven priority research questions addressing: identification of context-relevant emergency care indicators, barriers to effective emergency care; accuracy and impact of triage tools; potential quality improvement via registries; characteristics of people seeking emergency care; best practices for staff training and retention; and cost effectiveness of critical care - all within LMICs. CONCLUSIONS: Convened by WHO and facilitated by the University of Sheffield, the Global Emergency Care Research Network project (GEM-CARN) brought together a coalition of 16 countries to identify research priorities for strengthening emergency care in LMICs. Our article further assesses the quality of the RPS exercise and reviews the current evidence supporting the identified priorities.

Effects of service changes affecting distance/time to access urgent and emergency care facilities on patient outcomes: a systematic review.

BACKGROUND: Reconfiguration of urgent and emergency care services often increases travel time/distance for patients to reach an appropriate facility. Evidence of the effects of reconfiguration is important for local communities and commissioners and providers of health services. METHODS: We performed a systematic review of the evidence regarding effects of service reconfigurations that increase the time/distance for some patients to reach an urgent and emergency care (UEC) facility. We searched seven bibliographic databases from 2000 to February 2019 and used citation tracking and reference lists to identify additional studies. We included studies of any design that compared outcomes for people with conditions requiring emergency treatment before and after service reconfiguration with an associated change in travel time/distance to access UEC. Studies had to be conducted in the UK or other developed countries. Data extraction and quality assessment (using the Joanna Briggs Institute checklist for quasi-experimental studies) were undertaken by a single reviewer with a sample checked for accuracy and consistency. We performed a narrative synthesis of the included studies. Overall strength of evidence was assessed using a previously published method that considers volume, quality and consistency. RESULTS: We included 12 studies, of which six were conducted in the USA, two in the UK and four in other European countries. The studies used a variety of observational designs, with before-after and cohort designs being most common. Only two studies included an independent control site/sites where no reconfiguration had taken place. The reconfigurations evaluated in these studies reported relatively small effects on average travel times/distance. DISCUSSION: For studies of general UEC populations, there was no convincing evidence as to whether reconfiguration affected mortality risk. However, evidence of increased risk was identified from studies of patients with acute myocardial infarction, particularly 1 to 4 years after reconfiguration. Evidence for other conditions was inconsistent or very limited. CONCLUSIONS: We found insufficient evidence to determine whether increased distance to UEC increases mortality risk for the general population of people requiring UEC, although this conclusion may not extend to people with specific conditions.

Digital and online symptom checkers and health assessment/triage services for urgent health problems: systematic review.

OBJECTIVES: In England, the NHS111 service provides assessment and triage by telephone for urgent health problems. A digital version of this service has recently been introduced. We aimed to systematically review the evidence on digital and online symptom checkers and similar services. DESIGN: Systematic review. DATA SOURCES: We searched Medline, Embase, the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Health Management Information Consortium, Web of Science and ACM Digital Library up to April 2018, supplemented by phrase searches for known symptom checkers and citation searching of key studies. ELIGIBILITY CRITERIA: Studies of any design that evaluated a digital or online symptom checker or health assessment service for people seeking advice about an urgent health problem. DATA EXTRACTION AND SYNTHESIS: Data extraction and quality assessment (using the Cochrane Collaboration version of QUADAS for diagnostic accuracy studies and the National Heart, Lung and Blood Institute tool for observational studies) were done by one reviewer with a sample checked for accuracy and consistency. We performed a narrative synthesis of the included studies structured around pre-defined research questions and key outcomes. RESULTS: We included 29 publications (27 studies). Evidence on patient safety was weak. Diagnostic accuracy varied between different systems but was generally low. Algorithm-based triage tended to be more risk averse than that of health professionals. There was very limited evidence on patients' compliance with online triage advice. Study participants generally expressed high levels of satisfaction, although in mainly uncontrolled studies. Younger and more highly educated people were more likely to use these services. CONCLUSIONS: The English 'digital 111' service has been implemented against a background of uncertainty around the likely impact on important outcomes. The health system may need to respond to short-term changes and/or shifts in demand. The popularity of online and digital services with younger and more educated people has implications for health equity. PROSPERO REGISTRATION NUMBER: CRD42018093564.

Outcomes for Patients Who Contact the Emergency Ambulance Service and Are Not Transported to the Emergency Department: A Data Linkage Study.

Objectives: Emergency ambulance services do not transport all patients to hospital. International literature reports non-transport rates ranging from 3.7-93.7%. In 2017, 38% of the 11 million calls received by ambulance services in England were attended by ambulance but not transported to an Emergency Department (ED). A further 10% received clinical advice over the telephone. Little is known about what happens to patients following a non-transport decision. We aimed to investigate what happens to patients following an emergency ambulance telephone call that resulted in a non-transport decision, using a linked routine data-set. Methods: Six-months individual patient level data from one ambulance service in England, linked with Hospital Episode Statistics and national mortality data, were used to identify subsequent health events (ambulance re-contact, ED attendance, hospital admission, death) within 3 days (primary analysis) and 7 days (secondary analysis) of an ambulance call ending in non-transport to hospital. Non-clinical staff used a priority dispatch system e.g. Medical Priority Dispatch System to prioritize calls for ambulance dispatch. Non-transport to ED was determined by ambulance crew members at scene or clinicians at the emergency operating center when an ambulance was not dispatched (telephone advice). Results: The data linkage rate was 85% for patients who were discharged at scene (43,108/50,894). After removal of deaths associated with end of life care (N = 312), 9% (3,861/42,796) re-contacted the ambulance service, 12.6% (5,412/42,796) attended ED, 6.3% (2,694/42,796) were admitted to hospital, and 0.3% (129/42,796) died within 3 days of the call. Rates were higher for events occurring within 7 days. For example, 12% re-contacted the ambulance service, 16.1% attended ED, 9.3% were admitted to hospital, and 0.5% died. The linkage rate for telephone advice calls was low because ambulance services record less information about these patients (24% 2,514/10,634). A sensitivity analysis identified a range of subsequent event rates: 2.5-10.5% of patients were admitted to hospital and 0.06-0.24% of patient died within 3 days of the call. Conclusions: Most non-transported patients did not have subsequent health events. Deaths after non-transport are an infrequent event that could be selected for more detailed review of individual cases, to facilitate learning and improvement.

Why do ambulance services have different non-transport rates? A national cross sectional study.

BACKGROUND: Some patients calling ambulance services (known as Emergency Medical Services internationally) are not transported to hospital. In England, national ambulance quality indicators show considerable variation in non-transport rates between the ten large regional ambulance services. The aim of this study was to explain variation between ambulance services in two types of non-transport: discharge at scene and telephone advice. METHODS: Mixed model logistic regressions using one month of data (November 2014) from the Computer Aided Despatch systems of the ten large regional ambulance services in England. RESULTS: 41% (251 677/615 815) of patients calling ambulance services were not transported to hospital. Most were discharged at scene after attendance by an ambulance (29% n = 182 479) and a small percentage were given telephone advice (7% n = 40 679). Discharge at scene rates varied by patient-level factors e.g. they were higher for elderly patients, where the reason for calling was falls, and for patients attended by paramedics with extended skills. These patient-level factors did not explain variation between ambulance services. After adjustment for patient-level factors, the following ambulance service level factors explained variation in discharge at scene rates: proportion of patients attended by paramedics with extended skills (odds ratio 1.05 (95% CI 1.04, 1.07)), the perception of ambulance service staff that paramedics with extended skills were established and valued within the workforce (odds ratio 1.84 (1.45, 2.33), and the perception of ambulance service staff that senior management viewed non-transport as risky (odds ratio 0.78 (0.63, 0.98)). Variation in telephone advice rates could not be explained. CONCLUSIONS: Variation in discharge at scene rates was explained by differences in workforce configuration and managerial motivation, factors that are largely modifiable by ambulance services.

Understanding better how emergency doctors work. Analysis of distribution of time and activities of emergency doctors: a systematic review and critical appraisal of time and motion studies.

BACKGROUND: Optimising the efficiency and productivity of senior doctors is critical to ED function and delivery of safe patient care. Time and motion studies (TMS) can allow quantification of how these doctors spend their working time, identify inefficiencies in the current work processes and provide insights into improving working conditions, and enhancing productivity. Three questions were addressed: (1) How do senior emergency doctors spend their time in the ED? (2) How much of their time is spent on multitasking? (3) What is the number of tasks completed per hour? METHODS: The literature was systematically searched for TMS of senior emergency doctors. We searched for articles published in peer-reviewed journals in English language from 1998 to 2018 in the following databases: MEDLINE, EMBASE, Scopus, Web of Science and Cochrane. Studies were assessed for methodological quality using evidence-based quality criteria relevant for TMS including duration of observation, observer bias, Hawthorne effect and whether the task classification acknowledged any previous existing schemes. A narrative synthesis approach was followed. RESULTS: Fourteen TMS were included. The studies were liable to several biases including observer and Hawthorne bias. Overall, the time spent on direct face-to-face contact with the patient accounted for at least around 25%-40% of the senior doctors' time. The remaining time was mostly spent on indirect clinical care such as communication (8%-44%), documentation (10%-28%) and administrative tasks (2%-20%). The proportion of time spent on multitasking ranged from 10% to 23%. When reported, the number of tasks performed per hour was generally high. CONCLUSION: The review revealed that senior doctors spent a large percentage of their time on direct face-to-face contact with patients. The review findings provided a grounded understanding of how senior doctors spent their time in the ED and could be useful in implementing improvements to the emergency care system.

Senior doctor triage (SDT), a qualitative study of clinicians' views on senior doctors' involvement in triage and early assessment of emergency patients.

INTRODUCTION: Despite the focus during the last decade on introducing interventions such as senior doctor initial assessment or senior doctor triage (SDT) to reduce emergency department (ED) crowding, there has been little attempt to identify the views of emergency healthcare professionals on such interventions. The aim of this study was to gain an understanding of SDT from the perspective of emergency hospital staff. A secondary aim of this study was to develop a definition of SDT based on the interview findings and the available literature on this process. METHODS: Qualitative semi-structured telephone interviews were conducted with participants of different backgrounds including senior doctors, nurses, paramedics and ED managers. Textual data were analysed using a template analysis approach. RESULTS: 27 participants from 13 EDs across England were interviewed. SDT was viewed as a safety mechanism and a measure to control patient flow. The most prominent positive aspect was the ability to initiate early investigations and treatment. Various shortcomings of SDT were described such as the lack of standardisation of the process and its cost implications. Participants identified a number of barriers to this process including insufficient resources and exit block, and called for solutions focused on these issues. A proposed definition of an 'ideal' SDT was developed where it is described as a systematic brief assessment of patients arriving at the ED by a senior doctor-led team, which takes place in a dedicated unit. The aim of this assessment is to facilitate early investigation and management of patients, early patient disposition and guide junior staff to deliver safe and high-quality clinical care. CONCLUSION: This is the first national study to explore the opinions of various emergency and managerial staff on the SDT model. It revealed variable interpretations of this model and what it can and cannot offer. This has led to a standard definition of the SDT process, which can be useful for clinicians and researchers in emergency care.

Prioritizing novel and existing ambulance performance measures through expert and lay consensus: A three-stage multimethod consensus study.

BACKGROUND: Current ambulance quality and performance measures, such as response times, do not reflect the wider scope of care that services now provide. Using a three-stage consensus process, we aimed to identify new ways of measuring ambulance service quality and performance that represent service provider and public perspectives. DESIGN: A multistakeholder consensus event, modified Delphi study, and patient and public consensus workshop. SETTING AND PARTICIPANTS: Representatives from ambulance services, patient and public involvement (PPI) groups, emergency care clinical academics, commissioners and policymakers. RESULTS: Nine measures/principles were highly prioritized by >75% of consensus event participants, including measures relating to pain, patient experience, accuracy of dispatch decisions and patient safety. Twenty experts participated in two Delphi rounds to further refine and prioritize measures; 20 measures in three domains scored ≥8/9, indicating good consensus, including proportion of calls correctly prioritized, time to definitive care and measures related to pain. Eighteen patient/public representatives attended a consensus workshop, and six measures were identified as important. These include time to definitive care, response time, reduction in pain scores, calls correctly prioritized to appropriate levels of response and survival to hospital discharge for treatable emergency conditions. CONCLUSIONS: Using consensus methods, we identified a shortlist of ambulance outcome and performance measures that are important to ambulance clinicians and service providers, service users, commissioners, and clinical academics, reflecting current pre-hospital ambulance care and services. The measures can potentially be used to assess pre-hospital quality or performance over time, with most calculated using routinely available data.