Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts.

RATIONALE: Intensive care units (ICUs) admit the most severely ill patients. Once these patients are discharged from the ICU to a step-down ward, they continue to have their vital signs monitored by nursing staff, with Early Warning Score (EWS) systems being used to identify those at risk of deterioration. OBJECTIVES: We report the development and validation of an enhanced continuous scoring system for predicting adverse events, which combines vital signs measured routinely on acute care wards (as used by most EWS systems) with a risk score of a future adverse event calculated on discharge from the ICU. DESIGN: A modified Delphi process identified candidate variables commonly available in electronic records as the basis for a 'static' score of the patient's condition immediately after discharge from the ICU. L1-regularised logistic regression was used to estimate the in-hospital risk of future adverse event. We then constructed a model of physiological normality using vital sign data from the day of hospital discharge. This is combined with the static score and used continuously to quantify and update the patient's risk of deterioration throughout their hospital stay. SETTING: Data from two National Health Service Foundation Trusts (UK) were used to develop and (externally) validate the model. PARTICIPANTS: A total of 12 394 vital sign measurements were acquired from 273 patients after ICU discharge for the development set, and 4831 from 136 patients in the validation cohort. RESULTS: Outcome validation of our model yielded an area under the receiver operating characteristic curve of 0.724 for predicting ICU readmission or in-hospital death within 24 hours. It showed an improved performance with respect to other competitive risk scoring systems, including the National EWS (0.653). CONCLUSIONS: We showed that a scoring system incorporating data from a patient's stay in the ICU has better performance than commonly used EWS systems based on vital signs alone. TRIAL REGISTRATION NUMBER: ISRCTN32008295.

What is quality in long covid care? Lessons from a national quality improvement collaborative and multi-site ethnography.

BACKGROUND: Long covid (post covid-19 condition) is a complex condition with diverse manifestations, uncertain prognosis and wide variation in current approaches to management. There have been calls for formal quality standards to reduce a so-called "postcode lottery" of care. The original aim of this study-to examine the nature of quality in long covid care and reduce unwarranted variation in services-evolved to focus on examining the reasons why standardizing care was so challenging in this condition. METHODS: In 2021-2023, we ran a quality improvement collaborative across 10 UK sites. The dataset reported here was mostly but not entirely qualitative. It included data on the origins and current context of each clinic, interviews with staff and patients, and ethnographic observations at 13 clinics (50 consultations) and 45 multidisciplinary team (MDT) meetings (244 patient cases). Data collection and analysis were informed by relevant lenses from clinical care (e.g. evidence-based guidelines), improvement science (e.g. quality improvement cycles) and philosophy of knowledge. RESULTS: Participating clinics made progress towards standardizing assessment and management in some topics; some variation remained but this could usually be explained. Clinics had different histories and path dependencies, occupied a different place in their healthcare ecosystem and served a varied caseload including a high proportion of patients with comorbidities. A key mechanism for achieving high-quality long covid care was when local MDTs deliberated on unusual, complex or challenging cases for which evidence-based guidelines provided no easy answers. In such cases, collective learning occurred through idiographic (case-based) reasoning, in which practitioners build lessons from the particular to the general. This contrasts with the nomothetic reasoning implicit in evidence-based guidelines, in which reasoning is assumed to go from the general (e.g. findings of clinical trials) to the particular (management of individual patients). CONCLUSION: Not all variation in long covid services is unwarranted. Largely because long covid's manifestations are so varied and comorbidities common, generic "evidence-based" standards require much individual adaptation. In this complex condition, quality improvement resources may be productively spent supporting MDTs to optimise their case-based learning through interdisciplinary discussion. Quality assessment of a long covid service should include review of a sample of individual cases to assess how guidelines have been interpreted and personalized to meet patients' unique needs. STUDY REGISTRATION: NCT05057260, ISRCTN15022307.

Prevalence of orthostatic intolerance in long covid clinic patients and healthy volunteers: A multicenter study.

Orthostatic intolerance (OI), including postural orthostatic tachycardia syndrome (PoTS) and orthostatic hypotension (OH), are often reported in long covid, but published studies are small with inconsistent results. We sought to estimate the prevalence of objective OI in patients attending long covid clinics and healthy volunteers and associations with OI symptoms and comorbidities. Participants with a diagnosis of long covid were recruited from eight UK long covid clinics, and healthy volunteers from general population. All undertook standardized National Aeronautics and Space Administration Lean Test (NLT). Participants' history of typical OI symptoms (e.g., dizziness, palpitations) before and during the NLT were recorded. Two hundred seventy-seven long covid patients and 50 frequency-matched healthy volunteers were tested. Healthy volunteers had no history of OI symptoms or symptoms during NLT or PoTS, 10% had asymptomatic OH. One hundred thirty (47%) long covid patients had previous history of OI symptoms and 144 (52%) developed symptoms during the NLT. Forty-one (15%) had an abnormal NLT, 20 (7%) met criteria for PoTS, and 21 (8%) had OH. Of patients with an abnormal NLT, 45% had no prior symptoms of OI. Relaxing the diagnostic thresholds for PoTS from two consecutive abnormal readings to one abnormal reading during the NLT, resulted in 11% of long covid participants (an additional 4%) meeting criteria for PoTS, but not in healthy volunteers. More than half of long covid patients experienced OI symptoms during NLT and more than one in 10 patients met the criteria for either PoTS or OH, half of whom did not report previous typical OI symptoms. We therefore recommend all patients attending long covid clinics are offered an NLT and appropriate management commenced.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study.

Background: The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care). Objective: Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact. Design: Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders. Setting and participants: Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations. Results: Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation. Conclusions: We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used. Study registration: This study is registered as ISRCTN10863045. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.

Patient recovery in hospital is tracked by measuring heart rate, blood pressure and other 'vital signs' and converting them into a score. These are 'observed' regularly by nursing staff so that deterioration can be spotted early. However, taking observations can disturb patients, and taking them too often causes extra work for staff. More frequent monitoring is recommended for higher scores, but evidence is lacking. To work out how often patients should be monitored, we needed to know how likely it is for patients to become more unwell between observations. We analysed over 400,000 patient records from two hospitals to understand how scores change with time. We looked at three of the most serious risks for patients in hospital. These risks are dying, needing intensive care or having a cardiac arrest. We also looked at the risk that a patient's condition would deteriorate significantly before their measurements were taken again. We identified early signs of deterioration and how changes in vital signs affected the risk of a patient's condition becoming worse. From this we calculated a maximum risk of deterioration. We then calculated different monitoring schedules that keep individual patients below this risk level. Some of those would consume less staff time than current National Health Service guidelines suggest. We also watched staff record patients' vital signs. We learnt it takes about 5 minutes to take these measurements from each patient. This information helped us calculate how costs would change if patients' vital signs were taken more or less often. We found that patients with a low overall score could have their vital signs monitored less often without being in danger of serious harm. This frees up nursing time so that patients with a higher score can be monitored more often. Importantly, this can be achieved without employing more staff.

Mobilisation in the EveNing to prevent and TreAt deLirium (MENTAL): a mixed-methods, randomised controlled feasibility trial.

Background: Delirium is common in critically ill patients and associated with longer hospital stays, increased morbidity and higher healthcare costs. Non-pharmacological interventions have been advocated for delirium management, however there is little evidence evaluating feasibility and acceptability of physical interventions administered in the evening. The aim of this study was to conduct a feasibility trial of evening mobilisation to prevent and treat delirium in patients admitted to intensive care. Methods: In this mixed-methods, randomised controlled feasibility trial we recruited participants from intensive care units at two university hospitals in the United Kingdom. Eligible participants who were able to respond to verbal stimulus (Richmond agitation and sedation scale ≥3) and expected to stay in intensive care for at least 24 h were randomly assigned (1:1) to receive usual care or usual care plus evening mobilisation. The evening mobilisation was delivered between 19:00 and 21:00, for up to seven consecutive evenings or ICU discharge, whichever was sooner. All outcome assessments were completed by a team member blinded to randomisation and group allocation. Primary objective was to assess feasibility and acceptability of evening mobilisation. Primary feasibility outcomes were recruitment, consent and retention rates, and intervention fidelity. Intervention acceptability was evaluated through semi-structured interviews of participants and staff. Secondary outcomes included prevalence in incidence and duration of delirium, measured using the Confusion Assessment Method for ICU. This trial is registered at ClinicalTrials.gov, NCT05401461. Findings: Between July 16th, 2022, and October 31st, 2022, 58 eligible patients (29 usual care; 29 usual care plus evening mobilisation) were enrolled. We demonstrated the feasibility and acceptability of both the trial design and evening mobilisation intervention. Consent and retention rates over three months were 88% (58/66) and 90% (52/58) respectively, with qualitative analysis demonstrating good acceptability reported by both participants and staff. Secondary outcomes for the evening intervention group compared with the control group were: delirium incidence 5/26 (19%; 95% CI: 6-39%) vs 8/28 (29%; 95% CI: 13-49%) and mean delirium duration 2 days (SD 0.7) vs 4.25 days (SD 2.0). Interpretation: Results of this trial will inform the development of a definitive full-scale randomised controlled trial investigating the effects of evening mobilisation to treat delirium and improve health-related outcomes. Funding: None.

Mobilisation in the EveNing to TreAt deLirium (MENTAL): protocol for a mixed-methods feasibility randomised controlled trial.

INTRODUCTION: Delirium is common in critically ill patients and is associated with longer hospital stays, increased mortality and higher healthcare costs. A number of risk factors have been identified for the development of delirium in intensive care, two of which are sleep disturbance and immobilisation. Non-pharmacological interventions for the management of intensive care unit (ICU) delirium have been advocated, including sleep protocols and early mobilisation. However, there is a little published evidence evaluating the feasibility and acceptability of evening mobilisation. METHODS AND ANALYSIS: Mobilisation in the EveNing to TreAt deLirium (MENTAL) is a two-centre, mixed-methods feasibility randomised controlled trial (RCT). Sixty patients will be recruited from ICUs at two acute NHS trusts and randomised on a 1:1 basis to receive additional evening mobilisation, delivered between 19:00 and 21:00, or standard care. The underpinning hypothesis is that the physical exertion associated with evening mobilisation will promote better sleep, subsequently having the potential to reduce delirium incidence. The primary objective is to assess the feasibility and acceptability of a future, multicentre RCT. The primary outcome measures, which will determine feasibility, are recruitment and retention rates, and intervention fidelity. Acceptability of the intervention will be evaluated through semi-structured interviews of participants and staff. Secondary outcome measures include collecting baseline, clinical and outcome data to inform the power calculations of a future definitive trial. ETHICS AND DISSEMINATION: Ethical approval has been obtained through the Wales Research and Ethics Committee 6 (22/WA/0106). Participants are required to provide written informed consent. We aim to disseminate the findings through international conferences, international peer-reviewed journals and social media. TRIAL REGISTRATION NUMBER: NCT05401461.

Design and validation of a new Healthcare Systems Usability Scale (HSUS) for clinical decision support systems: a mixed-methods approach.

OBJECTIVE: To develop and validate a questionnaire to assess the usability of clinical decision support systems (CDSS) and to assist in the early identification of usability issues that may impact patient safety and quality of care. DESIGN: Mixed research methods were used to develop and validate the questionnaire. The qualitative study involved scale item development, content and face validity. Pilot testing established construct validity using factor analysis and facilitated estimates for reliability and internal consistency using the Cronbach's alpha coefficient. SETTING: Two hospitals within a single National Health Service Trust. PARTICIPANTS: We recruited a panel of 7 experts in usability and questionnaire writing for health purposes to test content validity; 10 participants to assess face validity and 78 participants for the pilot testing. To be eligible for this last phase, participants needed to be health professionals with at least 3 months experience using the local hospital electronic patient record system. RESULTS: Feedback from the face and content validity phases contributed to the development and improvement of scale items. The final Healthcare Systems Usability Scale (HSUS) proved quick to complete, easy to understand and was mostly worded by potential users. Exploratory analysis revealed four factors related to patient safety, task execution, alerts or recommendations accuracy, the effects of the system on workflow and ease of system use. These separate into four subscales: patient safety and decision effectiveness (seven items), workflow integration (six items), work effectiveness (five items) and user control (four items). These factors affect the quality of care and clinician's ability to make informed and timely decisions when using CDSS. The HSUS has a very good reliability with global Cronbach's alpha 0.914 and between 0.702 and 0.926 for the four subscales. CONCLUSION: The HSUS is a valid and reliable tool for usability testing of CDSS and early identification of usability issues that may cause medical adverse events.

LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS (LOCOMOTION): protocol for a mixed-methods study in the UK.

INTRODUCTION: Long COVID, a new condition whose origins and natural history are not yet fully established, currently affects 1.5 million people in the UK. Most do not have access to specialist long COVID services. We seek to optimise long COVID care both within and outside specialist clinics, including improving access, reducing inequalities, helping self-management and providing guidance and decision support for primary care. We aim to establish a 'gold standard' of care by systematically analysing current practices, iteratively improving pathways and systems of care. METHODS AND ANALYSIS: This mixed-methods, multisite study is informed by the principles of applied health services research, quality improvement, co-design, outcome measurement and learning health systems. It was developed in close partnership with patients (whose stated priorities are prompt clinical assessment; evidence-based advice and treatment and help with returning to work and other roles) and with front-line clinicians. Workstreams and tasks to optimise assessment, treatment and monitoring are based in three contrasting settings: workstream 1 (qualitative research, up to 100 participants), specialist management in 10 long COVID clinics across the UK, via a quality improvement collaborative, experience-based co-design and targeted efforts to reduce inequalities of access, return to work and peer support; workstream 2 (quantitative research, up to 5000 participants), patient self-management at home, technology-supported monitoring and validation of condition-specific outcome measures and workstream 3 (quantitative research, up to 5000 participants), generalist management in primary care, harnessing electronic record data to study population phenotypes and develop evidence-based decision support, referral pathways and analysis of costs. Study governance includes an active patient advisory group. ETHICS AND DISSEMINATION: LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS study is sponsored by the University of Leeds and approved by Yorkshire & The Humber-Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Participants will provide informed consent. Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers. TRIAL REGISTRATION NUMBER: NCT05057260, ISRCTN15022307.

Non-contact physiological monitoring of post-operative patients in the intensive care unit.

Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

Risk factors for new-onset atrial fibrillation during critical illness: A Delphi study.

Background: New-onset atrial fibrillation (NOAF) is common during critical illness and is associated with poor outcomes. Many risk factors for NOAF during critical illness have been identified, overlapping with risk factors for atrial fibrillation in patients in community settings. To develop interventions to prevent NOAF during critical illness, modifiable risk factors must be identified. These have not been studied in detail and it is not clear which variables warrant further study. Methods: We undertook an international three-round Delphi process using an expert panel to identify important predictors of NOAF risk during critical illness. Results: Of 22 experts invited, 12 agreed to participate. Participants were located in Europe, North America and South America and shared 110 publications on the subject of atrial fibrillation. All 12 completed the three Delphi rounds. Potentially modifiable risk factors identified include 15 intervention-related variables. Conclusions: We present the results of the first Delphi process to identify important predictors of NOAF risk during critical illness. These results support further research into modifiable risk factors including optimal plasma electrolyte concentrations, rates of change of these electrolytes, fluid balance, choice of vasoactive medications and the use of preventative medications in high-risk patients. We also hope our findings will aid the development of predictive models for NOAF.

Variability of environmental sound levels: An observational study from a general adult intensive care unit in the UK.

Background: Intensive care units are significantly louder than WHO guidelines recommend. Patients are disturbed by activities around them and frequently report disrupted sleep. This can lead to slower recovery and long-term health problems. Environmental sound levels are usually reported as LAeq24, a single daily value that reflects mean sound levels over the previous 24-h period. This may not be the most appropriate measure for intensive care units (ICUs) and other similar areas. Humans experience sound in context, and disturbance will vary according to both the individual and acoustic features of the ambient sounds. Loudness is one of a number of measures that approximate the human perception of sound, taking into account tone, duration, and frequency, as well as volume. Typically sounds with higher frequencies, such as alarms, are perceived as louder and more disturbing. Methods: Sound level data were collected from a single NHS Trust hospital general adult intensive care unit between October 2016 and May 2018. Summary data (mean sound levels (LAeq) and corresponding Zwicker calculated loudness values) were subsequently analysed by minute, hour, and day. Results: The overall mean LAeq24 across the study duration was 47.4 dBA. This varied by microphone location. We identified a clear pattern to sound level fluctuations across the 24-h period. Weekends were significantly quieter than weekdays in statistical terms but this reduction of 0.2 dB is not detectable by human hearing. Peak loudness values over 90 dB were recorded every hour. Conclusions: Perception of sound is sensitive to the environment and individual characteristics and sound levels in the ICU are location specific. This has implications for routine environmental monitoring practices. Peak loudness values are consistently between 90 and 100 dB. These may be driven by alarms and other sudden high-frequency sounds, leading to more disturbance than LAeq24 sound levels suggest. Addressing sounds with high loudness values may improve the ICU environment more than an overall reduction in the 24-h mean decibel value.

Monitoring sound levels in the intensive care unit: A mixed-methods system development project to optimize design features for a new electronic interface in the healthcare environment.

BACKGROUND: Intensive care units (ICU) are busy round the clock and it is difficult to maintain low sound levels that support patient rest. To help ICU staff manage activities we developed a visual display that monitors and reports sound levels in real-time. This facilitates immediate feedback, encouraging proactive behavior change to limit disturbances. METHODS: Following the principles of user-centered design practices we created our 'user persona' to understand the needs and goals of potential users of the system. We then conducted iterative user testing with current members of the ICU team, primarily using the 'think aloud' method to refine the design and functionality of our novel system. Ethnography evaluated team use of the display. RESULTS: The final design was simple, clear, and efficient, and both functional and aesthetically pleasing for the key user demographic. We identified challenges in the implementation and adoption process that were separate from the 'usability' of the system itself. CONCLUSIONS: Embedding the design process within the core user demographic ensured the final product delivered relevant information for key users, and that this information was intuitive to interpret. Initiating sustainable change is not straightforward. It requires recognition of cultural practices within teams, departments, professions, organizations, and strategies to maximize engagement.

Human factors in escalating acute ward care: a qualitative evidence synthesis.

BACKGROUND: Identifying how human factors affect clinical staff recognition and managment of the deteriorating ward patient may inform process improvements. We systematically reviewed the literature to identify (1) how human factors affect ward care escalation (2) gaps in the current literature and (3) critique literature methodologies. METHODS: We undertook a Qualitative Evidence Synthesis of care escalation studies. We searched MEDLINE, EMBASE and CINHAL from inception to September 2019. We used the Critical Appraisal Skills Programme and the Grading of Recommendations Assessment-Development and Evaluation and Confidence in Evidence from Reviews of Qualitative Research tool to assess study quality. RESULTS: Our search identified 24 studies meeting the inclusion criteria. Confidence in findings was moderate (20 studies) to high (4 studies). In 16 studies, the ability to recognise changes in the patient's condition (soft signals), including skin colour/temperature, respiratory pattern, blood loss, personality change, patient complaint and fatigue, improved the ability to escalate patients. Soft signals were detected through patient assessment (looking/listening/feeling) and not Early Warning Scores (eight studies). In contrast, 13 studies found a high workload and low staffing levels reduced staff's ability to detect patient deterioration and escalate care. In eight studies quantifiable deterioration evidence (Early Warning Scores) facilitated escalation communication, particularly when referrer/referee were unfamiliar. Conversely, escalating concerning non-triggering patients was challenging but achieved by some clinical staff (three studies). Team decision making facilitated the clinical escalation (six studies). CONCLUSIONS: Early Warning Scores have clinical benefits but can sometimes impede escalation in patients not meeting the threshold. Staff use other factors (soft signals) not captured in Early Warning Scores to escalate care. The literature supports strategies that improve the escalation process such as good patient assessment skills. PROSPERO REGISTRATION NUMBER: CRD42018104745.

Non-contact vital sign monitoring of patients in an intensive care unit: A human factors analysis of staff expectations.

BACKGROUND: Infra-red and thermal imaging enable wireless systems to monitor patients' vital signs and absence of wires may improve patient experiences. No studies have explored staff perceptions of the concept of this specific type of technology in the adult population. Understanding existing working systems before introducing technology could improve adoption. METHODS: We conducted semi-structured interviews with Intensive Care Unit (ICU) staff exploring perceptions of wireless patient monitoring. We used the Systems Engineering Initiative for Patient Safety (SEIPS) model to guide thematic analysis. RESULTS: We identified usability themes relating to staff perceptions of current patient monitoring experiences, staff perceptions of patient/relative expectations of ICU care, troubleshooting, hierarchy of monitoring, and consensus of trust. CONCLUSION: The concept of wireless monitoring has perceived benefits for patients and staff. The Systems Engineering Initiative for Patient Safety model guided a systems-based exploratory evaluation. Results highlight the social and environmental factors which may influence usability, adoption, or abandonment of wireless technology in the ICU.

Public involvement in the governance of population-level biomedical research: unresolved questions and future directions.

Population-level biomedical research offers new opportunities to improve population health, but also raises new challenges to traditional systems of research governance and ethical oversight. Partly in response to these challenges, various models of public involvement in research are being introduced. Yet, the ways in which public involvement should meet governance challenges are not well understood. We conducted a qualitative study with 36 experts and stakeholders using the World Café method to identify key governance challenges and explore how public involvement can meet these challenges. This brief report discusses four cross-cutting themes from the study: the need to move beyond individual consent; issues in benefit and data sharing; the challenge of delineating and understanding publics; and the goal of clarifying justifications for public involvement. The report aims to provide a starting point for making sense of the relationship between public involvement and the governance of population-level biomedical research, showing connections, potential solutions and issues arising at their intersection. We suggest that, in population-level biomedical research, there is a pressing need for a shift away from conventional governance frameworks focused on the individual and towards a focus on collectives, as well as to foreground ethical issues around social justice and develop ways to address cultural diversity, value pluralism and competing stakeholder interests. There are many unresolved questions around how this shift could be realised, but these unresolved questions should form the basis for developing justificatory accounts and frameworks for suitable collective models of public involvement in population-level biomedical research governance.

Implementing a system for the real-time risk assessment of patients considered for intensive care.

BACKGROUND: Delay in identifying deterioration in hospitalised patients is associated with delayed admission to an intensive care unit (ICU) and poor outcomes. For the HAVEN project (HICF ref.: HICF-R9-524), we have developed a mathematical model that identifies deterioration in hospitalised patients in real time and facilitates the intervention of an ICU outreach team. This paper describes the system that has been designed to implement the model. We have used innovative technologies such as Portable Format for Analytics (PFA) and Open Services Gateway initiative (OSGi) to define the predictive statistical model and implement the system respectively for greater configurability, reliability, and availability. RESULTS: The HAVEN system has been deployed as part of a research project in the Oxford University Hospitals NHS Foundation Trust. The system has so far processed > 164,000 vital signs observations and > 68,000 laboratory results for > 12,500 patients and the algorithm generated score is being evaluated to review patients who are under consideration for transfer to ICU. No clinical decisions are being made based on output from the system. The HAVEN score has been computed using a PFA model for all these patients. The intent is that this score will be displayed on a graphical user interface for clinician review and response. CONCLUSIONS: The system uses a configurable PFA model to compute the HAVEN score which makes the system easily upgradable in terms of enhancing systems' predictive capability. Further system enhancements are planned to handle new data sources and additional management screens.

Measuring sleep in the intensive care unit: Electroencephalogram, actigraphy, or questionnaire?

BACKGROUND: Studies consistently report deranged sleep in patients admitted to intensive care unit. Poor sleep has harmful physical and cognitive effects, and an evidence-based intervention to improve sleep is needed. It is, however, difficult to measure sleep in the intensive care unit. 'Gold standard' monitoring (polysomnography) is unsuitable for usual care. METHODS: We collected concurrent sleep data from electroencephalograph recordings, activity monitoring, and nurse- and patient-completed Richards-Campbell Sleep Questionnaires (RCSQ). RESULTS: Electroencephalograph data (n = 34) confirm poor sleep. Individual bouts last approximately 1 min and around 2 h of sleep overnight is common. Correlation between electroencephalograph, self-report, nurse-report, actigraphy and overall activity score is low (ρ = 0.123 (n = 24), 0.127 (n = 22), and 0.402 and - 0.201 (n = 13), respectively). Correlation between nurse and patient assessment is limited (ρ = 0.537 (n = 444)). CONCLUSIONS: No current method of sleep monitoring seems suitable in the intensive care unit. However, to facilitate comparison across studies, the patient-completed RCSQ seems the most meaningful measure.

How human factors affect escalation of care: a protocol for a qualitative evidence synthesis of studies.

INTRODUCTION: Failure to rescue is defined as mortality after complications during hospital care. Incidence ranges 10.9%-13.3% and several national reports such as National Confidential Enquiry into Patient Outcomes and Death and National Institute of Clinical Excellence CG 50 highlight failure to rescue as a significant problem for safe patient care.To avoid failure to rescue events, there must be successful escalation of care. Studies indicate that human factors such as situational awareness, team working, communication and a culture promoting safety contribute to avoidance of failure to rescue events. Understanding human factors is essential to developing work systems that mitigate barriers and facilitate prompt escalation of care. This qualitative evidence synthesis will identify and synthesise what is known about the human factors that affect escalation of care. METHODS AND ANALYSIS: We will search MEDLINE (Ovid), EMBASE (Ovid) and CINAHL, between database inception and 2018, for studies describing human factors affecting failure to rescue and/or care escalation. A search strategy was developed by two researchers and a medical librarian. Only studies exploring in-hospital (ward) populations using qualitative data collection methods will be included. Screening will be conducted by two researchers. We are likely to undertake a thematic synthesis, using the Thomas and Harden framework. Selected studies will be assessed for quality, rigour and limitations. Two researchers will extract and thematically synthesise codes using a piloted data extraction tool to develop analytical themes. ETHICS AND DISSEMINATION: The qualitative evidence synthesis will use available published literature and no ethical approval is required. This synthesis will be limited by the quality of studies, rigour and reproducibility of study findings. Results will be published in a peer-reviewed journal, publicised at conferences and on social media. PROSPERO REGISTRATION NUMBER: CRD42018104745.