Success Factors Facilitating Care During Escalation (the SUFFICE study)

Ede, J., Watkinson, P., Endacott, R., (2021) Protocol for a mixed methods exploratory study of success factors to escalation of care: the SUFFICE study. medRxiv 2021.11.01.21264875. Ede J, Petrinic T, Westgate V, Darbyshire J, Endacott R, Watkinson PJ. (2021) Human factors in escalating acute ward care: a qualitative evidence synthesis. BMJ Open Qual 10. Bedford, J. P., Ede, J. and Watkinson, P. J. (2021) ‘Triggers for new-onset atrial fibrillation in critically ill patients’, Intensive and Critical Care Nursing. Elsevier Ltd, 67, p. 103114. doi: 10.1016/j.iccn.2021.103114. Ede, J. et al. (2023) ‘Patient and public involvement and engagement (PPIE) in research: The Golden Thread’, Nursing in critical care, (April), pp. 16–19. doi: 10.1111/nicc.12921. Ede, J., Hutton, R., Watkinson, P., Kent, B. and Endacott, R. (2023) ‘Improving escalation of deteriorating patients through cognitive task analysis: Understanding differences between work-as-prescribed and work-as-done’, International Journal of Nursing Studies.BACKGROUND: In the United Kingdom, there continues to be preventable National Health Service (NHS) patient deaths. Contributory factors include inadequate recognition of deterioration, poor monitoring, or delayed escalation to a higher level of care. Strategies to improve care escalation, such as vital sign scoring systems and specialist teams who manage deterioration events, have shown variable impact on patient mortality. The need for greater care improvements has consistently been identified in NHS care reviews as well as patient stories. Furthermore, current research informing escalation improvements predominantly comes from examining failure to rescue events, neglecting what can be learned from rescue or successful escalation. AIM: The focus of this study was to address this knowledge gap by examining rescue and escalation events, and from this, to develop a Framework of Escalation Success Factors that can underpin a multi-faceted intervention to improve outcomes for deteriorating patients. METHODS: Escalation success factors, hospital and patient data were collected in a mixed methods, multi-site exploratory sequential study. Firstly, 151 ward care escalation events were observed to generate a theoretical understanding of the process. To identify escalation success factors, 390 care records were also reviewed from unwell ward patients in whom an Intensive Care Unit admission was avoided and compared to the records for patients who became unwell on the ward, admitted to an Intensive Care Unit, and died. Finally, thirty Applied Cognitive Task Analysis interviews were conducted with clinical experts (defined as greater than four years’ experience) including Ward Nurses (n= 7), Outreach Nurses (n= 5), Nurse Managers (n=5), Physiotherapists (n=4), Sepsis Nurses (n=3), Advanced Nurse Practitioners and Educators (n=2), Advance Clinical Practitioners (n=2), Nurse Consultant (n=1) and Doctor (n=1) to examine process of escalation in a Functional Resonance Analysis Model. RESULTS: In Phase 1, over half (n= 77, 51%) of the 151 escalation events observed were not initiated through an early warning score but other clinical concerns. The data demonstrated four escalation communication phenotypes (Informative, Outcome Focused, General Concern and Spontaneous Interaction) utilised by staff in different clinical contexts for different escalation purposes. In Phase 2, the 390 ward patient care record reviews (Survivors n=340, Non-survivors admitted to ICU n=50) identified that care and quality of escalation in the Non-survivor’s group was better overall than those that survived. Reviews also identified success factors present within deterioration events including Visibility, Monitoring, Adaptability, and Adjustments, not dissimilar to characteristics of high reliability organisations. Finally, Phase 3 interview data were dynamically modelled in a Functional Resonance Analysis Method. This illustrated differences in the number of escalation tasks contained in the early warning scoring system (n=8) compared to how escalation is successfully completed by clinical staff (n=24). Interview participants identified that 28% (9/32) of these tasks were cognitively difficult, also indicating how they overcome system complexity and challenges to successfully escalate. Interactions between escalation tasks were also examined, including Interdependence (how one affects another), Criticality (how many downstream tasks are initiated), Preconditions (what system factors need to be present), and Variability (factors which affect output reliability). This approach developed a system-focused understanding of escalation and signposted to process improvements. CONCLUSION: This research uniquely contributes to international evidence by presenting new elements to escalation of care processes. This includes indicating how frequently early warning scores trigger an escalation, the different ways in which escalation is communicated, that patient outcomes may inaccurately portray the quality of care delivered and examining the interaction between escalation tasks can identify areas of improvement. This is the first study to develop a preliminary Framework of Escalation Success Factors, which will be refined and used to underpin evidenced based care improvements. A key recommendation would be for organisations to use, when tested, the Framework of Escalation Success Factors to make system refinements that will promote successful escalation of care. PPI: This study has had Patient and Public Involvement and Engagement (PPIE) through a SUFFICE PPI Advisory Group

COVID-19 and patient safety in intensive care : what can we learn?

In March 2020, the World Health Organization (WHO) declared Severe Acute Respiratory Syndrome Coronavirus (COVID-19) a worldwide pandemic. An influx of patients with COVID-19-related critical illness necessitated rapid changes in care strategies to address overwhelming intensive care unit (ICU) service demands, the continued care of non-COVID-19 patients, and mitigate viral spread. These unparalleled challenges highlighted the safety critical nature of nursing, with patient safety being core. As the world recovers from the pandemic, it is vital we reflect on patient using a systems approach, to identify areas of learning (Komashie, et al., 2021). This article outlines key COVID-19 ICU safety impacts to highlight opportunities for learning and inform future ICU patient’s care

COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets

The availability of well-characterized neuroimaging data with large numbers of subjects, especially for clinical populations, is critical to advancing our understanding of the healthy and diseased brain. Such data enables questions to be answered in a much more generalizable manner and also has the potential to yield solutions derived from novel methods that were conceived after the original studies’ implementation. Though there is currently growing interest in data sharing, the neuroimaging community has been struggling for years with how to best encourage sharing data across brain imaging studies. With the advent of studies that are much more consistent across sites (e.g., resting functional magnetic resonance imaging, diffusion tensor imaging, and structural imaging) the potential of pooling data across studies continues to gain momentum. At the mind research network, we have developed the collaborative informatics and neuroimaging suite (COINS; http://coins.mrn.org) to provide researchers with an information system based on an open-source model that includes web-based tools to manage studies, subjects, imaging, clinical data, and other assessments. The system currently hosts data from nine institutions, over 300 studies, over 14,000 subjects, and over 19,000 MRI, MEG, and EEG scan sessions in addition to more than 180,000 clinical assessments. In this paper we provide a description of COINS with comparison to a valuable and popular system known as XNAT. Although there are many similarities between COINS and other electronic data management systems, the differences that may concern researchers in the context of multi-site, multi-organizational data sharing environments with intuitive ease of use and PHI security are emphasized as important attributes

Ambulatory blood pressure monitoring using telemedicine: proof-of-concept cohort and failure modes and effects analyses

Background: The COVID-19 pandemic has accelerated adoption of remote consulting in healthcare. Despite opportunities posed by telemedicine, most hypertension services in Europe have suspended ambulatory blood pressure monitoring (ABPM). Methods: We examined the process and performance of remotely delivered ABPM using two methodologies: firstly, a Failure Modes and Effects Analysis (FMEA) and secondly, a quantitative analysis comparing ABPM data from a subgroup of 65 participants of the Screening for Hypertension in the INpatient Environment (SHINE) diagnostic accuracy study. The FMEA was performed over seven sessions from February to March 2021, with a multidisciplinary team comprising a patient representative, a research coordinator with technical expertise and four research clinicians. Results: The FMEA identified a single high-risk step in the remote ABPM process. This was cleaning of monitoring equipment in the context of the COVID-19 pandemic, unrelated to the remote setting. A total of 14 participants were scheduled for face-to-face ABPM appointments, before the UK March 2020 COVID-19 lockdown; 62 were scheduled for remote ABPM appointments since emergence of the COVID-19 pandemic between November 2020 and August 2021. A total of 65 (88%) participants completed ABPMs; all obtained sufficient successful measurements for interpretation. For the 10 participants who completed face-to-face ABPM, there were 402 attempted ABPM measurements and 361 (89%) were successful. For the 55 participants who completed remote ABPM, there were 2516 attempted measurements and 2214 (88%) were successful. There was no significant difference in the mean per-participant error rate between face-to-face (0.100, SD 0.009) and remote (0.143, SD 0.132) cohorts (95% CI for the difference -0.125 to 0.045 and two-tailed P-value 0.353). Conclusions: We have demonstrated that ABPM can be safely and appropriately provided in the community remotely and without face-to-face contact, using video technology for remote fitting appointments, alongside courier services for delivery of equipment to participants

The use of wearable pulse oximeters in the prompt detection of hypoxemia and during movement: diagnostic accuracy study

Background: Commercially available wearable (ambulatory) pulse oximeters have been recommended as a method for managing patients at risk of physiological deterioration, such as active patients with COVID-19 disease receiving care in hospital isolation rooms; however, their reliability in usual hospital settings is not known. Objective: We report the performance of wearable pulse oximeters in a simulated clinical setting when challenged by motion and low levels of arterial blood oxygen saturation (SaO2). Methods: The performance of 1 wrist-worn (Wavelet) and 3 finger-worn (CheckMe O2+, AP-20, and WristOx2 3150) wearable, wireless transmission–mode pulse oximeters was evaluated. For this, 7 motion tasks were performed: at rest, sit-to-stand, tapping, rubbing, drinking, turning pages, and using a tablet. Hypoxia exposure followed, in which inspired gases were adjusted to achieve decreasing SaO2 levels at 100%, 95%, 90%, 87%, 85%, 83%, and 80%. Peripheral oxygen saturation (SpO2) estimates were compared with simultaneous SaO2 samples to calculate the root-mean-square error (RMSE). The area under the receiver operating characteristic curve was used to analyze the detection of hypoxemia (ie, SaO2<90%). Results: SpO2 estimates matching 215 SaO2 samples in both study phases, from 33 participants, were analyzed. Tapping, rubbing, turning pages, and using a tablet degraded SpO2 estimation (RMSE>4% for at least 1 device). All finger-worn pulse oximeters detected hypoxemia, with an overall sensitivity of ≥0.87 and specificity of ≥0.80, comparable to that of the Philips MX450 pulse oximeter. Conclusions: The SpO2 accuracy of wearable finger-worn pulse oximeters was within that required by the International Organization for Standardization guidelines. Performance was degraded by motion, but all pulse oximeters could detect hypoxemia. Our findings support the use of wearable, wireless transmission–mode pulse oximeters to detect the onset of clinical deterioration in hospital settings. Trial Registration: ISRCTN Registry 61535692; http://www.isrctn.com/ISRCTN61535692 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-03440