Implementation of a critical care outreach team in a children's hospital.

Introduction: Proactive surveillance by a critical care outreach team (CCOT) can promote early recognition of deterioration in hospitalized patients but is uncommon in pediatric rapid response systems (RRSs). After our children's hospital introduced a CCOT in 2019, we aimed to characterize early implementation outcomes. We hypothesized that CCOT rounding would identify additional children at risk for deterioration. Methods: The CCOT, staffed by a dedicated critical care nurse (RN), respiratory therapist, and attending, conducts daily in-person rounds with charge RNs on medical-surgical units, to screen RRS-identified high-risk patients for deterioration. In this prospective study, observers tracked rounds discussion content, participation, and identification of new high-risk patients. We compared 'identified-patient-discussions' (IPD) about RRS-identified patients, and 'new-patient-discussions' (NPD) about new patients with Fisher's exact test. For new patients, we performed thematic analysis of clinical data to identify deterioration related themes. Results: During 348 unit-rounds over 20 days, we observed 383 discussions - 35 (9%) were NPD. Frequent topics were screening for clinical concerns (374/383, 98%), active clinical concerns (147/383, 39%), and watcher activation (66/383, 17%). Most discussions only included standard participants (353/383, 92%). Compared to IPD, NPD more often addressed active concerns (74.3% vs 34.8%, p < 0.01) and staffing resource concerns (5.7% vs 0.6%, p < 0.04), and more often incorporated extra participants (25.7% vs 6%, p < 0.01). In thematic analysis of 33 new patients, most (29/33, 88%) had features of deterioration. Conclusion: A successfully implemented CCOT enhanced identification of clinical deterioration not captured by existing RRS resources. Future work will investigate its impact on operational safety and patient-centered outcomes.

Parents' Trigger Tool for Children with Medical Complexity - PAT-CMC: Development of a recognition tool for clinical deterioration at home.

AIM: To develop a trigger tool for parents and lay caregivers of children with medical complexity (CMC) at home and to validate its content. DESIGN: This was a multi-method study, using qualitative data, a Delphi method and a concept mapping approach. METHODS: A three-round electronic Delphi was performed from December 2021 to April 2022 with a panel of 23 expert parents and 30 healthcare providers, supplemented by a preliminary qualitative exploration of children's signs of deterioration and three consensus meetings to develop the PArents' Trigger Tool for Children with Medical Complexity (PAT-CMC). Cognitive interviews with parents were performed to assess the comprehensiveness and comprehensibility of the tool. The COREQ checklist, the COSMIN guidelines and the CREDES guidelines guided the reporting respectively of the qualitative study, the development and content validity of the trigger tool and the Delphi study. RESULTS: The PAT-CMC was developed and its content validated to recognize clinical deterioration at home. The tool consists of 7 main clusters of items: Breathing, Heart, Devices, Behaviour, Neuro-Muscular, Nutrition/Hydration and Other Concerns. A total of 23 triggers of deterioration were included and related to two recommendations for escalation of care, using a traffic light coding system. CONCLUSION: Priority indicators of clinical deterioration of CMC were identified and integrated into a validated trigger tool designed for parents or other lay caregivers at home, to recognize signs of acute severe illness and initiate healthcare interventions. IMPACT: The PAT-CMC was developed to guide families in recognizing signs of deterioration in CMC and has potential for initiating an early escalation of care. This tool may also be useful to support education provided by healthcare providers to families before hospital discharge. PATIENT OR PUBLIC CONTRIBUTION: Parents of CMC were directly involved in the selection of relevant indicators of children's clinical deterioration and the development of the trigger tool. They were not involved in the design, conducting, reporting or dissemination plans of this research.

Impact of dynamic parameter of trends in vital signs on the prediction of serious events in hospitalized patients -a retrospective observational study.

Aim: Although early detection of patients' deterioration may improve outcomes, most of the detection criteria use on-the-spot values of vital signs. We investigated whether adding trend values over time enhanced the ability to predict adverse events among hospitalized patients. Methods: Patients who experienced adverse events, such as unexpected cardiac arrest or unplanned ICU admission were enrolled in this retrospective study. The association between the events and the combination of vital signs was evaluated at the time of the worst vital signs 0-8 hours before events (near the event) and at 24-48 hours before events (baseline). Multivariable logistic analysis was performed, and the area under the receiver operating characteristic curve (AUC) was used to assess the prediction power for adverse events among various combinations of vital sign parameters. Results: Among 24,509 in-patients, 54 patients experienced adverse events(cases) and 3,116 control patients eligible for data analysis were included. At the timepoint near the event, systolic blood pressure (SBP) was lower, heart rate (HR) and respiratory rate (RR) were higher in the case group, and this tendency was also observed at baseline. The AUC for event occurrence with reference to SBP, HR, and RR was lower when evaluated at baseline than at the timepoint near the event (0.85 [95%CI: 0.79-0.92] vs. 0.93 [0.88-0.97]). When the trend in RR was added to the formula constructed of baseline values of SBP, HR, and RR, the AUC increased to 0.92 [0.87-0.97]. Conclusion: Trends in RR may enhance the accuracy of predicting adverse events in hospitalized patients.

Higher baseline serum bilirubin levels are associated with increased risk of early neurological deterioration in women with acute ischemic stroke.

Background and objectives: Early neurological deterioration (END) occurs in up to one-third of patients with acute ischemic stroke (AIS) and associated with poor outcome. The role of serum bilirubin in END remains controversial. This study aims to investigate the association of total bilirubin (TBIL), direct bilirubin (DBIL) and indirect bilirubin (IBIL) with END. Methods: This study was a cross-sectional retrospective study with 344 AIS patients enrolled. We retrospectively reviewed consecutive AIS patients with END through a medical record retrieval system and enrolled patients as control randomly from the AIS patients without END at the same period. The bilirubin levels were compared between the END group and No END group. The correlations of bilirubin with END were assessed according to the bilirubin tertiles on the cohort of different genders. Results: In women, as the bilirubin level increased, the occurrence of END showed an increasing trend. The linear association was significant based on the tertiles of all bilirubin types (TBIL p = 0.003; DBIL p = 0.025; IBIL p = 0.025), while in men no similar trend was observed. After adjustment for confounders, higher TBIL (p for trend 0.009) and DBIL (p for trend 0.033) levels were associated with increased risk of END in women. The adjusted OR for T3 relative to T1 was 5.240 (95% CI 1.496-18.347) in TBIL and 3.549 (95% CI 1.089-11.566) in DBIL. Multivariate logistic regression showed that DBIL was independently associated with END in women (OR 1.717, 95% CI 1.106-2.666). The study also found that DBIL was superior to TBIL and IBIL in prediction of END occurrence in women, with greater predictive value. Discussion: There were gender differences in the relationship between bilirubin and END, and DBIL level was positively associated with END occurrence in women, not in men. DBIL had greater incremental predictive value for END than TBIL and IBIL.

General ward nurses detection and response to clinical deterioration in three hospitals at the Kenyan coast: a convergent parallel mixed methods study.

BACKGROUND: In low and middle-income countries like Kenya, critical care facilities are limited, meaning acutely ill patients are managed in the general wards. Nurses in these wards are expected to detect and respond to patient deterioration to prevent cardiac arrest or death. This study examined nurses' vital signs documentation practices during clinical deterioration and explored factors influencing their ability to detect and respond to deterioration. METHODS: This convergent parallel mixed methods study was conducted in the general medical and surgical wards of three hospitals in Kenya's coastal region. Quantitative data on the extent to which the nurses monitored and documented the vital signs 24 h before a cardiac arrest (death) occurred was retrieved from patients' medical records. In-depth, semi-structured interviews were conducted with twenty-four purposefully drawn registered nurses working in the three hospitals' adult medical and surgical wards. RESULTS: This study reviewed 405 patient records and found most of the documentation of the vital signs was done in the nursing notes and not the vital signs observation chart. During the 24 h prior to death, respiratory rate was documented the least in only 1.2% of the records. Only a very small percentage of patients had any vital event documented for all six-time points, i.e. four hourly. Thematic analysis of the interview data identified five broad themes related to detecting and responding promptly to deterioration. These were insufficient monitoring of vital signs linked to limited availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork constraints among healthcare workers. CONCLUSION: The study showed that nurses did not consistently monitor and record vital signs in the general wards. They also worked in suboptimal ward environments that do not support their ability to promptly detect and respond to clinical deterioration. The findings illustrate the importance of implementation of standardised systems for patient assessment and alert mechanisms for deterioration response. Furthermore, creating a supportive work environment is imperative in empowering nurses to identify and respond to patient deterioration. Addressing these issues is not only beneficial for the nurses but, more importantly, for the well-being of the patients they serve.

Importance of specific vital signs in nurses' recognition and response to deteriorating patients: A scoping review.

AIM(S): To explore the published research related to nurses' documentation and use of vital signs in recognising and responding to deteriorating patients. DESIGN: Scoping review of international, peer-reviewed research studies. DATA SOURCES: Cumulative Index to Nursing and Allied Health Literature Complete, Medline Complete, American Psychological Association PsycInfo and Excerpta Medica were searched on 25 July 2023. REPORTING METHOD: Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. RESULTS: Of 3880 potentially eligible publications, 32 were included. There were 26 studies of nurses' vital sign documentation: 21 adults and five paediatric. The most and least frequently documented vital signs were blood pressure and respiratory rate respectively. Seven studies focused on vital signs and rapid response activation or afferent limb failure. Five studies of vital signs used to trigger the rapid response system showed heart rate was the most frequent and respiratory rate and conscious state were the least frequent. Heart rate was least likely and oxygen saturation was most likely to be associated with afferent limb failure (n = 4 studies). CONCLUSION: Despite high reliance on using vital signs to recognise clinical deterioration and activate a response to deteriorating patients in hospital settings, nurses' documentation of vital signs and use of vital signs to activate rapid response systems is poorly understood. There were 21studies of nurses' vital sign documentation in adult patients and five studies related to children. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: A deeper understanding of nurses' decisions to assess (or not assess) specific vital signs, analysis of the value or importance nurses place (or not) on specific vital sign parameters is warranted. The influence of patient characteristics (such as age) or the clinical practice setting, and the impact of nurses' workflows of vital sign assessment warrants further investigation. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Improvement in Functional Outcome from 6 to 12 Months After Moderate and Severe Traumatic Brain Injury Is Frequent, But May Not Be Detected With the Glasgow Outcome Scale Extended.

The aims of this study were (1) to report outcome and change in outcome in patients with moderate and severe traumatic brain injury (mo/sTBI) between 6 and 12 months post-injury as measured by the Glasgow Outcome Scale Extended (GOSE), (2) to explore if demographic/injury-related variables can predict improvement in GOSE score, and (3) to investigate rate of improvement in Disability Rating Scale (DRS) score, in patients with a stable GOSE. All surviving patients ≥16 years of age who were admitted with mo/sTBI (Glasgow Coma Scale [GCS] score ≤13) to the regional trauma center in Central Norway between 2004 and 2019 were prospectively included (n = 439 out of 503 eligible). GOSE and DRS were used to assess outcome. Twelve-months post-injury, 13% with moTBI had severe disability (GOSE 2-4) versus 27% in sTBI, 26% had moderate disability (GOSE 5-6) versus 41% in sTBI and 62% had good recovery (GOSE 7-8) versus 31% in sTBI. From 6 to 12 months post-injury, 27% with moTBI and 32% with sTBI had an improvement, whereas 6% with moTBI and 6% with sTBI had a deterioration in GOSE score. Younger age and higher GCS score were associated with improved GOSE score. Improvement was least frequent for patients with a GOSE score of 3 at 6 months. In patients with a stable GOSE score of 3, an improvement in DRS score was observed in 22 (46%) patients. In conclusion, two thirds and one third of patients with mo/sTBI, respectively, had a good recovery. Importantly, change, mostly improvement, in GOSE score between 6 and 12 months was frequent and argues against the use of 6 months outcome as a time end-point in research. The GOSE does, however, not seem to be sensitive to actual change in function in the lower categories and a combination of outcome measures may be needed to describe the consequences after TBI.

The Effect of Modified Early Warning Score (MEWS) and Nursing Guide Application on Postoperative Patient Outcomes: A Randomized Controlled Study.

PURPOSE: The aim of this study is to determine the effect of nursing guide application (NGA) on patient outcomes in patients followed up according to the modified early warning score (MEWS) in the postoperative period. DESIGN: A randomized controlled clinical trial. METHODS: The sample of the study consisted of 252 patients who underwent surgical intervention under general anesthesia in a university hospital between July 29, 2022, and October 31, 2022. FINDINGS: Results showed that the development of complications was less in the study group (SG) compared to the control group (CG) during anesthesia (P = .027), in the postanesthesia care unit (PACU) (P = .017), and in the clinic (P = .001). It was found that the duration of stay in PACU in the CG was significantly shorter than in the study group (P < .001), and as the duration of stay in PACU in CG decreased, the MEWS increased (r = -0.201, P = .024). We found that there were fewer patients transferred to the intensive care unit (ICU) after PACU (P = .007), the MEWS was lower, and the number of nursing interventions applied to patients was higher (P < .05). CONCLUSIONS: In patients followed up according to MEWS, NGA had a positive effect on preventing the development of complications and shortening the intervention time for complications, decreasing ICU admission, decreasing MEWS and increasing the number of nursing interventions. Based on the results, it may be recommended to use MEWS+NGA in the early postoperative period as it positively affects patient outcomes.

Infectious and sepsis presentations to, and hospital admissions from emergency departments in Victoria, Australia.

OBJECTIVE: To investigate the frequency and outcomes of adult infectious and sepsis presentations to, and hospital admissions from, Emergency Departments (EDs) in Victoria, Australia. METHODS: Retrospective cohort study using the Victorian Emergency Minimum Dataset and Victorian Admitted Episodes Dataset. We included adults (age ≥ 18 years) presenting to an ED, or admitted to hospital from ED in Victoria between July 2017 and June 2018. One-year mortality was analysed until June 2019 using the Victorian Death Index, and ICD-10 coding was used to identify cases. RESULTS: Among 1.28 million ED presentations over 1 year, 12.00% and 0.45% were coded with infectious and sepsis diagnoses, respectively. Despite having lower triage categories, patients with infections were more likely to be admitted to hospital (50.4% vs 44.9%), but not directly to ICU (0.8%). Patients coded with sepsis were assigned higher triage categories and required hospital admission much more frequently (96.4% vs 44.9%), including to ICU (15.9% vs 0.8%). Patients presenting with infections and sepsis had increased risk of 1-year mortality (adjusted hazard ratio 1.44 and 4.13, respectively). Of the 648 280 hospital admissions from the ED, infection and sepsis were coded in 23.69% and 2.66%, respectively, and the adjusted odds ratio for 1-year mortality were 1.64 and 4.79, respectively. CONCLUSIONS: Infections and sepsis are common causes of presentation to, and admission from the ED in Victoria. Such patients experience higher mortality than non-infectious patients, even after adjusting for age. There is a need to identify modifiable factors contributing to these outcomes.

Using clinical simulation to assess a new paediatric ESCALATION system education package: Empirical research mixed methods.

AIM: The aim of the study was to assess the suitability of an online education package to prepare health professionals to use a new paediatric early warning system. DESIGN: Quasi-experimental mixed methods using co-production. METHODS: Participants completed the Package and participated in up to four clinical scenarios. Data were collected using self-report surveys, and during clinical scenarios; escalation of care, documentation, family involvement, communication handovers were assessed, and recorded debriefings were thematically analysed. Data were integrated using tabulated joint displays. RESULTS: Eleven nurses and three doctors were recruited from three mixed adult and paediatric hospitals. Following completion of the Package and clinical scenarios 13/14 (93%) participants agreed preparedness and confidence to use the ESCALATION System had increased. For 53% handovers, the communication framework was followed, for 79% charts, documentation was complete. Participants engaged with the parent (actor) for 97% scenario interactions. The Package was effective and participation in clinical scenarios appeared to enhance learning. PATIENT OR PUBLIC CONTRIBUTION: Consumers participated in the steering group overseeing the study and in the expert panel who reviewed the education package and clinical scenarios.

Transforming nursing assessment in acute hospitals: A cluster randomised controlled trial of an evidence-based nursing core assessment (the ENCORE trial).

BACKGROUND: Patient safety is threatened when early signs of clinical deterioration are missed or not acted upon. This research began as a clinical-academic partnership established around a shared concern of nursing physical assessment practices on general wards and delayed recognition of clinical deterioration. The outcome was the development of a complex intervention facilitated at the ward level for proactive nursing surveillance. METHODS: The evidence-based nursing core assessment (ENCORE) trial was a pragmatic cluster-randomised controlled trial. We hypothesised that ward intervention would reduce the incidence of patient rescue events (medical emergency team activations) and serious adverse events. We randomised 29 general wards in a 1:2 allocation, across 5 Australian hospitals to intervention (n = 10) and usual care wards (n = 19). Skilled facilitation over 12 months enabled practitioner-led, ward-level practice change for proactive nursing surveillance. The primary outcome was the rate of medical emergency team activations and secondary outcomes were unplanned intensive care unit admissions, on-ward resuscitations, and unexpected deaths. Outcomes were prospectively collected for 6 months following the initial 6 months of implementation. Analysis was at the patient level using generalised linear mixed models to account for clustering by ward. RESULTS: We analysed 29,385 patient admissions to intervention (n = 11,792) and control (n = 17,593) wards. Adjusted models for overall effects suggested the intervention increased the rate of medical emergency team activations (adjusted incidence rate ratio 1.314; 95 % confidence interval 0.975, 1.773), although the confidence interval was compatible with a marginal decrease to a substantial increase in rate. Confidence intervals for secondary outcomes included a range of plausible effects from benefit to harm. However, considerable heterogeneity was observed in intervention effects by patient comorbidity. Among patients with few comorbid conditions in the intervention arm there was a lower medical emergency team activation rate and decreased odds of unexpected death. Among patients with multimorbidity in the intervention arm there were higher rates of medical emergency team activation and intensive care unit admissions. CONCLUSION: Trial outcomes have refined our assumptions about the impact of the ENCORE intervention. The intervention appears to have protective effects for patients with low complexity where frontline teams can respond locally. It also appears to have redistributed medical emergency team activations and unplanned intensive care unit admissions, mobilising higher rates of rescue for patients with multimorbidity. TRIAL REGISTRATION NUMBER: ACTRN12618001903279 (Date of registration: 22/11/2018; First participant recruited: 01/02/2019).

Three Years of Continuous Vital Signs Monitoring on the General Surgical Ward: Is It Sustainable? A Qualitative Study.

Continuous monitoring of vital signs using a wireless wearable device was implemented in 2018 at a surgical care unit of an academic hospital. This study aimed at gaining insight into nurses' and patients' perspectives regarding the use and innovation of a continuous vital signs monitoring system, three years after its introduction. This qualitative study was performed in a surgical, non-intensive care unit of an academic hospital in 2021. Key-user nurses (nurses with additional training and expertise with the device) and patients were selected for semi-structured interviews, and nurses from the ward were selected for a focus group interview using a topic list. Transcripts of the audio tapes were deductively analysed using four dimensions for adoptions of information and communication technologies (ICT) devices in healthcare. The device provided feelings of safety for nurses and patients. Nurses and patients had a few issues with the device, including the size and the battery life. Nurses gained knowledge and skills in using the system for measurement and interpretations. They perceived the system as a tool to improve the recognition of clinical decline. The use of the system could be further developed regarding the technical device's characteristics, nurses' interpretation of the data and the of type of alarms, the information needs of patients, and clarification of the definition and standardization of continuous monitoring. Three years after the introduction, wireless continuous vital signs monitoring is the new standard of care according to the end-users at the general surgical ward.

Risk factors and predicting nomogram for the clinical deterioration of non-severe community-acquired pneumonia.

BACKGROUND: Currently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management. METHOD: A retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Age, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74-0.82) in the training set and 0.75 (95% CI: 0.67-0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability. CONCLUSION: The study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.

Improving escalation of deteriorating patients through cognitive task analysis: Understanding differences between work-as-prescribed and work-as-done.

BACKGROUND: Appropriate care escalation requires the detection and communication of in-hospital patient deterioration. Although deterioration in the ward environment is common, there continue to be patient deaths where problems escalating care have occurred. Learning from the everyday work of health care professionals (work-as-done) and identifying performance variability may provide a greater understanding of the escalation challenges and how they overcome these. The aims of this study were to i) develop a representative model detailing escalation of care ii) identify performance variability that may negatively or positively affect this process and iii) examine linkages between steps in the escalation process. METHODS: Thirty Applied Cognitive Task Analysis interviews were conducted with clinical experts (>4 years' experience) including Ward Nurses (n = 7), Outreach or Sepsis Nurses (n = 8), Nurse Manager or Consultant (n = 6), Physiotherapists (n = 4), Advanced Practitioners (n = 4), and Doctor (n = 1) from two National Health Service hospitals and analysed using Framework Analysis. Task-related elements of care escalation were identified and represented in a Functional Resonance Analysis Model. FINDINGS: The NEWS2's clinical escalation response constitutes eight unique tasks and illustrates work-as-prescribed, but our interview data uncovered an additional 24 tasks (n = 32) pertaining to clinical judgement, decisions or processes reflecting work-as-done. Over a quarter of these tasks (9/32, 28 %) were identified by experts as cognitively challenging with a high likelihood of performance variability. Three out of the nine variable tasks were closely coupled and interdependent within the Functional Resonance Analysis Model ('synthesising data points', 'making critical decision to escalate' and 'identifying interim actions') so representing points of potential escalation failure. Data assimilation from different clinical information systems with poor usability was identified as a key cognitive challenge. CONCLUSION: Our data support the emphasis on the need to retain clinical judgement and suggest that future escalation protocols and audit guidance require in-built flexibility, supporting staff to incorporate their expertise of the patient condition and the clinical environment. Improved information systems to synthesise the required data surrounding an unwell patient to reduce staff cognitive load, facilitate decision-making, support the referral process and identify actions are required. Fundamentally, reducing the cognitive load when assimilating core escalation data allows staff to provide better and more creative care. Study registration (ISRCTN 38850) and ethical approval (REC Ref 20/HRA/3828; CAG-20CAG0106).

Night-time detection and response in relation to deteriorating inpatients: A scoping review.

BACKGROUND: Although detection and response to clinical deterioration have been studied, the range and nature of studies focused on night-time clinical setting remain unclear. AIM: This study aimed to identify and map existing research and findings concerning night-time detection and response to deteriorating inpatients in usual care or research settings. STUDY DESIGN: A scoping review method was used. PubMed, CINAHL, Web of Science, and Ichushi-Web databases were systematically searched. We included studies focusing on night-time detection and response to clinical deterioration. RESULTS: Twenty-eight studies were included. These studies were organized into five categories: night-time medical emergency team or rapid response team (MET/RRT) response, night-time observation using the early warning score (EWS), available resources for physicians' practice, continuous monitoring of specific parameters, and screening for night-time clinical deterioration. The first three categories were related to interventional measures in usual care settings, and relevant findings mainly demonstrated the actual situation and challenges of night-time practice. The final two categories were related to the interventions in the research settings and included innovative interventions to identify at-risk or deteriorating patients. CONCLUSIONS: Systematic interventional measures, such as MET/RRT and EWS, could have been sub-optimally performed at night. Innovations in monitoring technologies or implementation of predictive models could be helpful in improving the detection of night-time deterioration. RELEVANCE TO CLINICAL PRACTICE: This review provides a compilation of current evidence regarding night-time practice concerning patient deterioration. However, a lack of understanding exists on specific and effective practices regarding timely action for deteriorating patients at night.

Time Window for Induced Hypertension in Acute Small Vessel Occlusive Stroke With Early Neurological Deterioration.

BACKGROUND: Therapeutic-induced hypertension treatment (iHTN) is helpful for alleviating early neurological deterioration (END) in acute small vessel occlusive stroke. We examined the time parameters related to iHTN effectiveness in these patients. METHODS: We retrospectively reviewed patients with acute small vessel occlusive stroke who underwent iHTN for END, defined as an increase of ≥2 points in total National Institutes of Health Stroke Scale (NIHSS) score or ≥1 point in motor items of NIHSS. The primary outcome was an early neurological improvement (ENI; a decrease of ≥2 points in total NIHSS score or ≥1 point in motor items of NIHSS), and the secondary outcome was any neurological improvement (a decrease of ≥1 point in the total NIHSS score). We conducted a multivariable logistic regression analysis, adjusting for demographics, risk factors, baseline clinical status, and intervention-related variables. We also generated a restricted cubic spline curve for the END-to-iHTN time cutoff. RESULTS: Among the 1062 patients with small vessel occlusive stroke screened between 2017 and 2021, 136 patients who received iHTN within 24 hours from END were included. The mean age was 65.1 (±12.0) years, and 61.0% were male. Sixty-five (47.8%) patients showed ENI and 77 (56.6%) patients showed any neurological improvement. END-to-iHTN time was significantly shorter in patients with ENI (150 [49-322] versus 290 [97-545] minutes; P=0.018) or any neurological improvement (150 [50-315] versus 300 [130-573] minutes; P=0.002). A 10-minute increase in the time between END and iHTN decreased the odds of achieving ENI (odds ratio, 0.984 [95% CI, 0.970-0.997]; P=0.019) or any neurological improvement (odds ratio, 0.978 [95% CI, 0.964-0.992]; P=0.002). The restricted cubic spline curve showed that the odds ratio of ENI reached its minimum at ≈3 hours. CONCLUSIONS: Among patients with small vessel occlusive stroke with END, a shorter interval between END and the initiation of iHTN was associated with increased odds of achieving neurological improvement. The efficacy of iHTN may be limited to induction within the first 3 hours of END.

Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.

OBJECTIVE: To identify factors influencing implementation of machine learning algorithms (MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a validated implementation framework. MATERIALS AND METHODS: A systematic review of studies of implemented or trialed real-time clinical deterioration prediction MLAs was undertaken, which identified: how MLA implementation was measured; impact of MLAs on clinical processes and patient outcomes; and barriers, enablers and uncertainties within the implementation process. Review findings were then mapped to the SALIENT end-to-end implementation framework to identify the implementation stages at which these factors applied. RESULTS: Thirty-seven articles relating to 14 groups of MLAs were identified, each trialing or implementing a bespoke algorithm. One hundred and seven distinct implementation evaluation metrics were identified. Four groups reported decreased hospital mortality, 1 significantly. We identified 24 barriers, 40 enablers, and 14 uncertainties and mapped these to the 5 stages of the SALIENT implementation framework. DISCUSSION: Algorithm performance across implementation stages decreased between in silico and trial stages. Silent plus pilot trial inclusion was associated with decreased mortality, as was the use of logistic regression algorithms that used less than 39 variables. Mitigation of alert fatigue via alert suppression and threshold configuration was commonly employed across groups. CONCLUSIONS: : There is evidence that real-world implementation of clinical deterioration prediction MLAs may improve clinical outcomes. Various factors identified as influencing success or failure of implementation can be mapped to different stages of implementation, thereby providing useful and practical guidance for implementers.

Clinical deterioration as a nurse sensitive indicator in the out-of-hospital context: A scoping review.

AIMS: To explore and summarise the literature on the concept of 'clinical deterioration' as a nurse-sensitive indicator of quality of care in the out-of-hospital context. DESIGN: The scoping review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review and the JBI best practice guidelines for scoping reviews. METHODS: Studies focusing on clinical deterioration, errors of omission, nurse sensitive indicators and the quality of nursing and midwifery care for all categories of registered, enrolled, or licensed practice nurses and midwives in the out-of-hospital context were included regardless of methodology. Text and opinion papers were also considered. Study protocols were excluded. DATA SOURCES: Data bases were searched from inception to June 2022 and included CINAHL, PsychINFO, MEDLINE, The Allied and Complementary Medicine Database, EmCare, Maternity and Infant Care Database, Australian Indigenous HealthInfoNet, Informit Health and Society Database, JSTOR, Nursing and Allied Health Database, RURAL, Cochrane Library and Joanna Briggs Institute. RESULTS: Thirty-four studies were included. Workloads, education and training opportunities, access to technology, home visits, clinical assessments and use of screening tools or guidelines impacted the ability to recognise, relay information and respond to clinical deterioration in the out-of-hospital setting. CONCLUSIONS: Little is known about the work of nurses or midwives in out-of-hospital settings and their recognition, reaction to and relay of information about patient deterioration. The complex and subtle nature of non-acute deterioration creates challenges in defining and subsequently evaluating the role and impact of nurses in these settings. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Further research is needed to clarify outcome measures and nurse contribution to the care of the deteriorating patient in the out-of-hospital setting to reduce the rate of avoidable hospitalisation and articulate the contribution of nurses and midwives to patient care. IMPACT: What Problem Did the Study Address? Factors that impact a nurse's ability to recognise, relay information and respond to clinical deterioration in the out-of-hospital setting are not examined to date. What Were the Main Findings? A range of factors were identified that impacted a nurse's ability to recognise, relay information and respond to clinical deterioration in the out-of-hospital setting including workloads, education and training opportunities, access to technology, home visits, clinical assessments, use of screening tools or guidelines, and avoidable hospitalisation. Where and on whom will the research have an impact? Nurses and nursing management will benefit from understanding the factors that act as barriers and facilitators for effective recognition of, and responding to, a deteriorating patient in the out-of-hospital setting. This in turn will impact patient survival and satisfaction. REPORTING METHOD: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review guidelines guided this review. The PRISMA-Scr Checklist (Tricco et al., 2018) is included as (supplementary file 1).Data sharing is not applicable to this article as no new data were created or analysed in this study." NO PATIENT OR PUBLIC CONTRIBUTION: Not required as the Scoping Review used publicly available information.

Development and Validation of a Machine Learning Algorithm Using Clinical Pages to Predict Imminent Clinical Deterioration.

BACKGROUND: Early detection of clinical deterioration among hospitalized patients is a clinical priority for patient safety and quality of care. Current automated approaches for identifying these patients perform poorly at identifying imminent events. OBJECTIVE: Develop a machine learning algorithm using pager messages sent between clinical team members to predict imminent clinical deterioration. DESIGN: We conducted a large observational study using long short-term memory machine learning models on the content and frequency of clinical pages. PARTICIPANTS: We included all hospitalizations between January 1, 2018 and December 31, 2020 at Vanderbilt University Medical Center that included at least one page message to physicians. Exclusion criteria included patients receiving palliative care, hospitalizations with a planned intensive care stay, and hospitalizations in the top 2% longest length of stay. MAIN MEASURES: Model classification performance to identify in-hospital cardiac arrest, transfer to intensive care, or Rapid Response activation in the next 3-, 6-, and 12-hours. We compared model performance against three common early warning scores: Modified Early Warning Score, National Early Warning Score, and the Epic Deterioration Index. KEY RESULTS: There were 87,783 patients (mean [SD] age 54.0 [18.8] years; 45,835 [52.2%] women) who experienced 136,778 hospitalizations. 6214 hospitalized patients experienced a deterioration event. The machine learning model accurately identified 62% of deterioration events within 3-hours prior to the event and 47% of events within 12-hours. Across each time horizon, the model surpassed performance of the best early warning score including area under the receiver operating characteristic curve at 6-hours (0.856 vs. 0.781), sensitivity at 6-hours (0.590 vs. 0.505), specificity at 6-hours (0.900 vs. 0.878), and F-score at 6-hours (0.291 vs. 0.220). CONCLUSIONS: Machine learning applied to the content and frequency of clinical pages improves prediction of imminent deterioration. Using clinical pages to monitor patient acuity supports improved detection of imminent deterioration without requiring changes to clinical workflow or nursing documentation.