Implementing an electronic observation and early warning score chart in the emergency department: a feasibility study

Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU: 2023

RATIONALE

Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care hospitals have implemented systems aimed at detecting and responding to such patients.

OBJECTIVES

To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients.

PANEL DESIGN

The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based Clinical Practice Guidelines.

METHODS

We generated actionable questions using the Population, Intervention, Control, and Outcomes (PICO) format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation Approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs).

RESULTS

The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among unselected patients. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system.

CONCLUSIONS

The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Predicting ICU admission and death in the Emergency Department: A comparison of six early warning scores

AIM

To compare the ability of the most used Early Warning Scores (EWS) to identify adult patients at risk of poor outcomes in the emergency department (ED).

METHODS

Single-center, retrospective observational study. We evaluated the digital records of consecutive ED admissions in patients ≥ 18 years from 2010 to 2019 and calculated NEWS, NEWS2, MEWS, RAPS, REMS, and SEWS based on parameters measured on ED arrival. We assessed the discrimination and calibration performance of each EWS in predicting death/ICU admission within 24 hours using ROC analysis and visual calibration. We also measured the relative weight of clinical and physiological derangements that identified patients missed by EWS risk stratification using neural network analysis.

RESULTS

Among 225,369 patients assessed in the ED during the study period, 1941 (0.9%) were admitted to ICU or died within 24 hours. NEWS was the most accurate predictor (area under the receiver operating characteristic [AUROC] curve 0.904 [95% CI 0.805-0.913]), followed by NEWS2 (AUROC 0.901). NEWS was also well calibrated. In patients judged at low risk (NEWS < 2), 359 events occurred (18.5% of the total). Neural network analysis revealed that age, systolic BP, and temperature had the highest relative weight for these NEWS-unpredicted events.

CONCLUSIONS

NEWS is the most accurate EWS for predicting the risk of death/ICU admission within 24 h from ED arrival. The score also had a fair calibration with few events occurring in patients classified at low risk. Neural network analysis suggests the need for further improvements by focusing on the prompt diagnosis of sepsis and the development of practical tools for the measurement of the respiratory rate.

Implementation of Prediction Models in the Emergency Department from an Implementation Science Perspective-Determinants, Outcomes, and Real-World Impact: A Scoping Review

STUDY OBJECTIVE

Prediction models offer a promising form of clinical decision support in the complex and fast-paced environment of the emergency department (ED). Despite significant advancements in model development and validation, implementation of such models in routine clinical practice remains elusive. This scoping review aims to survey the current state of prediction model implementation in the ED and to provide insights on contributing factors and outcomes from an implementation science perspective.

METHODS

We searched 4 databases from their inception to May 20, 2022: MEDLINE (through PubMed), Embase, Scopus, and CINAHL. Articles that reported implementation outcomes and/or contextual determinants under the Reach, Effectiveness, Adoption, Implementation Maintenance (RE-AIM)/Practical, Robust, Implementation, and Sustainability Model (PRISM) framework were included. Characteristics of studies, models, and results of the RE-AIM/PRISM domains were summarized narratively.

RESULTS

Thirty-six reports on 31 implementations were included. The most common prediction models implemented were early warning scores. The most common implementation strategies used were training stakeholders, infrastructural changes, and using evaluative or iterative strategies. Only one report examined ED patients' perspectives, whereas the rest were focused on the experience of health care workers or organizational stakeholders. Key determinants of successful implementation include strong stakeholder engagement, codevelopment of workflows and implementation strategies, education, and usability.

CONCLUSION

Examining ED prediction models from an implementation science perspective can provide valuable insights and help guide future implementations.

Assessing the Usability of a Novel Wearable Remote Patient Monitoring Device for the Early Detection of In-Hospital Patient Deterioration: Observational Study

Background

Patients admitted to general wards are inherently at risk of deterioration. Thus, tools that can provide early detection of deterioration may be lifesaving. Frequent remote patient monitoring (RPM) has the potential to allow such early detection, leading to a timely intervention by health care providers.

Objective

This study aimed to assess the potential of a novel wearable RPM device to provide timely alerts in patients at high risk for deterioration.

Methods

This prospective observational study was conducted in two general wards of a large tertiary medical center. Patients determined to be at high risk to deteriorate upon admission and assigned to a telemetry bed were included. On top of the standard monitoring equipment, a wearable monitor was attached to each patient, and monitoring was conducted in parallel. The data gathered by the wearable monitors were analyzed retrospectively, with the medical staff being blinded to them in real time. Several early warning scores of the risk for deterioration were used, all calculated from frequent data collected by the wearable RPM device: these included (1) the National Early Warning Score (NEWS), (2) Airway, Breathing, Circulation, Neurology, and Other (ABCNO) score, and (3) deterioration criteria defined by the clinical team as a “wish list” score. In all three systems, the risk scores were calculated every 5 minutes using the data frequently collected by the wearable RPM device. Data generated by the early warning scores were compared with those obtained from the clinical records of actual deterioration among these patients.

Results

In total, 410 patients were recruited and 217 were included in the final analysis. The median age was 71 (IQR 62-78) years and 130 (59.9%) of them were male. Actual clinical deterioration occurred in 24 patients. The NEWS indicated high alert in 16 of these 24 (67%) patients, preceding actual clinical deterioration by 29 hours on average. The ABCNO score indicated high alert in 18 (75%) of these patients, preceding actual clinical deterioration by 38 hours on average. Early warning based on wish list scoring criteria was observed for all 24 patients 40 hours on average before clinical deterioration was detected by the medical staff. Importantly, early warning based on the wish list scoring criteria was also observed among all other patients who did not deteriorate.

Conclusions

Frequent remote patient monitoring has the potential for early detection of a high risk to deteriorate among hospitalized patients, using both grouped signal-based scores and algorithm-based prediction. In this study, we show the ability to formulate scores for early warning by using RPM. Nevertheless, early warning scores compiled on the basis of these data failed to deliver reasonable specificity. Further efforts should be directed at improving the specificity and sensitivity of such tools.

Trial Registration

ClinicalTrials.gov NCT04220359; https://clinicaltrials.gov/ct2/show/NCT04220359

Translation of evidence into policy to improve clinical practice: the development of an emergency department rapid response system

BACKGROUND

Undetected clinical deterioration is a major cause of high mortality events in Emergency Department (ED) patients. Yet, there is no known model to guide the recognition and response to clinical deterioration in the ED, integrating internal and external resources.

METHODS

An integrative review was firstly conducted to identify the critical components of recognising and responding to clinical deterioration in the ED. Components identified from the review were analysed by clinical experts and informed the development of an ED Clinical Emergency Response System (EDCERS).

RESULTS

Twenty four eligible studies were included in the review. Eight core components were identified: 1) vital sign monitoring; 2) track and trigger system; 3) communication plan; 4) response time; 5) emergency nurse response; 6) emergency physician response; 7) critical care team response; and 8) specialty team response. These components informed the development of the EDCERS protocol, integrating responses from staff internal and external to the ED.

CONCLUSIONS

EDCERS was based on the best available evidence and considered the cultural context of care. Future research is needed to determine the useability and impact of EDCERS on patient and health outcomes.

Innovations in vital signs measurement for the detection of hypertension and shock in pregnancy

Approximately 820 women die in pregnancy and childbirth every day worldwide, with 99% of these occurring in low-resource settings. The most common causes of maternal mortality are haemorrhage, sepsis and hypertensive disorders. There are established, effective solutions to these complications, however challenges remain in identifying who is at greatest risk and ensuring that interventions are delivered early when they have the greatest potential to benefit. Measuring vital signs is the first step in identifying women at risk. Overstretched or poorly trained staff and inadequate access to accurate, reliable equipment to measure vital signs can potentially result in delayed treatment initiation. Early warning systems may help alert users to identify patients at risk, especially where novel technologies can improve usability by automating calculations and alerting users to abnormalities. This may be of greatest benefit in under-resourced settings where task-sharing is common and early identification of complications can allow for prioritisation of life-saving interventions. This paper highlights the challenges of accurate vital sign measurement in pregnancy and identifies innovations which may improve detection of pregnancy complications.

National early warning score (NEWS) in a Finnish multidisciplinary emergency department and direct vs. late admission to intensive care

OBJECTIVES

We investigated the national early warning scores (NEWSs) and related outcomes of patients in a tertiary referral center's multidisciplinary emergency department (ED). Patients were further categorized into three groups: triaged directly to intensive care unit (EDICU), triaged to general ward with later ICU admission (EDwardICU) and triaged to general ward (EDward). NEWSs and subsequent outcomes among these sub groups were compared.

METHODS

We conducted a prospective one-month cohort study in Tampere University Hospital's ED, Finland. ED-NEWSs were obtained for all adult patients without treatment limitations, and control (ward) NEWSs were further obtained for the EDwardICU and EDward patients.

RESULTS

Cohort consisted of 1,354 patients with a median ED-NEWS of 2, and higher ED-NEWS was associated with in-hospital mortality (OR 1.26, 95% CI 1.11-1.42; AUROC 0.75, 0.64‒0.86, p < 0.001) and 30-day mortality (OR 1.27, 1.17-1.39; AUROC 0.78, 0.71‒0.84, p < 0.001) irrespective of age and comorbidity. There were 64 patients in EDICU group, 12 patients in EDwardICU group and 1,278 patients in EDward group with median ED-NEWSs of 7, 3 and 2 (p < 0.001), respectively. After the first 24 h in wards, median NEWSs of the EDwardICU patients had substantially increased as compared with EDward patients (6 vs. 2, p < 0.001). There were no statistical differences in last NEWS before ICU admission between the EDICU and EDwardICU patients (7 vs. 8, p = 0.534), or in ICU severity-of-illness scores or patient outcomes.

CONCLUSIONS

ED-NEWS is independently associated with in-hospital and 30-day mortality with acceptable discrimination capability. Direct and late ICU admissions occurred with comparable NEWSs at admission.

A ward-based time study of paper and electronic documentation for recording vital sign observations

OBJECTIVE

To investigate time differences in recording observations and an early warning score using traditional paper charts and a novel e-Obs system in clinical practice.

METHODS

Researchers observed the process of recording observations and early warning scores across 3 wards in 2 university teaching hospitals immediately before and after introduction of the e-Obs system. The process of recording observations included both measurement and documentation of vital signs. Interruptions were timed and subtracted from the measured process duration. Multilevel modeling was used to compensate for potential confounding factors.

RESULTS

In all, 577 nurse events were observed (281 paper, 296 e-Obs). The geometric mean time to take a complete set of vital signs was 215 s (95% confidence interval [CI], 177 s-262 s) on paper, and 150 s (95% CI, 130 s-172 s) electronically. The treatment effect ratio was 0.70 (95% CI, 0.57-0.85, P  < .001). The treatment effect ratio in ward 1 was 0.37 (95% CI, 0.26-0.53), in ward 2 was 0.98 (95% CI, 0.70-1.38), and in ward 3 was 0.93 (95% CI, 0.66-1.33).

DISCUSSION

Introduction of an e-Obs system was associated with a statistically significant reduction in overall time to measure and document vital signs electronically compared to paper documentation. The reductions in time varied among wards and were of clinical significance on only 1 of 3 wards studied.

CONCLUSION

Our results suggest that introduction of an e-Obs system could lower nursing workload as well as increase documentation quality.