Quality metrics for the evaluation of Rapid Response Systems: Proceedings from the third international consensus conference on Rapid Response Systems.

BACKGROUND: Clinically significant deterioration of patients admitted to general wards is a recognized complication of hospital care. Rapid Response Systems (RRS) aim to reduce the number of avoidable adverse events. The authors aimed to develop a core quality metric for the evaluation of RRS. METHODS: We conducted an international consensus process. Participants included patients, carers, clinicians, research scientists, and members of the International Society for Rapid Response Systems with representatives from Europe, Australia, Africa, Asia and the US. Scoping reviews of the literature identified potential metrics. We used a modified Delphi methodology to arrive at a list of candidate indicators that were reviewed for feasibility and applicability across a broad range of healthcare systems including low and middle-income countries. The writing group refined recommendations and further characterized measurement tools. RESULTS: Consensus emerged that core outcomes for reporting for quality improvement should include ten metrics related to structure, process and outcome for RRS with outcomes following the domains of the quadruple aim. The conference recommended that hospitals should collect data on cardiac arrests and their potential predictability, timeliness of escalation, critical care interventions and presence of written treatment goals for patients remaining on general wards. Unit level reporting should include the presence of patient activated rapid response and metrics of organizational culture. We suggest two exploratory cost metrics to underpin urgently needed research in this area. CONCLUSION: A consensus process was used to develop ten metrics for better understanding the course and care of deteriorating ward patients. Others are proposed for further development

Delivering high-quality cardiopulmonary resuscitation in-hospital

This review discusses recent data relating to delivering high-quality cardiopulmonary resuscitation (CPR) to patients with in-hospital cardiac arrest. Recent findings: Delivering high-quality CPR requires interventions at a national, local, team and individual rescuer level. These include measuring patient outcomes, patient safety incident reporting, education, an increased emphasis on human factors, briefing and debriefing of resuscitation teams, and the use of sensing devices that provide real-time prompts or feedback to rescuers during CPR. Data from national registries, patient safety incident reports and mock codes can be used to identify areas for improving practice. Education of staff is essential in both technical and nontechnical resuscitation skills (human factors). Resuscitation team performance can be improved by ensuring teams brief and plan beforehand and also debrief using feedback data collected during resuscitation events. The use of feedback and prompt devices helps improve adherence to guidelines for chest compression quality but data are lacking in terms of showing improved patient outcomes. Summary: Delivering high-quality CPR in-hospital requires a multifaceted approach. Collecting data during arrests and feeding back in real time and postevent during debriefings can be used to improve delivery of high-quality CPR. There are few studies that show improvement in actual patient outcomes (e. g., survival to hospital discharge) with improvements in delivery of high-quality CPR. Recognizing the importance of both technical and nontechnical skills (human factors) to deliver high-quality CPR is essential

The use of CPR feedback/prompt devices during training and CPR performance : a systematic review

Objectives: In lay persons and health care providers performing cardiopulmonary resuscitation (CPR), does the use of CPR feedback/prompt devices when compared to no device improve CPR skill acquisition, retention, and real life performance? Methods: The Cochrane database of systematic reviews; Medline (1950-Dec 2008): EmBASE (1988-Dec 2008) and Psychinfo (1988-Dec 2008) were searched using ("Prompt$" or "Feedback" as text words) AND ("Cardiopulmonary Resuscitation" [Mesh] OR "Heart Arrest" [Mesh]). Inclusion criteria were articles describing the effect of audio or visual feedback/prompts on CPR skill acquisition, retention or performance. Results: 509 papers were identified of which 33 were relevant. There were no randomised controlled studies in humans (LOE 1). Two non-randomised cross-over studies (LOE 2) and four with retrospective controls (LOE 3) in humans and 20 animal/manikin (LOE 5) studies contained data supporting the use of feedback/prompt devices. Two LOE 5 studies were neutral. Six LOE 5 manikin studies provided opposing evidence. Conclusions: There is good evidence supporting the use of CPR feedback/prompt devices during CPR training to improve CPR skill acquisition and retention. Their use in clinical practice as part of an overall strategy to improve the quality of CPR may be beneficial. The accuracy of devices to measure compression depth should be calibrated to take account of the stiffness of the support surface upon which CPR is being performed (e.g. floor/mattress). Further studies are needed to determine if these devices improve patient outcomes

Effect of mattress deflection on CPR quality assessment for older children and adolescents

Appropriate chest compression (CC) depth is associated with improved CPR outcome. CCs provided in hospital are often conducted on a compliant mattress. The objective was to quantify the effect of mattress compression on the assessment of CPR quality in children. Methods: A force and deflection sensor (FDS) was used during CPR in the Pediatric Intensive Care Unit and Emergency Department of a children's hospital. The sensor was interposed between the chest of the patient and hands of the rescuer and measured CC depth. Following CPR event, each event was reconstructed with a manikin and an identical mattress/backboard/patient configuration. CCs were performed using FDS on the sternum and a reference accelerometer attached to the spine of the manikin, providing a means to Calculate the mattress deflection. Results: Twelve CPR events with 14,487 CC (11 patients, median age 14.9 years) were recorded and reconstructed: 9 on ICU beds (9296 CC), 3 on stretchers (5191 CC). Measured mean CC depth during CPR was 47 +/- 8 mm on ICU beds, and 45 +/- 7 mm on stretcher beds with overestimation of 13 +/- 4 mm and 4 +/- 1 mm, respectively, due to mattress compression. After adjusting for this, the proportion of CC that met the CPR guidelines decreased from 88.4 to 31.8% on ICU beds (p < 0.001), and 86.3 to 64.7% on stretcher (p < 0.001 The proportion of appropriate depth CC was significantly smaller on ICU beds (p < 0.001). Conclusion: CC conducted on a non-rigid surface may not be deep enough. FDS may overestimate CC depth by 28% on ICU beds, and 10% on stretcher beds

Predicting transfers to intensive care in children using CEWT and other early warning systems

Background and Objective: The Children’s Early Warning Tool (CEWT), developed in Australia, is widely used in many countries to monitor the risk of deterioration in hospitalized children. Our objective was to compare CEWT prediction performance against a version of the Bedside Pediatric Early Warning Score (Bedside PEWS), Between the Flags (BTF), and the pediatric Calculated Assessment of Risk and Triage (pCART). Methods: We conducted a retrospective observational study of all patient admissions to the Comer Children’s Hospital at the University of Chicago between 2009–2019. We compared performance for predicting the primary outcome of a direct ward-to-intensive care unit (ICU) transfer within the next 12 h using the area under the receiver operating characteristic curve (AUC). Alert rates at various score thresholds were also compared. Results: Of 50,815 ward admissions, 1,874 (3.7%) experienced the primary outcome. Among patients in Cohort 1 (years 2009–2017, on which the machine learning-based pCART was trained), CEWT performed slightly worse than Bedside PEWS but better than BTF (CEWT AUC 0.74 vs. Bedside PEWS 0.76, P Conclusion: CEWT has good discrimination for predicting which patients will likely be transferred to the ICU, while pCART performed the best.</p