Improving Shared Situation Awareness for High-risk Therapies in Hospitalized Children.

BACKGROUND: High-risk therapies (HRTs), including medications and medical devices, are an important driver of preventable harm in children's hospitals. To facilitate shared situation awareness (SA) and thus targeted harm prevention, we aimed to increase the percentage of electronic health record (EHR) alerts with the correct descriptor of an HRT from 11% to 100% on a high-acuity hospital unit over a 6-month period. METHODS: The interdisciplinary team defined an HRT as a medication or device with a significant risk for harm that required heightened awareness. Our aim for interventions was to (1) educate staff on a new HRT algorithm; (2) develop a comprehensive table of HRTs, risks, and mitigation plans; (3) develop bedside signs for patients receiving HRTs; and (4) restructure unit huddles. Qualitative interviews with families, nurses, and medical teams were used to assess shared SA and inform the development and adaptation of interventions. The primary outcome metric was the percentage of EHR alerts for an HRT that contained a correct descriptor of the therapy for use by the care team and institutional safety leaders. RESULTS: The percentage of EHR alerts with a correct HRT descriptor increased from an average of 11% to 96%, with special cause variation noted on a statistical process control chart. Using qualitative interview data, we identified critical awareness gaps, including establishing a shared mental model between nursing staff and the medical team as well as engagement of families at the bedside to monitor for complications. CONCLUSIONS: Explicit, structured processes and huddles can increase HRT SA among the care team, patient, and family.

Optimizing Situation Awareness to Reduce Emergency Transfers in Hospitalized Children.

BACKGROUND AND OBJECTIVES: Interventions to improve care team situation awareness (SA) are associated with reduced rates of unrecognized clinical deterioration in hospitalized children. By addressing themes from recent safety events and emerging corruptors to SA in our system, we aimed to decrease emergency transfers (ETs) to the ICU by 50% over 10 months. METHODS: An interdisciplinary team of physicians, nurses, respiratory therapists, and families convened to improve the original SA model for clinical deterioration and address communication inadequacies and evolving technology in our inpatient system. The key drivers included the establishment of a shared mental model, psychologically safe escalation, and efficient and effective SA tools. Novel interventions including the intentional inclusion of families and the interdisciplinary team in huddles, a mental model checklist, door signage, and an electronic health record SA navigator were evaluated via a time series analysis. Sequential inpatient-wide testing of the model allowed for iteration and consensus building across care teams and families. The primary outcome measure was ETs, defined as any ICU transfer in which the patient receives intubation, inotropes, or ≥3 fluid boluses within 1 hour. RESULTS: The rate of ETs per 10 000 patient-days decreased from 1.34 to 0.41 during the study period. This coincided with special cause improvement in process measures, including risk recognition before medical response team activation and the use of tools to facilitate shared SA. CONCLUSIONS: An innovative, proactive, and reliable process to predict, prevent, and respond to clinical deterioration was associated with a nearly 70% reduction in ETs.

Design, Implementation, and Validation of a Pediatric ICU Sepsis Prediction Tool as Clinical Decision Support.

BACKGROUND: Sepsis is an uncontrolled inflammatory reaction caused by infection. Clinicians in the pediatric intensive care unit (PICU) developed a paper-based tool to identify patients at risk of sepsis. To improve the utilization of the tool, the PICU team integrated the paper-based tool as a real-time clinical decision support (CDS) intervention in the electronic health record (EHR). OBJECTIVE: This study aimed to improve identification of PICU patients with sepsis through an automated EHR-based CDS intervention. METHODS: A prospective cohort study of all patients admitted to the PICU from May 2017 to May 2019. A CDS intervention was implemented in May 2018. The CDS intervention screened patients for nonspecific sepsis criteria, temperature dysregulation and a blood culture within 6 hours. Following the screening, an interruptive alert prompted nursing staff to complete a perfusion screen to assess for clinical signs of sepsis. The primary alert performance outcomes included sensitivity, specificity, and positive and negative predictive value. The secondary clinical outcome was completion of sepsis management tasks. RESULTS: During the 1-year post implementation period, there were 45.0 sepsis events per 1,000 patient days over 10,805 patient days. The sepsis alert identified 392 of the 436 sepsis episodes accurately with sensitivity of 92.5%, specificity of 95.6%, positive predictive value of 46.0%, and negative predictive value of 99.7%. Examining only patients with severe sepsis confirmed by chart review, test characteristics fell to a sensitivity of 73.3%, a specificity of 92.5%. Prior to the initiation of the alert, 18.6% (13/70) of severe sepsis patients received recommended sepsis interventions. Following the implementation, 34% (27/80) received these interventions in the time recommended, p = 0.04. CONCLUSION: An EHR CDS intervention demonstrated strong performance characteristics and improved completion of recommended sepsis interventions.

Improving Timely Recognition and Treatment of Sepsis in the Pediatric ICU.

BACKGROUND: Sepsis is a leading cause of pediatric mortality worldwide. The implementation of sepsis bundles and clinical decision support (CDS) tools have been useful in improving sepsis recognition and treatment. METHODS: Interventions targeted the pediatric ICU (PICU) sepsis identification process and focused on implementation of multidisciplinary sepsis huddles prompted by an automated CDS tool. The primary outcome measure was days between delayed sepsis recognition, with secondary outcome measures of the percentages of patients receiving goal-directed evidence-based sepsis therapies, including antibiotics within 1 hour, rapid fluid bolus within 20 minutes, and lactate measurement within 1 hour. The researchers also tracked median time to antibiotics. RESULTS: Average days between delayed sepsis recognition improved from one episode every 9 days to one episode every 28 days. The percentage of patients who received antibiotics within 1 hour improved from 33.9% to 45.5%, received a fluid bolus within 20 minutes increased from 54.7% to 61.8%, and had a lactate measured within 1 hour increased from 59.4% to 71.1% post-CDS alert; none were statistically significant. Median time to antibiotics prior to CDS alert implementation was 1.53 hours, with improvement to 1.05 hours postimplementation (p = 0.03). CONCLUSION: Implementation of multidisciplinary sepsis huddles and an automated CDS alert in the PICU led to an improvement in days between delayed sepsis recognition and a significant improvement in time to antibiotics.

2009 pandemic influenza A (H1N1) in critically ill children in Cincinnati, Ohio.

OBJECTIVE: To compare the clinical features, management, and outcome of critically ill children with H1N1 to children with seasonal influenza from the previous three influenza seasons. DESIGN: The overall number of hospitalizations and the proportion cared for in the pediatric intensive care unit during the H1N1 epidemic period and the three previous influenza seasons (2007-2009) were determined. Medical records of patients admitted to the pediatric intensive care unit with H1N1 and seasonal influenza infection were reviewed. SETTING: Cincinnati Children's Hospital Medical Center, a large, 523-bed hospital located in Cincinnati. PATIENTS: Hospitalized children with laboratory-confirmed seasonal or H1N1 infection. MEASUREMENTS: Study variables included demographic data (age, gender), clinical factors (weight, Pediatric Risk of Mortality III scores, presenting signs and symptoms, comorbid conditions), management (length of mechanical ventilation, other treatments, including high-frequency oscillatory ventilatory support, inhaled nitric oxide, or extracorporeal membrane oxygenation), and outcome (overall and pediatric intensive care unit length of stay and mortality). MAIN RESULTS: Overall, 312 children were hospitalized with H1N1 and 222 with seasonal influenza from the three previous seasons. Children with H1N1 infection were significantly less likely to require pediatric intensive care unit care compared to children with seasonal influenza infection (14% vs. 24%, p = .02). Compared to children with seasonal influenza, children in the pediatric intensive care unit with H1N1 were older (median age in months 107 vs. 68, p = .05) and significantly more likely to have comorbid conditions (64% vs. 40%, p = .03), especially respiratory conditions. While there were no significant differences in severity of illness by Pediatric Risk of Mortality III scores or pediatric intensive care unit length of stay, children with H1N1 were significantly less likely to have acute respiratory failure (p = .04) or die compared to children with seasonal influenza infection (p = .03). CONCLUSIONS: In contrast to other studies, we found that critically ill children with H1N1 had a significantly lower morbidity and mortality compared to children with seasonal influenza.

Extracorporeal membrane oxygenation, extubation, and lung-recruitment maneuvers as rescue therapy in a patient with tracheal dehiscence following slide tracheoplasty.

Long-segment congenital tracheal stenosis is characterized by complete tracheal rings. Surgery is required during infancy to optimize outcomes, and the post-surgery complications include mucus plugging, airway trauma, dehiscence at the surgery site, and death. We report a 5-week-old patient who developed a tracheal-wall dehiscence after a slide tracheoplasty. To safeguard against further dehiscence and to protect her one functional lung, we used extracorporeal membrane oxygenation (ECMO). After she was stabilized on veno-arterial ECMO we extubated and continued ECMO for 5 days. On postoperative day 14 we removed the ECMO and transitioned her to high-frequency oscillatory ventilation, and performed slow lung-recruitment maneuvers every 2 hours. This strategy of ECMO with extubation, then high-frequency oscillatory ventilation is a useful rescue therapy in patients with postoperative tracheal dehiscence.