Evaluation of Electronic Medical Record Vital Sign Data Versus a Commercially Available Acuity Score in Predicting Need for Critical Intervention at a Tertiary Children's Hospital.

OBJECTIVES: Evaluate the ability of vital sign data versus a commercially available acuity score adapted for children (pediatric Rothman Index) to predict need for critical intervention in hospitalized pediatric patients to form the foundation for an automated early warning system. DESIGN: Retrospective review of electronic medical record data. SETTING: Academic children's hospital. PATIENTS: A total of 220 hospitalized children 6.7 ± 6.7 years old experiencing a cardiopulmonary arrest (condition A) and/or requiring urgent intervention with transfer (condition C) to the ICU between January 2006 and July 2011. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Physiologic data 24 hours preceding the event were extracted from the electronic medical record. Vital sign predictors were constructed using combinations of age-adjusted abnormalities in heart rate, systolic and diastolic blood pressures, respiratory rate, and peripheral oxygen saturation to predict impending deterioration. Sensitivity and specificity were determined for vital sign-based predictors by using 1:1 age-matched and sex-matched non-ICU control patients. Sensitivity and specificity for a model consisting of any two vital sign measurements simultaneously outside of age-adjusted normal ranges for condition A, condition C, and condition A or C were 64% and 54%, 57% and 53%, and 59% and 54%, respectively. The pediatric Rothman Index (added to the electronic medical record in April 2009) was evaluated in a subset of these patients (n = 131) and 16,138 hospitalized unmatched non-ICU control patients for the ability to predict condition A or C, and receiver operating characteristic curves were generated. Sensitivity and specificity for a pediatric Rothman Index cutoff of 40 for condition A, condition C, and condition A or C were 56% and 99%, 13% and 99%, and 28% and 99%, respectively. CONCLUSIONS: A model consisting of simultaneous vital sign abnormalities and the pediatric Rothman Index predict condition A or C in the 24-hour period prior to the event. Vital sign only prediction models have higher sensitivity than the pediatric Rothman Index but are associated with a high false-positive rate. The high specificity of the pediatric Rothman Index merits prospective evaluation as an electronic adjunct to human-triggered early warning systems.

Child Health Needs and the Pediatric Critical Care Medicine Workforce: 2020-2040.

This article, focused on the current and future pediatric critical care medicine (PCCM) workforce, is part of a supplement in Pediatrics anticipating the future supply of the pediatric subspecialty workforce. It draws on information available in the literature, data from the American Board of Pediatrics, and findings from a model that estimates the future supply of pediatric subspecialists developed by the American Board of Pediatrics Foundation in collaboration with the Carolina Workforce Research Center at the University of North Carolina at Chapel Hill's Cecil G. Sheps Center for Health Services Research and Strategic Modeling and Analysis Ltd. A brief history of the field of PCCM is provided, followed by an in-depth examination of the current PCCM workforce and a subsequent evaluation of workforce forecasts from 2020 to 2040. Under baseline conditions, the PCCM workforce is expected to increase by 105% during the forecasted period, more than any other pediatric subspecialty. Forecasts are modeled under a variety of multifactorial conditions meant to simulate the effects of changes to the supply of PCCM subspecialists, with only modest changes observed. Future PCCM workforce demand is unclear, although some suggest an oversupply may exist and that market forces may correct this. The findings generate important questions regarding the future state of the PCCM workforce and should be used to guide trainees considering a PCCM career, subspecialty leaders responsible for hosting training programs, staffing ICUs, and governing bodies that oversee training program accreditation and subspecialist certification.

Do Lower Costs for Applicants Come at the Expense of Program Perception? A Cross-Sectional Survey Study of Virtual Residency Interviews.

Background: Travel costs and application fees make in-person residency interviews expensive, compounding existing financial burdens on medical students. We hypothesized virtual interviews (VI) would be associated with decreased costs for applicants compared to in-person interviews (IPI) but at the expense of gathering information with which to assess the program. Objective: To survey senior medical students and postgraduate year (PGY)-1 residents regarding their financial burden and program perception during virtual versus in-person interviews. Methods: The authors conducted a single center, multispecialty study comparing costs of IPI vs VI from 2020-2021. Fourth-year medical students and PGY-1 residents completed one-time surveys regarding interview costs and program perception. The authors compared responses between IPI and VI groups. Potential debt accrual was calculated for 3- and 7-year residencies. Results: Two hundred fifty-two (of 884, 29%) surveys were completed comprising 75 of 169 (44%) IPI and 177 of 715 (25%) VI respondents. The VI group had significantly lower interview costs compared to the IPI group (median $1,000 [$469-$2,050 IQR] $784-$1,216 99% CI vs $3,200 [$1,700-$5,500 IQR] $2,404-$3,996 99% CI, P<.001). The VI group scored lower for feeling the interview process was an accurate representation of the residency program (3.3 [0.5] vs 4.1 [0.7], P<.001). Assuming interview costs were completely loan-funded, the IPI group will have accumulated potential total loan amounts $2,334 higher than the VI group at 2% interest and $2,620 at 6% interest. These differences were magnified for a 7-year residency. Conclusions: Virtual interviews save applicants thousands of dollars at the expense of their perception of the residency program.

Part 16: education, implementation, and teams: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.

Optimizing the links in the Chain of Survival improves outcomes and saves lives. The use of evidence-based education and implementation strategies will allow organizations and communities to strengthen these links in the most effective and efficient manner.

Adherence to Pediatric Cardiac Arrest Guidelines Across a Spectrum of Fifty Emergency Departments: A Prospective, In Situ, Simulation-based Study.

BACKGROUND AND OBJECTIVES: Pediatric out-of-hospital cardiac arrest survival outcomes are dismal (<10%). Care that is provided in adherence to established guidelines has been associated with improved survival. Lower mortality rates have been reported in higher-volume hospitals, teaching hospitals, and trauma centers. The primary objective of this article was to explore the relationship of hospital characteristics, such as annual pediatric patient volume, to adherence to pediatric cardiac arrest guidelines during an in situ simulation. Secondary objectives included comparing adherence to other team, provider, and system factors. METHODS: This prospective, multicenter, observational study evaluated interprofessional teams in their native emergency department (ED) resuscitation bays caring for a simulated 5-year-old child presenting in cardiac arrest. The primary outcome, adherence to the American Heart Association pediatric guidelines, was assessed using a 14-item tool including three component domains: basic life support (BLS), pulseless electrical activity (PEA), and ventricular fibrillation (VF). Provider, team, and hospital-level data were collected as independent data. EDs were evaluated in four pediatric volume groups (low < 1,800/year; medium 1,800-4,999; medium-high 5,000-9,999; high > 10,000). Cardiac arrest adherence and domains were evaluated by pediatric patient volume and other team and hospital-level characteristics, and path analyses were performed to evaluate the contribution of patient volume, systems readiness, and teamwork on BLS, PEA, and VF adherence. RESULTS: A total of 101 teams from a spectrum of 50 EDs participated including nine low pediatric volume (<1,800/year), 36 medium volume (1,800-4,999/year), 24 medium-high (5,000-9,999/year), and 32 high volume (≥10000/year). The median total adherence score was 57.1 (interquartile range = 50.0-78.6). This was not significantly different across the four volume groups. The highest level of adherence for BLS and PEA domains was noted in the medium-high-volume sites, while no difference was noted for the VF domain. The lowest level of BLS adherence was noted in the lowest-volume EDs. Improved adherence was not directly associated with higher pediatric readiness survey (PRS) score provider experience, simulation teamwork performance, or more providers with Pediatric Advanced Life Support (PALS) training. EDs in teaching hospitals with a trauma center designation that served only children demonstrated higher adherence compared to nonteaching hospitals (64.3 vs 57.1), nontrauma centers (64.3 vs. 57.1), and mixed pediatric and adult departments (67.9 vs. 57.1), respectively. The overall effect sizes for total cardiac adherence score are ED type γ = 0.47 and pediatric volume (low and medium vs. medium-high and high) γ = 0.41. A series of path analyses models was conducted that indicated that overall pediatric ED volume predicted significantly better guideline adherence, but the effect of volume on performance was only mediated by the PRS for the VF domain. CONCLUSIONS: This study demonstrated variable adherence to pediatric cardiac arrest guidelines across a spectrum of EDs. Overall adherence was not associated with ED pediatric volume. Medium-high-volume EDs demonstrated the highest levels of adherence for BLS and PEA. Lower-volume EDs were noted to have lower adherence to BLS guidelines. Improved adherence was not directly associated with higher PRS score provider experience, simulation teamwork performance, or more providers with PALS training. This study demonstrates that current approaches optimizing the care of children in cardiac arrest in the ED (provider training, teamwork training, environmental preparation) are insufficient.

Differences in the Quality of Pediatric Resuscitative Care Across a Spectrum of Emergency Departments.

IMPORTANCE: The quality of pediatric resuscitative care delivered across the spectrum of emergency departments (EDs) in the United States is poorly described. In a recent study, more than 4000 EDs completed the Pediatric Readiness Survey (PRS); however, the correlation of PRS scores with the quality of simulated or real patient care has not been described. OBJECTIVE: To measure and compare the quality of resuscitative care delivered to simulated pediatric patients across a spectrum of EDs and to examine the correlation of PRS scores with quality measures. DESIGN, SETTING, AND PARTICIPANTS: This prospective multicenter cohort study evaluated 58 interprofessional teams in their native pediatric or general ED resuscitation bays caring for a series of 3 simulated critically ill patients (sepsis, seizure, and cardiac arrest). MAIN OUTCOMES AND MEASURES: A composite quality score (CQS) was measured as the sum of 4 domains: (1) adherence to sepsis guidelines, (2) adherence to cardiac arrest guidelines, (3) performance on seizure resuscitation, and (4) teamwork. Pediatric Readiness Survey scores and health care professional demographics were collected as independent data. Correlations were explored between CQS and individual domain scores with PRS. RESULTS: Overall, 58 teams from 30 hospitals participated (8 pediatric EDs [PEDs], 22 general EDs [GEDs]). The mean CQS was 71 (95% CI, 68-75); PEDs had a higher mean CQS (82; 95% CI, 79-85) vs GEDs (66; 95% CI, 63-69) and outperformed GEDs in all domains. However, when using generalized estimating equations to estimate CQS controlling for clustering of the data, PED status did not explain a higher CQS (ß = 4.28; 95% CI, -4.58 to 13.13) while the log of pediatric patient volume did explain a higher CQS (ß = 9.57; 95% CI, 2.64-16.49). The correlation of CQS to PRS was moderate (r = 0.51; P < .001). The correlation was weak for cardiac arrest (r = 0.24; P = .07), weak for sepsis (ρ = 0.45; P < .001) and seizure (ρ = 0.43; P = .001), and strong for teamwork (ρ = 0.71; P < .001). CONCLUSIONS AND RELEVANCE: This multicenter study noted significant differences in the quality of simulated pediatric resuscitative care across a spectrum of EDs. The CQS was higher in PEDs compared with GEDs. However, when controlling for pediatric patient volume and other variables in a multivariable model, PED status does not explain a higher CQS while pediatric patient volume does. The correlation of the PRS was moderate for simulation-based measures of quality.

Examining pediatric resuscitation education using simulation and scripted debriefing: a multicenter randomized trial.

IMPORTANCE: Resuscitation training programs use simulation and debriefing as an educational modality with limited standardization of debriefing format and content. Our study attempted to address this issue by using a debriefing script to standardize debriefings. OBJECTIVE: To determine whether use of a scripted debriefing by novice instructors and/or simulator physical realism affects knowledge and performance in simulated cardiopulmonary arrests. DESIGN Prospective, randomized, factorial study design. SETTING: The study was conducted from 2008 to 2011 at 14 Examining Pediatric Resuscitation Education Using Simulation and Scripted Debriefing (EXPRESS) network simulation programs. Interprofessional health care teams participated in 2 simulated cardiopulmonary arrests, before and after debriefing. PARTICIPANTS: We randomized 97 participants (23 teams) to nonscripted low-realism; 93 participants (22 teams) to scripted low-realism; 103 participants (23 teams) to nonscripted high-realism; and 94 participants (22 teams) to scripted high-realism groups. INTERVENTION Participants were randomized to 1 of 4 arms: permutations of scripted vs nonscripted debriefing and high-realism vs low-realism simulators. MAIN OUTCOMES AND MEASURES: Percentage difference (0%-100%) in multiple choice question (MCQ) test (individual scores), Behavioral Assessment Tool (BAT) (team leader performance), and the Clinical Performance Tool (CPT) (team performance) scores postintervention vs preintervention comparison (PPC). RESULTS: There was no significant difference at baseline in nonscripted vs scripted groups for MCQ (P = .87), BAT (P = .99), and CPT (P = .95) scores. Scripted debriefing showed greater improvement in knowledge (mean [95% CI] MCQ-PPC, 5.3% [4.1%-6.5%] vs 3.6% [2.3%-4.7%]; P = .04) and team leader behavioral performance (median [interquartile range (IQR)] BAT-PPC, 16% [7.4%-28.5%] vs 8% [0.2%-31.6%]; P = .03). Their improvement in clinical performance during simulated cardiopulmonary arrests was not significantly different (median [IQR] CPT-PPC, 7.9% [4.8%-15.1%] vs 6.7% [2.8%-12.7%], P = .18). Level of physical realism of the simulator had no independent effect on these outcomes. CONCLUSIONS AND RELEVANCE: The use of a standardized script by novice instructors to facilitate team debriefings improves acquisition of knowledge and team leader behavioral performance during subsequent simulated cardiopulmonary arrests. Implementation of debriefing scripts in resuscitation courses may help to improve learning outcomes and standardize delivery of debriefing, particularly for novice instructors.