Browsing by Author "Brady, Patrick W."

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    Efficacy and Safety of Pediatric Critical Care Physician Telemedicine Involvement in Rapid Response Team and Code Response in a Satellite Facility
    (Wolters Kluwer, 2019-02) Berrens, Zachary J.; Gosdin, Craig H.; Brady, Patrick W.; Tegtmeyer, Ken; Medicine, School of Medicine
    OBJECTIVES: Satellite inpatient facilities of larger children's hospitals often do not have on-site intensivist support. In-house rapid response teams and code teams may be difficult to operationalize in such facilities. We developed a system using telemedicine to provide pediatric intensivist involvement in rapid response team and code teams at the satellite facility of our children's hospital. Herein, we compare this model with our in-person model at our main campus. DESIGN: Cross-sectional. SETTING: A tertiary pediatric center and its satellite facility. PATIENTS: Patients admitted to the satellite facility. INTERVENTIONS: Implementation of a rapid response team and code team model at a satellite facility using telemedicine to provide intensivist support. MEASUREMENTS AND MAIN RESULTS: We evaluated the success of the telemedicine model through three a priori outcomes: 1) reliability: involvement of intensivist on telemedicine rapid response teams and codes, 2) efficiency: time from rapid response team and code call until intensivist response, and 3) outcomes: disposition of telemedicine rapid response team or code calls. We compared each metric from our telemedicine model with our established main campus model. MAIN RESULTS: Critical care was involved in satellite campus rapid response team activations reliably (94.6% of the time). The process was efficient (median response time 7 min; mean 8.44 min) and effective (54.5 % patients transferred to PICU, similar to the 45-55% monthly rate at main campus). For code activations, the critical care telemedicine response rate was 100% (6/6), with a fast response time (median 1.5 min). We found no additional risk to patients, with no patients transferred from the satellite campus requiring a rapid escalation of care defined as initiation of vasoactive support, greater than 60 mL/kg in fluid resuscitation, or endotracheal intubation. CONCLUSIONS: Telemedicine can provide reliable, timely, and effective critical care involvement in rapid response team and Code Teams at satellite facilities.
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    Epidemiology and Severity of Illness of MIS-C and Kawasaki Disease During the COVID-19 Pandemic
    (American Academy of Pediatrics, 2023) Molloy, Matthew J.; Auger, Katherine A.; Hall, Matt; Shah, Samir S.; Schondelmeyer, Amanda C.; Parikh, Kavita; Kazmier, Katherine M.; Katragadda, Harita; Jacob, Seethal A.; Jerardi, Karen E.; Ivancie, Rebecca; Hartley, David; Bryan, Mersine A.; Bhumbra, Samina; Arnold, Staci D.; Brady, Patrick W.; Pediatrics, School of Medicine
    Background and objectives: Multisystem inflammatory syndrome in children (MIS-C) is a novel, severe condition following severe acute respiratory syndrome coronavirus 2 infection. Large epidemiologic studies comparing MIS-C to Kawasaki disease (KD) and evaluating the evolving epidemiology of MIS-C over time are lacking. We sought to understand the illness severity of MIS-C compared with KD and evaluate changes in MIS-C illness severity over time during the coronavirus disease 2019 pandemic compared with KD. Methods: We included hospitalizations of children with MIS-C and KD from April 2020 to May 2022 from the Pediatric Health Information System administrative database. Our primary outcome measure was the presence of shock, defined as the use of vasoactive/inotropic cardiac support or extracorporeal membrane oxygenation. We examined the volume of MIS-C and KD hospitalizations and the proportion of hospitalizations with shock over time using 2-week intervals. We compared the proportion of hospitalizations with shock in MIS-C and KD patients over time using generalized estimating equations adjusting for hospital clustering and age, with time as a fixed effect. Results: We identified 4868 hospitalizations for MIS-C and 2387 hospitalizations for KD. There was a higher proportion of hospitalizations with shock in MIS-C compared with KD (38.7% vs 5.1%). In our models with time as a fixed effect, we observed a significant decrease in the odds of shock over time in MIS-C patients (odds ratio 0.98, P < .001) but not in KD patients (odds ratio 1.00, P = .062). Conclusions: We provide further evidence that MIS-C is a distinct condition from KD. MIS-C was a source of lower morbidity as the pandemic progressed.
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    Identifying and Validating Pediatric Hospitalizations for MIS-C Through Administrative Data
    (American Academy of Pediatrics, 2023) Auger, Katherine A.; Hall, Matt; Arnold, Staci D.; Bhumbra, Samina; Bryan, Mersine A.; Hartley, David; Ivancie, Rebecca; Katragadda, Harita; Kazmier, Katie; Jacob, Seethal A.; Jerardi, Karen E.; Molloy, Matthew J.; Parikh, Kavita; Schondelmeyer, Amanda C.; Shah, Samir S.; Brady, Patrick W.; Medicine, School of Medicine
    Background: Individual children's hospitals care for a small number of patients with multisystem inflammatory syndrome in children (MIS-C). Administrative databases offer an opportunity to conduct generalizable research; however, identifying patients with MIS-C is challenging. Methods: We developed and validated algorithms to identify MIS-C hospitalizations in administrative databases. We developed 10 approaches using diagnostic codes and medication billing data and applied them to the Pediatric Health Information System from January 2020 to August 2021. We reviewed medical records at 7 geographically diverse hospitals to compare potential cases of MIS-C identified by algorithms to each participating hospital's list of patients with MIS-C (used for public health reporting). Results: The sites had 245 hospitalizations for MIS-C in 2020 and 358 additional MIS-C hospitalizations through August 2021. One algorithm for the identification of cases in 2020 had a sensitivity of 82%, a low false positive rate of 22%, and a positive predictive value (PPV) of 78%. For hospitalizations in 2021, the sensitivity of the MIS-C diagnosis code was 98% with 84% PPV. Conclusion: We developed high-sensitivity algorithms to use for epidemiologic research and high-PPV algorithms for comparative effectiveness research. Accurate algorithms to identify MIS-C hospitalizations can facilitate important research for understanding this novel entity as it evolves during new waves.