Browsing by Author "Auger, Katherine A."

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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.
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    A Validated Method for Identifying Unplanned Pediatric Readmission
    (Elsevier, 2016-03) Auger, Katherine A.; Mueller, Emily L.; Weinberg, Steven H.; Forster, Catherine; Shah, Anita; Wolski, Christine; Mussman, Grant; Ipsaro, Anna Jolanta; Davis, Matthew M.; Department of Pediatrics, IU School of Medicine
    Objective To validate the accuracy of pre-encounter hospital designation as a novel way to identify unplanned pediatric readmissions and describe the most common diagnoses for unplanned readmissions among children. Study design We examined all hospital discharges from 2 tertiary care children's hospitals excluding deaths, normal newborn discharges, transfers to other institutions, and discharges to hospice. We performed blinded medical record review on 641 randomly selected readmissions to validate the pre-encounter planned/unplanned hospital designation. We identified the most common discharge diagnoses associated with subsequent 30-day unplanned readmissions. Results Among 166 994 discharges (hospital A: n = 55 383; hospital B: n = 111 611), the 30-day unplanned readmission rate was 10.3% (hospital A) and 8.7% (hospital B). The hospital designation of “unplanned” was correct in 98% (hospital A) and 96% (hospital B) of readmissions; the designation of “planned” was correct in 86% (hospital A) and 85% (hospital B) of readmissions. The most common discharge diagnoses for which unplanned 30-day readmissions occurred were oncologic conditions (up to 38%) and nonhypertensive congestive heart failure (about 25%), across both institutions. Conclusions Unplanned readmission rates for pediatrics, using a validated, accurate, pre-encounter designation of “unplanned,” are higher than previously estimated. For some pediatric conditions, unplanned readmission rates are as high as readmission rates reported for adult conditions. Anticipating unplanned readmissions for high-frequency diagnostic groups may help focus efforts to reduce the burden of readmission for families and facilities. Using timing of hospital registration in administrative records is an accurate, widely available, real-time way to distinguish unplanned vs planned pediatric readmissions.