Identifying and Validating Pediatric Hospitalizations for MIS-C Through Administrative Data.

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.

Facilitators and Barriers to Providing Vaccinations During Hospital Visits.

BACKGROUND: Many children are undervaccinated at the time of hospital admission. Our objective was to explore the facilitators and barriers to vaccinating during hospitalization. METHODS: We conducted qualitative interviews of parents, primary care pediatricians, emergency department (ED) physicians, and pediatric hospitalists. Parents of undervaccinated hospitalized children who were admitted through the ED were invited to participate. We used purposive sampling to identify physician participants. Semistructured interviews querying participants' perspectives on hospital-based vaccination were audiorecorded and transcribed. Parent demographics and physician practice characteristics were collected. Transcripts were analyzed for facilitators and barriers to vaccinating during acute hospital visits by using inductive content analysis. A conceptual framework was developed on the basis of the social ecological model. RESULTS: Twenty-one parent interviews and 10 physician interviews were conducted. Of parent participants, 86% were female; 76% were white. Physician participants included 3 primary care pediatricians, 3 ED physicians, and 4 hospitalists. Facilitators and barriers fell under 4 major themes: (1) systems-level factors, (2) physician-level factors, (3) parent-provider interactional factors, and (4) parent- and child-level factors. Parent participants reported a willingness to receive vaccines during hospitalizations, which aligned with physician participants' experiences. Another key facilitator identified by parent and physician participants was the availability of shared immunization data. Identified by parent and physician participants included the availability of shared immunization data. Barriers included being unaware that the child was vaccine-eligible, parental beliefs against vaccination, and ED and inpatient physicians' perceived lack of skills to effectively communicate with vaccine-hesitant parents. CONCLUSIONS: Parents and physicians identified several key facilitators and barriers to vaccinating during hospitalization. Efforts to provide inpatient vaccines need to address existing barriers.

Urban-rural disparities in interfacility transfers for children during COVID-19.

PURPOSE: We aimed to identify temporal trends and differences in urban and rural pediatric interfacility transfers (IFTs) before and during the COVID-19 pandemic. METHODS: We conducted a cross-sectional analysis of IFT among children <18 years from January 2019 to June 2022 using the Pediatric Health Information System. The primary outcome was IFTs from general hospitals to referral children's hospitals. The primary exposure was patient rurality, defined by Rural-Urban Commuting Area codes. We categorized IFTs into medical, surgical, and mental health diagnoses and analyzed trends by month. We calculated observed-to-expected (O-E) ratios of pre-pandemic (March 2019-Feb 2020) transfers compared to pandemic year 1 (March 2020-Feb 2021) and year 2 (March 2021-February 2022) using Poisson modeling. FINDINGS: Of 419,250 IFTs, 18.8% (n = 78,751) were experienced by rural-residing children. The O-E ratio of IFT in year 1 for urban children was 14.0% (95% confidence interval [CI] 13.8, 14.2) and 14.8% (95% CI 14.4, 15.3) for rural children compared to pre-pandemic (P = .0001). In year 2, transfers rebounded with IFTs for rural-residing children increasing more than urban-residing children (101.7% [95% CI 100.1, 103.4] compared to 90.7% [95% CI 89.0, 90.4], P < .0001). For mental-health indications in year 2, rural transfer ratios were higher than urban, 126.8% (95% CI, 116.7, 137.6) compared to 113.7% (95% CI 109.9, 117.6), P = .0168. CONCLUSIONS: Pediatric IFTs decreased dramatically during pandemic year 1. In year 2, while medical and surgical transfers continued to lag pre-pandemic volumes, transfers for mental health indications significantly exceeded pre-pandemic levels, particularly among rural-residing children.