Model correction of diagnostic coding-based RSV incidence for children 0–4 years in the US

Autor: Sabina O. Nduaguba, Phuong T. Tran, Almut G. Winterstein
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-8 (2024)
Druh dokumentu: article
ISSN: 1471-2334
DOI: 10.1186/s12879-024-09474-y
Popis: Abstract Background Although administrative claims data have a high degree of completeness, not all medically attended Respiratory Syncytial Virus-associated lower respiratory tract infections (RSV-LRTIs) are tested or coded for their causative agent. We sought to determine the attribution of RSV to LRTI in claims data via modeling of temporal changes in LRTI rates against surveillance data. Methods We estimated the weekly incidence of LRTI (inpatient, outpatient, and total) for children 0–4 years using 2011–2019 commercial insurance claims, stratified by HHS region, matched to the corresponding weekly NREVSS RSV and influenza positivity data for each region, and modelled against RSV, influenza positivity rates, and harmonic functions of time assuming negative binomial distribution. LRTI events attributable to RSV were estimated as predicted events from the full model minus predicted events with RSV positivity rate set to 0. Results Approximately 42% of predicted RSV cases were coded in claims data. Across all regions, the percentage of LRTI attributable to RSV were 15–43%, 10–31%, and 10–31% of inpatient, outpatient, and combined settings, respectively. However, when compared to coded inpatient RSV-LRTI, 9 of 10 regions had improbable corrected inpatient LRTI estimates (predicted RSV/coded RSV ratio
Databáze: Directory of Open Access Journals
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