Protocol for EHR laboratory data preprocessing and seasonal adjustment using R and RStudio

Victorine P. Muse; Søren Brunak

doi:10.1016/j.xpro.2024.102912

Protocol for EHR laboratory data preprocessing and seasonal adjustment using R and RStudio

Victorine P. Muse, Søren Brunak^*

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

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Abstract

Seasonality in laboratory healthcare data is associated with possible under- and overdiagnoses of patients in the clinic. Here, we present a protocol to analyze electronic health record data for seasonality patterns and adjust existing reference intervals for these changes using R software. We describe steps for preprocessing population-wide patient laboratory data into a single dataset. We then detail steps for defining strata, normalizing to median, and fitting data to selected functions. For complete details on the use and execution of this protocol, please refer to Muse et al. (2023).¹

Originalsprog	Engelsk
Artikelnummer	102912
Tidsskrift	STAR Protocols
Vol/bind	5
Udgave nummer	1
Antal sider	11
ISSN	2666-1667
DOI	https://doi.org/10.1016/j.xpro.2024.102912
Status	Udgivet - 2024

Bibliografisk note

Funding Information:
We thank the Novo Nordisk Foundation ( NNF14CC0001 and NNF17OC0027594 ) as well as the Danish Innovation Fund ( 5184-00102B ) for providing funding for the study. V.P.M. is the recipient of a fellowship from the Novo Nordisk Foundation as part of the Copenhagen Bioscience PhD Programme, supported through grant ( NNF19SA0035440 ).

Publisher Copyright:
© 2024 The Author(s)

Adgang til dokumentet

10.1016/j.xpro.2024.102912Licens: CC BY-NC-ND

FulltextForlagets udgivne version, 2,83 MBLicens: CC BY-NC-ND

Citationsformater

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