Transforming electronic health record polysomnographic data into the Observational Medical Outcome Partnership's Common Data Model: a pilot feasibility study
Abstract Well-defined large-volume polysomnographic (PSG) data can identify subgroups and predict outcomes of obstructive sleep apnea (OSA). However, current PSG data are scattered across numerous sleep laboratories and have different formats in the electronic health record (EHR). Hence, this study...
Guardado en:
Autores principales: | Jeong-Whun Kim, Seok Kim, Borim Ryu, Wongeun Song, Ho-Young Lee, Sooyoung Yoo |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/fb9dd1478b724f68922232830a14aa88 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Thirty-day hospital readmission prediction model based on common data model with weather and air quality data
por: Borim Ryu, et al.
Publicado: (2021) -
Trajectories in glycated hemoglobin and body mass index in children and adolescents with diabetes using the common data model
por: Yun Jeong Lee, et al.
Publicado: (2021) -
Polysomnographic Sleep and Attentional Deficits in Traumatized North Korean Refugees
por: Lee J, et al.
Publicado: (2021) -
Qualitative and quantitative analyses of polysomnographic measurements in foals
por: Antonia Zanker, et al.
Publicado: (2021) - Pilot and feasibility studies