TY - GEN
T1 - Environmental Geomarker to Assess Impact on Hospitalization
AU - Sato, Kikue
AU - Furukawa, Taiki
AU - Kobayashi, Daisuke
AU - Oyama, Shintaro
AU - Shiratori, Yoshimune
N1 - Publisher Copyright:
© 2024 The Authors.
PY - 2024/8/22
Y1 - 2024/8/22
N2 - By linking medical real-world data with geographic information, it is possible to evaluate the impact on hospitalization based on these characteristics, such as patient residence information and disease and medical information. In this study, environmental exposure to air pollutants was reported as a risk factor, and predictive models were used to examine factors affecting health. The importance of the characteristics appeared according to the disease, and overall, the patient profile at the time of admission, such as ADL, was shown to be high, but for respiratory diseases, the cumulative concentration of air pollutants NO2, SPM, and NOx for one year before the onset of admission was the top risk factor for long-term hospitalization, suggesting the influence of exposure due to environmental factors.
AB - By linking medical real-world data with geographic information, it is possible to evaluate the impact on hospitalization based on these characteristics, such as patient residence information and disease and medical information. In this study, environmental exposure to air pollutants was reported as a risk factor, and predictive models were used to examine factors affecting health. The importance of the characteristics appeared according to the disease, and overall, the patient profile at the time of admission, such as ADL, was shown to be high, but for respiratory diseases, the cumulative concentration of air pollutants NO2, SPM, and NOx for one year before the onset of admission was the top risk factor for long-term hospitalization, suggesting the influence of exposure due to environmental factors.
KW - Air Pollutants
KW - Geomarker
KW - Machine Learning
KW - Predictive Model
UR - http://www.scopus.com/inward/record.url?scp=85201998467&partnerID=8YFLogxK
U2 - 10.3233/SHTI240720
DO - 10.3233/SHTI240720
M3 - 会議への寄与
C2 - 39176508
AN - SCOPUS:85201998467
T3 - Studies in Health Technology and Informatics
SP - 1574
EP - 1575
BT - Digital Health and Informatics Innovations for Sustainable Health Care Systems - Proceedings of MIE 2024
A2 - Mantas, John
A2 - Hasman, Arie
A2 - Demiris, George
A2 - Saranto, Kaija
A2 - Marschollek, Michael
A2 - Arvanitis, Theodoros N.
A2 - Ognjanovic, Ivana
A2 - Benis, Arriel
A2 - Gallos, Parisis
A2 - Zoulias, Emmanouil
A2 - Andrikopoulou, Elisavet
PB - IOS Press BV
T2 - 34th Medical Informatics Europe Conference, MIE 2024
Y2 - 25 August 2024 through 29 August 2024
ER -