TY  - GEN
N2  - The term Adverse Safety Events (ASEs) refers to harm from medical errors and, if considered a disease, would rank third among the leading causes of death in the U.S. Patient safety research has traditionally performed manual review of patient care records (PCR) to characterize ASEs and develop prevention strategies. Manual review is labor-intensive, which prohibits continuous monitoring and improvement. Automating detection of ASEs would overcome these barriers and allow the healthcare community to address safety issues at a population scale. Our objective is to demonstrate the feasibility of automatically detecting safety events in PCRs.
DO  - 10.6083/wp988k473
DO  - DOI
AB  - The term Adverse Safety Events (ASEs) refers to harm from medical errors and, if considered a disease, would rank third among the leading causes of death in the U.S. Patient safety research has traditionally performed manual review of patient care records (PCR) to characterize ASEs and develop prevention strategies. Manual review is labor-intensive, which prohibits continuous monitoring and improvement. Automating detection of ASEs would overcome these barriers and allow the healthcare community to address safety issues at a population scale. Our objective is to demonstrate the feasibility of automatically detecting safety events in PCRs.
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
T1  - Enhancing epidemiological safety in prehospital care by detecting adverse events in patient care records
ED  - American Medical Response
ED  - Collaborator
DA  - 2020
AU  - Bahr, Nathan
AU  - Kain, Alexander
AU  - Bedrick, Steven
AU  - Guise, Jeanne-Marie
L1  - https://digitalcollections.ohsu.edu/record/8340/files/ResearchWeek.2020.Bahr.Nathan.pdf
PB  - Oregon Health and Science University
PY  - 2020
ID  - 8340
L4  - https://digitalcollections.ohsu.edu/record/8340/files/ResearchWeek.2020.Bahr.Nathan.pdf
KW  - Safety Management
KW  - Medical Records
KW  - Classification
KW  - Neural Networks, Computer
KW  - Epidemiology
KW  - chart review
KW  - patient care records
KW  - adverse safety events
TI  - Enhancing epidemiological safety in prehospital care by detecting adverse events in patient care records
Y1  - 2020
L2  - https://digitalcollections.ohsu.edu/record/8340/files/ResearchWeek.2020.Bahr.Nathan.pdf
LK  - https://digitalcollections.ohsu.edu/record/8340/files/ResearchWeek.2020.Bahr.Nathan.pdf
UR  - https://digitalcollections.ohsu.edu/record/8340/files/ResearchWeek.2020.Bahr.Nathan.pdf
ER  -