Automated Travel History Extraction From Clinical Notes for Informing the Detection of Emergent Infectious Disease Events: Algorithm Development and Validation.
Kelly S PetersonJulia LewisOlga V PattersonAlec B ChapmanDaniel W DenhalterPatricia A LyeVanessa W StevensShantini D GamageGary A RoselleKatherine S WallaceMakoto M JonesPublished in: JMIR public health and surveillance (2021)
Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.
Keyphrases
- infectious diseases
- electronic health record
- machine learning
- deep learning
- coronavirus disease
- sars cov
- healthcare
- loop mediated isothermal amplification
- high throughput
- mental health
- adverse drug
- case report
- emergency department
- current status
- health information
- quality improvement
- label free
- quantum dots
- real time pcr
- advance care planning