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VitalCore: Analytics and Support Dashboard for Medical Device Integration.
Choi, Hyonyoung; Lor, Amanda; Megonegal, Mike; Ji, Xiayan; Watson, Amanda; Weimer, James; Lee, Insup.
Afiliação
  • Choi H; Dept. of Computer and Information Science, University of Pennsylvania.
  • Lor A; Penn Medicine, University of Pennsylvania.
  • Megonegal M; Penn Medicine, University of Pennsylvania.
  • Ji X; Dept. of Computer and Information Science, University of Pennsylvania.
  • Watson A; Dept. of Computer and Information Science, University of Pennsylvania.
  • Weimer J; Dept. of Computer and Information Science, University of Pennsylvania.
  • Lee I; Dept. of Computer and Information Science, University of Pennsylvania.
Article em En | MEDLINE | ID: mdl-35582521
ABSTRACT
Medical professionals spend extensive time collecting, validating, reviewing, and analyzing medical device data. These devices use vendor-specific applications with lengthy troubleshooting times, causing extended downtimes where medical professionals have to manually document patient data in the electronic health record (EHR). Manual logging of this data creates delays and leaves it vulnerable to errors, manipulation, and omissions. In this paper, we present VitalCore, a medical device integration platform that supports access to medical device data in real-time. We deploy VitalCore in three applications at Penn Medicine Medical Device Dashboard, Ventilation Alert, and Anomaly Detector. In the Medical Device Dashboard, we reduced, by up to six times, the amount of time required of medical professionals, clinical engineers, and IT analysts by simplifying the troubleshooting workflow, thus decreasing downtimes and increasing clinical productivity. In Ventilation Alert, we demonstrated the ability to assist medical professionals by alerting them to newly ventilated patients. In Anomaly Detector, we showed that we could predict anomalous patterns in our data with 93% accuracy.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_sistemas_informacao_saude Tipo de estudo: Guideline Idioma: En Revista: IEEE Int Conf Connect Health Appl Syst Eng Technol Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 1_ASSA2030 Problema de saúde: 1_sistemas_informacao_saude Tipo de estudo: Guideline Idioma: En Revista: IEEE Int Conf Connect Health Appl Syst Eng Technol Ano de publicação: 2021 Tipo de documento: Article
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