title: EHDViz: clinical dashboard development using open-source technologies.
abstract: OBJECTIVE
  To design, develop and prototype clinical dashboards to integrate high-frequency health and wellness data streams using interactive and real-time data visualisation and analytics modalities.
  
  
  METHODS
  We developed a clinical dashboard development framework called electronic healthcare data visualization (EHDViz) toolkit for generating web-based, real-time clinical dashboards for visualising heterogeneous biomedical, healthcare and wellness data. The EHDViz is an extensible toolkit that uses R packages for data management, normalisation and producing high-quality visualisations over the web using R/Shiny web server architecture. We have developed use cases to illustrate utility of EHDViz in different scenarios of clinical and wellness setting as a visualisation aid for improving healthcare delivery.
  
  
  RESULTS
  Using EHDViz, we prototyped clinical dashboards to demonstrate the contextual versatility of EHDViz toolkit. An outpatient cohort was used to visualise population health management tasks (n=14,221), and an inpatient cohort was used to visualise real-time acuity risk in a clinical unit (n=445), and a quantified-self example using wellness data from a fitness activity monitor worn by a single individual was also discussed (n-of-1). The back-end system retrieves relevant data from data source, populates the main panel of the application and integrates user-defined data features in real-time and renders output using modern web browsers. The visualisation elements can be customised using health features, disease names, procedure names or medical codes to populate the visualisations. The source code of EHDViz and various prototypes developed using EHDViz are available in the public domain at http://ehdviz.dudleylab.org.
  
  
  CONCLUSIONS
  Collaborative data visualisations, wellness trend predictions, risk estimation, proactive acuity status monitoring and knowledge of complex disease indicators are essential components of implementing data-driven precision medicine. As an open-source visualisation framework capable of integrating health assessment, EHDViz aims to be a valuable toolkit for rapid design, development and implementation of scalable clinical data visualisation dashboards.
authors.affiliation: Harris Center for Precision Wellness, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Marcus A
authors.initials: MA
authors.lastname: Badgeley
authors.affiliation: Harris Center for Precision Wellness, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Khader
authors.initials: K
authors.lastname: Shameer
authors.affiliation: Harris Center for Precision Wellness, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Benjamin S
authors.initials: BS
authors.lastname: Glicksberg
authors.affiliation: Harris Center for Precision Wellness, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Max S
authors.initials: MS
authors.lastname: Tomlinson
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Anesthesiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Levin
authors.affiliation: Department of Anesthesiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: McCormick
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Kasarskis
authors.affiliation: Department of Anesthesiology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: David L
authors.initials: DL
authors.lastname: Reich
authors.affiliation: Harris Center for Precision Wellness, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, New York, USA.
authors.forename: Joel T
authors.initials: JT
authors.lastname: Dudley
mesh_terms: D003626:Data Display; D003628:Database Management Systems; D003695:Delivery of Health Care / Q000592:standards*; D004582:Electronics, Medical / Q000379:methods*; D020407:Internet
keywords: biomedical informatics; clinical dashboard; clinical decision systems; data visuzalization; early warning systems