1 / 14

Jim Ong Trinka Coster, MD Kevin Leary, MD Ida Sim, MD PhD Stephen Porter, MD

Data Visualization Authoring And Display Tools For Patient Data Review. Jim Ong Trinka Coster, MD Kevin Leary, MD Ida Sim, MD PhD Stephen Porter, MD. Stottler Henke Walter Reed Army Institute of Research Uniformed Services Univ. of the Health Sciences UC San Francisco School of Medicine

domoniquel
Download Presentation

Jim Ong Trinka Coster, MD Kevin Leary, MD Ida Sim, MD PhD Stephen Porter, MD

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Data Visualization Authoring And Display Tools For Patient Data Review Jim Ong Trinka Coster, MD Kevin Leary, MD Ida Sim, MD PhD Stephen Porter, MD • Stottler Henke • Walter Reed Army Institute of Research • Uniformed Services Univ. of the Health Sciences • UC San Francisco School of Medicine • Harvard Medical School • This research was funded in large part by the Office of the Secretary of Defense (OSD) and was managed by the U.S. Army Telemedicine and Advanced Technology Research Center (TATRC).

  2. Goal and Assumptions Goal Current state-of-the-art Limitations • Help clinicians review patient data more effectively before, during, and after patient encounters to improve patient care and increase patient safety. • EMRs that employ web application servers, relational databases • Source-oriented queries • Modest use of graphics • Time-consuming and difficult for clinicians to query and mentally integrate patient data from different EMR screens. .

  3. Our Approach Patient Views DataMontage Dense, graphical displays of subsets of the patient’s medical history that support various clinical perspectives – such as: medical problem body system demographic group treatment protocol Modular software toolkit for creating and displaying dense, coordinated timelines and time-series graph displays. Operates standalone or embedded w/in a desktop, client-server, or web-based system.

  4. View Design Method 1. 2. 3. 4. 5. 6. Analyzed clinical guidelines to identify relevant patient data, reference values, organization, and presentation Gathered clinician input, developed strawman designs Identified data available in clinical database Developed mockups of initial graphical display design Elicited clinician feedback and refined view design Implemented view generation logic

  5. Cardiac View (ICDB) Module Graph Reference ranges Show/hide module roll over  short text notes mouse click  html detail Timeline high in normal range

  6. Reference value Diabetes View (ICDB) Datetime reference line Non-linear time scale

  7. Selecting a time-stamped note draws a datetime reference line Normal range / grid lines

  8. DataMontage mockup

  9. Hypertension View (ICDB)

  10. Coordinated Cross-Patient and Single-Patient Views

  11. Coordinated Cross-Patient and Single-Patient Views

  12. DataMontage Editor Overview pane Details pane

  13. DataMontage Java API

  14. DataMontage Summary COTS Product Applications Benefits • First production release: 9/04 • 5/14/07 - version 2.0 • Patient Care • Drug Safety • Quality Assurance • Improved patient care • Increased patient safety .

More Related