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Medical Informatics: Opportunities for Improving Patient Care Ben Shneiderman ben@cs.umd.edu @benbendc Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies
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IOM Report: Health IT and Patient Safety Problem - Poorly designed health IT can create new hazards in the already complex delivery of care. - Dosing errors, failure to detect life-threatening illnesses & delaying treatment due to poor HCI or loss of data have led to serious injury & death. Recommendations: - User-centered design & human factors applied to health IT www.iom.edu/Reports/2011/ Health-IT-and-Patient-Safety-Building-Safer-Systems-for-Better-Care.aspx
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Strategic Health IT Advanced Research Projects (SHARP): Office of National Coordinator - Security of Health Information Technology - Patient-Centered Cognitive Support - Healthcare Application and Network Platform Architectures - Secondary Use of EHR Data Sharpc.org www.cs.umd.edu/hcil/sharp
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HCIL’s Research Initiatives Medical Lab Tests - Tracking Completion in Complex Workflows - Guidelines for Design of Tables & Actions - Retrospective Analysis Medication Reconciliation Patient Histories – Analysis & Search - Temporal Event Sequences - Point & Interval Events Wrong Patient Errors (BONUS)
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Medical Lab Tests Tracking Sharpc.org www.cs.umd.edu/hcil/sharp
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Medical Lab Tests Tracking & Retrospective Analysis www.cs.umd.edu/hcil/sharp
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Medication Reconciliation: Current Form www.cs.umd.edu/hcil/sharp Univ of Maryland HCIL tasks - Missing Laboratory Reports - Medication Reconciliation - Alarms and Alerts Management www.youtube.com/watch?v=ZGf1EiuIIIM
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Prototype by Tiffany Chao VIDEO AVAILABLE AT www.cs.umd.edu/hcil/sharp Prototype by Tiffany Chao VIDEO: www.cs.umd.edu/hcil/sharp
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Successful adoption efforts 10 Example # 1: Twinlist running on Microsoft Amalga Platform Contact: Hank Rappaport Example #2: Twinlist adapted for problem list reconciliation in cancer risk assessment (Hughes riskApps™ - an EHR module) Contact: Kevin S. Hughes, Massachusetts General Hospital
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Patient Histories: LifeLines www.cs.umd.edu/hcil/lifelines2
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Patient Histories: LifeLines2 www.cs.umd.edu/hcil/lifelines2
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Patient Histories: LifeFlow www.cs.umd.edu/hcil/lifeflow
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Patient Histories: EventFlow www.cs.umd.edu/hcil/eventflow
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Patient Histories: PairFinder www.cs.umd.edu/hcil/pairfinder
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Temporal Event Sequences www.cs.umd.edu/hcil/lifelines2 /eventflow /pairfinder ToolEvent TypesRecordsDisplay LifeLinesPoints & intervalsOneOne record LifeLines2PointsManyMany records SimilanPointsManyMany records LifeFlowPointsManyMany records & aggregate EventFlowPoints & intervalsManyMany records & aggregate PairFinderPointsManyTemporal record distributions
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Reducing Wrong Patient Errors: Animated Transitions & Photos BONUS
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Reducing Wrong Patient Errors: Animated Transitions & Photos
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( Taieb-Maimon, Plaisant & Shneiderman, 2012) The combination of animation & photo resulted in a significant increase in error recognition rate relative to the control & animation groups Dramatic implications for commercial systems Control Photo Combined 36% Animation 7% 43% 63%63% Reducing Wrong Patient Errors: Animated Transitions & Photos
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www.cs.umd.edu/hcil/sharp Take Away Messages Healthcare is fertile area for HCI & InfoVis Patient Safety is a national priority We have tools for analysts Tomorrow: Workshop on EHR Informatics Thanks to: Oracle Corporation NIH/National Cancer Institute grant RC1-CA147489, SHARP grant 10510592 – Office of National Coordinator www.cs.umd.edu/hcil/lifeflow /eventflow /pairfinder
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