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Ux and research_computing_webinar_v2 Ux and research_computing_webinar_v2 Presentation Transcript

  • UX and Research Computing:Enabling Human-Centric Data AnalyticsAcademyHealth EDM Forum WebinarMay, 2013Philip R.O. Payne, Ph.D.Associate Professor and Chair, Biomedical Informatics (College of Medicine)Associate Professor, Health Services Management and Policy (College of Public Health)Associate Director for Data Sciences, Center for Clinical and Translational ScienceExecutive-in-residence, Office of Technology Transfer and Commercialization
  • Overview1) Definitions and key concepts• User experience (UX) research• Patient-centered research information needs• Current landscape2) A snapshot of what is possible Interactive data analytics3) Future directions4) Discussion
  • Overview1) Definitions and key concepts• User experience (UX) research• Patient-centered research information needs• Current landscape2) A snapshot of what is possible Interactive data analytics3) Future directions4) Discussion
  • User Experience (UX) Research UX can be defined as "a persons perceptionsand responses that result from the use oranticipated use of a product, system orservice” ISO 9241-210:2010 (Ergonomics of human-system interaction -Part 210: Human-centered design for interactive systems) In a computing context, UX research can beconcerned with (but not limited to): Human factors and workflow analysis Human-computer interaction (HCI) Data visualization Cognitive science
  • Origins of the Term “User Experience” “I invented the term because I thought humaninterface and usability were too narrow. Iwanted to cover all aspects of the person’sexperience with the system includingindustrial design, graphics, the interface, thephysical interaction, and the manual.” Attributed to Don Norman Discussing his prior work as Vice President of the AdvancedTechnology Group at Apple Computer
  • User Centered Design and UX
  • Alignment of UX with Patient CenteredResearch Information NeedsAdapted from: Embi PJ, Payne PR. The Role of Biomedical Informatics in Facilitating OutcomesResearch: Current Practice and Future Directions. Circulation. 2009. Dec 8;120(23):2393-9.UX!
  • An Interesting Intersection That is WorthFurther Exploration…UXPatientCenteredResearchEnhancedProductivity?Optimizingapproaches todata presentationand interactionEvaluatingheterogeneousand multi-dimensional dataImprovedquality, timeliness, and efficiency ofresearch
  • Critical Issues to Consider Human beings possess well-documented strengthsin the areas of pattern recognition and higher-orderreasoning that allow them to interpret complex data setsin ways that remain difficult to reproduce usingcomputers Given these capabilities, it is important to presentdata in a manner that optimizes human-computerinteraction. This need is pertinent to the broad domain of patientfocused healthcare research, such as comparativeeffectiveness research (CER), patient-centeredoutcomes research (PCOR), and quality improvement(QI) research
  • A Summary of Activity at The Intersection ofUX and Patient Centered Research (1) Funding for UX-relevant research, as compared toclinical research relevant funding or funding for otherareas, is low (around 2%) UX-relevant research and clinical research relevantresearch funding has expanded at a rate higher than thatof the total NIH award portfolio. The rate of growth for UX-relevant funding has notkept pace with the rate of growth for clinical researchrelevant funding. Publication rates have been and continue to be verylow, particularly in the context of methodologydevelopment
  • UX and Patient Centered Research: Funding (1)0.00%10.00%20.00%30.00%40.00%50.00%60.00%70.00%80.00%90.00%100.00%2007 2008 2009 2010 2011Distribution of Total Funding by AreaTotal NIH FundingClinical Research FundingUX Funding
  • UX and Patient Centered Research: Funding (2)0.750.850.951.051.151.251.351.452007 2008 2009 2010 2011Relative Funding Growth RateUX FundingClinical Research FundingTotal NIH Funding
  • UX and Patient Centered Research: PublicationsSummary of literature search and abstraction results for manuscripts withcurated MESH terms corresponding to both “clinical research” and somecombination of “computer-human interaction”, “usability” or “datavisualization”, published between 2010 and 2012.
  • A Summary of Activity at The Intersection ofUX and Patient Centered Research (2) Based on the preceding review of funding andpublications, it can be argued that:1) The application of UX theories and methods may improveour ability to understand the types of complex andheterogeneous data commonly encountered in the patientcentered research use cases2) Increased investment in UX research anddevelopment, particularly as it pertains to the broadclinical research domain, has the potential to increase“downstream” research productivity and resultantincreases in the applicable knowledge-base, with a lowmarginal cost3) Socio-cultural factors may play a role in the precedingissue
  • Overview1) Definitions and key concepts• User experience (UX) research• Patient-centered research information needs• Current landscape2) A snapshot of what is possible Interactive data analytics3) Future directions4) Discussion
  • A Rapid Tour of Interactive Data Analytics Important qualifiers:1) This is not a systematic review of the domain2) I likely have missed a number of important projectsand investigators3) I have selected a few personal favorites4) Not all of these are research-specific and severalare not focused on biomedicine Goals:1) Review a compelling examples of how UXapproaches can enable interactive, human analytics2) Highlight the work of a small number of veryproductive research groups working in this area
  • 3 Exemplary Sources of UX Innovation1) University of Maryland HCI Lab2) School of Interactive Computing @ GeorgiaTech3) VIZBI (International Biological DataVisualization Collaborative)
  • University of Maryland HCI Labhttp://www.cs.umd.edu/hcil/Ben Shneiderman, PhD
  • Example 1: Network Visualization bySemantic Substrates (1) Focus on supporting visual exploration ofdistributed and heterogeneous databases Enables human-controlled semantic partitioningof search space to improve specificity and fidelityof results Simplifies information retrieval task Supports cross-linkage of semantically relateddata, information, and knowledge resources Employs a network visualization approach toachieve these goalsSource: Aleks Aris and Ben Shneiderman, University of Maryland Human-Computer Interaction Lab
  • Example 1: Network Visualization bySemantic Substrates (2)Source: Aleks Aris and Ben Shneiderman, University of Maryland Human-Computer Interaction Lab
  • Example 2: Network Visualization ForScientific Literature Synthesis (1) Focus on enabling/supporting complex and“deep” search of scientific literature for discoveryand synthesis purposes Provides for integrated presentation of both: Text mining results (document summarization) Citation networks Helps end-users to identify critical “clusters” ofliterature and then explore the content ofscientific papers that cause them to be organizedas such.Source: Action Science Explorer, Cody Dunne, Robert Gove, Bonnie Dorr, Judith Klavans, VahedQazvinian, Dragomir Radev, and Ben Shneiderman, University of Maryland Human-Computer Interaction Lab
  • Example 2: Network Visualization ForScientific Literature Synthesis (2)Source: Action Science Explorer, Cody Dunne, Robert Gove, Bonnie Dorr, JudithKlavans, Vahed Qazvinian, Dragomir Radev, and Ben Shneiderman, University of MarylandHuman-Computer Interaction Lab
  • Example 3: Visualization of TemporalTrends in Biomedical Data (1) Lifelines data visualization tools supportssummarization of temporal trends in categoricaldata derived from EHRs Primary focus is on supporting/enablinghypothesis generation activities Built around a data selection  alignment ranking summarization zooming UImetaphor Analogous to human cognitiveprocesses/workflows in similar problem solvingcontextsSource: Lifelines2, Taowei Wang, Catherine Plaisant and Ben Shneiderman, University of Maryland Human-Computer Interaction Lab
  • Example 3: Visualization of TemporalTrends in Biomedical Data (2)Source: Lifelines2, Taowei Wang, Catherine Plaisant and BenShneiderman, University of Maryland Human-Computer Interaction Lab
  • Example 4: Interactive/Integrative Queryand Summarization for EHR Data (1) Event-based query engine for data as found inEHRs Uses a visual query language paradigm Enables creation of queries that are difficult toexpress using conventional, formal querylangauges Supports temporal summarization of bothmultivariate and categorical data Can integrate data sets beyond HER Literature, web, etc.Source: PatternFinder, Catherine Plaisant, Patricia Abbott and Ben Shneiderman, University of MarylandHuman-Computer Interaction Lab
  • Example 4: Interactive/Integrative Queryand Summarization for EHR Data (2)Source: PatternFinder, Catherine Plaisant, Patricia Abbott and BenShneiderman, University of Maryland Human-Computer Interaction LabAs Implemented in Amalga
  • Example 5: Identifying Critical Nodes inSocial Networks (1) Based on core assumptions of scale freenetwork theory Helps to identify key “gatekeepers” that serve tolink disparate groups of collaborators In this example case, used to identify such“gatekeepers” in the context of party affiliationand policy development, but can easily beapplied to: Scientific collaborations Socio-cultural determinant of diseaseSource: Ben Shneiderman, University of Maryland Human-Computer Interaction Lab
  • Example 5: Identifying Critical Nodes inSocial Networks (2)Source: Ben Shneiderman, University of Maryland Human-Computer Interaction Lab
  • Greg Abowd’s Lab: School of InteractiveComputing @ Georgia Techhttp://www.gregoryabowd.com
  •  Ubiquitous computing Mobile devices Sensors Data visualization Socio-cultural models Adoption Interaction UsabilityGreg Abowd’s Current HealthcareRelevant Research FociLeveraging mobile devices tocapture in-home “behaviorspecimens”
  • VIZBI: International Biological Data VisualizationCollaborative and Meeting Serieshttp://www.vizbi.orgUX: Its not just about clinical data!
  • VIZBI 2012: Interactive Kinome Inhibitor LibraryChandan Sona and V Badireenath Konkimalla (National Institute of Science Education and Research, Institute ofPhysics Campus, Sachivalaya Marg, PO: Sainik School, Bhubaneswar - 751 005 India)
  • VIZBI 2012: Integrative Visualization of Tumor Subtypes inCancer Genomics Data SetsAlexander Lex, Marc Streit, Hans-Joerg Schulz, Christian Partl, Dieter Schmalstieg, Peter J. Park, Nils Gehlenborg(Harvard Medical School, Boston, USA; Broad Institute, Cambridge, USA; Graz University ofTechnology, Graz, Austria; Johannes Kepler University, Linz, Austria; University of Rostock, Rostock, Germany)
  • VIZBI 2012: Visualization and Analysis of Very LargeNetwork Graphs from High Dimensional DataThanos Theo and Tom Freeman (The Roslin Institute The University of Edinburgh Easter Bush Midlothian EH259RG Scotland, UK)
  • Key Take Home Items…1) Human-centric design matters2) UX enables hybrid approaches to analytics that leverage bothcomputational and human strengths Discovery Pattern recognition Temporal reasoning Summarization3) Mobile and senor technologies represent emergent opportunitiesfor both data collection and UX innovation4) Network theory is common in current UX trends Real-world (e.g., social) Data-centric Predictive5) UX innovation with biomedical relevance is largely happeningoutside of the traditional AHC setting
  • Overview1) Definitions and key concepts• User experience (UX) research• Patient-centered research information needs• Current landscape2) A snapshot of what is possible Interactive data analytics3) Future directions4) Discussion
  • Towards aConceptualModel forResearch andInnovation at theIntersection ofPatient-CentricHealth Researchand UXInnovation
  • Future Directions (1) Several critical resources must be leveraged to support/enablepatient centric research: EHR-derived clinical phenotypes Patient-reported data Bio-molecular phenotypes Supporting sources of knowledge (such as that found in publicdata sets or bibliographic databases) Therefore, we should undertake UX-focused research anddevelopment related to: The presentation of and interaction with structured, semi-structured, and unstructured data found The visualization of complex and heterogeneous data The provision of systematic and reproducible dataintegration, presentation, and interaction “pipelines”
  • Future Directions (2) Investments in UX related research related to the facilitation ofpatient centered research are not “keeping pace” with the growth inuser needs for such methods and technologies. This trend is evidenced both in terms of grants and contracts, as wellas downstream contributions to the state of knowledge evidenced viapeer-reviewed literature. Therefore, I believe that increased policy and funding support for UXresearch and development with direct relevance to the patientcentered research domain Ideally, new support mechanisms would be designed in a mannerthat includes tight coupling of UX research efforts with drivingbiological and clinical problems This will require community dialogue!
  • Overview1) Definitions and key concepts• User experience (UX) research• Patient-centered research information needs• Current landscape2) A snapshot of what is possible Interactive data analytics3) Future directions4) Discussion
  • Science 2.0: A Vision for a Future Where UXInnovation is Critical to Knowledge GenerationBen Shneiderman’s work highlighted in Science, Sciene Today, and Wired MagazineCoverage in 2008 – what about now?
  • Discussion Items1) Is the current level of investment in UXresearch appropriate relative to the broaderNIH funding portfolio?2) Is there a need for a community-developedresearch agenda at the intersection of UX andpatient-centered research?3) What (if any) socio-cultural or policy changesare needed to advance UX innovation in thecontext of patient-centered research?
  • Thank you for your time and attention!• philip.payne@osumc.edu• http://go.osu.edu/payne