Primer Series

T8 Saturday, November 10 8:30 am - 4:30 pm
Introduction to Biomedical and Health Informatics
Dominic Covvey, University of Waterloo, Waterloo, Ontario, Canada
John Holmes, University of Pennsylvania, Philadelphia, PA
Chris Cimino, Albert Einstein College of Medicine, Bronx, NY

This is an intense, multi-instructor, full-day tutorial intended to introduce those with little or no knowledge of informatics, to the nature, key concepts, and applications of this discipline. We examine what the field is about and how it can help us address key challenges in the health field. Major objectives of the tutorial include enhancing the value of the conference to the participant and helping the participant discover specific topics of interest that can be explored both during and after the conference. Although no tutorial of this duration can cover all topics, the material targets the high profile areas of informatics such as clinical or health care informatics, bioinformatics, and public health informatics, and points the participants in the direction of broader and deeper enquiry.

By the end of the tutorial, participants will be able to:

• Understand the current landscape of the science and practice of Health Informatics.
  
• Better determine and define your areas of interest in informatics.
  
• Select sessions at the conference in your areas of greatest interest.
  
• Launch a systematic process of broadening and deepening their knowledge.
  
• Access Health Informatics information resources.
  

• Health, Health care, and their Challenges for Health Informatics
  
• Bioinformatics
  
• The Nature, Structure, and Management of Health Data, Information, and Knowledge
  
• The Nature, Structure, and Management of Health Data, Information, and Knowledge "Intelligent" Health Systems
  
• Health Communications Systems
  
• The Health User Interface and Interactive Systems
  
• Human/Social Aspects of Health Information Systems
  
• Major Healthcare Applications
  
• Major Healthcare Applications
  
• Health Informatics Education
  
• The Future and Persistent Issues in Health Informatics
  

• List and describe some online medical virtual worlds
• Describe the technology underlying virtual worlds
• Identify the advantages and limitations of individual and team training in these environments
• Describe methods of evaluating individual and team performance in virtual worlds
• Identify opportunities and issues in integrating virtual worlds into medical curricula.

• What is an online virtual world? "Serious Games"; 3D graphical representation of real spaces; a virtual learning environment that affords/supports both exploration and guided activity
• Avatars, NPCs and assets - "Avatars" or computer characters controlled by real people; AI and computer-controlled characters; 3D graphics; computing requirements for avatar-avatar and avatar-object interaction
• Identifying learning goals - Assessing learners' needs and analysis of learning goals; types of learning outcomes best suited for training with virtual worlds
• Design and development of medical scenarios
• Medical models: Methods of representing patient physiology and pathology
• Assessment of individual and team performance in multi-person medical scenarios
• Integrating Virtual Worlds training into medical curricula
• Guidelines for training with distributed, flexible learning technologies

• Describe the transformational goals of the CTSA program and examples of biomedical informatics initiatives to support those goals
• Understand the current organization of the Biomedical informatics initiatives within the CTSA program
• Apply lessons learned so far in the CTSA program to their own institutional programs
• Identify additional resources in other large collaborative projects that can help meet the goals of the CTSA program

• Introduction to the CTSA program
• Transformational goals and examples of Biomedical Informatics initiatives to support those goals
• Current organization of the CTSA program biomedical informatics initiatives
• Lessons learned so far
• Additional collaborative resources
• Question and answer period

• Understand the basics of grid computing, web services, and internet technologies
• Learn how to deploy Grid services of value to the biomedical informatics community.
• Access standard HealthGrid related services such as security, data management, execution management, information services and common runtime.
• Access standard Open Source toolkits for building Grid services.
• Build HealthGrid services to address informatics issues of identity management, storage, security services, access and integration, community scheduling framework, workspace management and resources allocation.
• Understand what organizations are leading the HealthGrid, developing standards, and how to engage in the HealthGrid community.

• Fundamentals of Grid computing infrastructure
• Grid Services
• Grid Toolkits
• HealthGrid Applications and Communities of Practice
• HealthGrid Organization

• Students will be able to identify the 3 UMLS Knowledge Sources, and describe how systems developers can use these data and programs to build electronic information systems that process biomedical and health data and information.
• Students will understand how the Metathesaurus data files represent many different vocabularies (including SNOMED CT and RxNorm, HIPAA standard code sets, etc.) in a common, explicit format, while preserving "source transparency" for each individual vocabulary.
• Students will know how to (1) access UMLS resources via the UMLS Knowledge Source Server (UMLSKS), including its Web browser; and to (2) use MetamorphoSys to install the UMLS and to produce customized Metathesaurus subsets, and search and view subsets using the companion RRF Browser.

• UMLS Introduction and Overview
• Metathesaurus
• Semantic Network
• SPECIALIST Lexicon and Tools
• UMLS Tools (UMLSKS, MetamorphoSys, & the RRF Browser)
• UMLS Use Cases

• Learn about the basic principles of wireless communication technologies and be familiar with fundamental concepts and their acronyms.
• Know the advantages and disadvantages of various wireless communication modalities useful in health care settings.
• Select and configure simple wLANs, which are HIPAA compliant.
• Recognize the difficulty of setting up mobile communication environments involving dif-ferent networks such as WiFi wLANs and 3G cellular networks.
• Appreciate the security concerns of wireless communication in health care.

• Fundamental concepts of wireless communication for local, personal, and wide area net-works. Current and evolving standards with their advantages and disadvantages.
• Fundamental concepts of current wireless wider area networks using cellular communica-tion technologies such as GSM and CDMA and their migration towards a third genera-tion (3G) system.
• Mobile communication for voice, data, and video using Internet protocols.
• Planning for wireless networks and practical considerations related to reliability and se-curity in health care settings.
• Description and experiences of using a wLAN in the Emergency Department and a dis-cussion of a mobile wireless wide area network using WiFi, Wi-Max, and 3G technolo-gies for communicating in the pre-hospital EMS environment.

• Understand the basic principles of data mining
• Apply appropriate data mining techniques in clinical research
• Interpret data mining results and how they inform statistical analysis

• Biomedical databases
• Data visualization
• Intelligent data analysis
• Explanatory data mining
• Predictive data mining
• Data mining software
• Applications of data mining in biomedical domains
• Data preparation: methods for cleaning, reduction, and coding
• Association rule discovery
• Classification and prediction
• Clustering and visualization
• When to data mine
• Evaluating data mining software
• Ethical concerns in data mining

• Understand why biologists and clinicians use each measurement technology, and the advantages of each.
  
• Be able to explain which genomic and genetic methods are most appropriate for studying diseases.
  
• Be able to list high-level requirements for an infrastructure relating research and clinical genetic and genomic data.
  

• Health, Healthcare, and their Challenges for Health Informatics
• Bioinformatics
• The Nature, Structure, and Management of Health Data, Information, and Knowledge "Intelligent" Health Systems
• Health Communications Systems
• The Health User Interface and Interactive Systems
• Human/Social Aspects of Health Information Systems
• Major Healthcare Applications
• Health Informatics Education
• The Future and Persistent Issues in Health Informatics

• Know what ontologies are and how they are structured and developed
  
• Know about some important ontologies used in biomedical informatics
  
• Know how ontologies are used to build representative types of application systems in biomedical informatics
  

• What is an ontology?
  
• Kinds of ontologies
  
• Open-Directory Project
  
• Foundational model of anatomy
  
• Gene ontology
  
• NCI Thesaurus
  
• EON
  
• Applications of ontologies
  
• Structured-data entry for EHR
  
• Information retrieval
  
• Data annotation
  
• Knowledge-based systems
  
• Languages for building ontologies
  
• Principles of ontology development
  
• Tools for building and managing ontologies
  
• Future trends
  
• Model-Driven Architecture
  
• The Semantic Web
  

T5 Saturday, November 10 8:30 am - 12:00 pm
Evaluating Health IT Projects: A Practical Approach
Caitlin M. Cusack, Partners Healthcare, Wellesley, MA
Dan Gaylin, National Opinion Research Center, Chicago, IL

For years, health IT (HIT) has been implemented with the goals of improving clinical care processes, health care quality, and patient safety. In short, it's been viewed as the right thing to do. In those early days, evaluation took a back seat to project work. Frequently, evaluations were not performed at all - at a tremendous loss to the health IT field. Given the large investment required for HIT projects, our stakeholders are increasingly demanding to know both the actual and future value of these projects. As a field we are moving away from talking about theoretical value, to a place where we must measure real value. Isolated studies and anecdotal evidence are not enough - not for our stakeholders, nor for the health care community at large. Evaluations must be viewed as an integral piece of every project, not as an afterthought.

While much has been written about the theory of evaluation, there has been a dearth of practical real-world tools to ease the process of writing evaluation plans. As more health IT projects have kicked-off, the lack of such practical tools has become even more apparent. The instructors in this course have taken the theory of evaluating HIT, and developed a practical approach to planning and executing evaluations. The tutorial has been designed to share these tools with others as they embark on developing evaluation plans of their own.

By the end of the tutorial, participants will be able to:

• Compile metrics for a health IT project
  
• Determine which metrics are practical to measure
  
• Formulate a plan around the chosen metrics
  
• Write an evaluation plan
  

• Motivations behind evaluation
  
• The National Resources Center Evaluation Toolkit: how to write an evaluation plan
  
• Quantitative, qualitative, and survey Considerations
  
• Conducting evaluations on a shoestring case study
  
• Turning theory into practice
  

• the assumptions and motivation for formal definitions of detailed clinical models
  
• how standard coded terminologies are referenced by detailed clinical models, and the different roles that SNOMED CT and LOINC play in the models
  
• the various alternative logical models for implementing clinical models related to diagnoses, allergies, problems, procedures, orders, and observations.
  
• the importance of adhering to terminology and modeling standards in developing or purchasing interoperable EHR systems
  
• national and international activities for sharing models that enable interoperability of EHR systems
  

• What are detailed clinical models?
  
• Why are detailed clinical models important?
  
• What are the requirements for defining and using detailed clinical models?
  
• Name-value pair (NVP) and entity-attribute-value (EAV) strategies for representing clinical data
  
• What are the proper roles for use of LOINC, SNOMED CT, drug codes (First Data Bank, RxNorm) and classifications in the models
  
• The necessity of supporting both pre and post coordinated models in a clinical system
  
• Approaches to the representation of negation and pertinent negative findings
  
• Storing data that belongs to another person (relative, family member, donor) in the patient record
  
• Specific alternatives for modeling including observations, diagnoses, problems, procedures, allergies
  
• Open candid discussion of ideas that the participants have about ways that the modeling issues can be addressed
  
• Importance of supporting open consensus standards for EHR systems that are purchased or developed
  
• Brief discussion of various national and international activities related to formal clinical data models
  

• Understand a systematic approach to addressing key health care organizational goals through a clinical decision support program.
  
• Understand the broad range of potential clinical decision support interventions, and opportunities to use them to accomplish specific objectives.
  
• Describe individual techniques and considerations for overcoming organizational and technical barriers to successful clinical decision support.
  

• A 6-step process for improving outcomes with CDS
  
• Key tasks and lessons for accomplishing each step in successful CDS implementation
  
• Case example of building a successful CDS program to accomplish your objectives using CDS program development worksheets
  
• Interactive discussion addressing questions you've always wanted to ask about CDS
  
• Developing an action plan to bring back to your organizations
  
• Overcoming organizational and technical barriers to successful CDS
  

• Have an understanding of the splitter's view of the benefit of EHRs
  
• Have an understanding of the power of loosely coupled components when supporting different but overlapping roles
  
• Have an approach to breaking up the EHR problem to deliver benefit earlier and less expensively
  

• Granular benefit framework
• Measurable quality or cost return
• Changes required (Process, Role, Technology) for that return
• Shortest path to that return
• Putting pieces together to gain speed and flexibility:
• Case example: How decoupled PHRs and EMRs might work together
• Staging implementation of EHR components to deliver benefit in excess of cost
• Examples of how this might be done in a mall practice or health system

• Understand the current state of eRx.
• Learn of the impact of eRx on ambulatory prescribing including new challenges associated with implementing this technology for clinicians, pharmacists and office staff.
• Learn how eRx can dramatically impact prescribing workflow, including unexpected effects on office staff responsibilities.
• Learn how inpatient medication reconciliation has been addressed with an IT solution /tool used. Similarly, attendees will learn of plans to also address post-discharge medication reconciliation requirements.
• Understand a balanced perspective on the unintended consequences of IT, CPOE and eRx.
• Learn of large scale efforts at regional and national levels to implement and evaluate eRx use in diverse clinical settings.

• Electronic prescribing
• Ambulatory prescribing with decision support
• Medication reconciliation
• Unintended consequences of eRx
• Overview of the eRx research agenda

• Understand how clinical data standards influence the functionality and usability of EHRs
• Evaluate the appropriate roles and the strengths/limitations of several prominent data standards
• Appreciate the practical difficulties of applying existing data standards effectively within EHRs
• Understand a number of current initiatives striving to increase the value of standards for EHRs, including the ELINCS lab-reporting project

• Purpose/role of data standards in ambulatory EHRs
• No EHR is an island
• Semantic interoperability
• Important data standards for EHRs
• Messaging standards (HL7, NCPDP SCRIPT)
• Document standards (CCR, CDA)
• Terminology standards (LOINC, SNOMED-CT, NDC, RxNorm, other drug terminologies)
• Issues/barriers in the practical adoption and use of data standards
• Current initiatives to address/overcome barriers
• Work of private entities (HL7, Connecting For Health)
• Work of federal government (HITSP, CCHIT, NLM)
• Case Study: ELINCS (EHR-Laboratory Interoperability and Connectivity Standards)

T2 Saturday, November 10 8:30 am - 12:00 pm
Building Bayesian Decision Support Systems
Peter J. Haug, Intermountain Health Care, Salt Lake City, UT
Dominik Aronsky, Vanderbilt University, Nashville, TN

Medical decision support systems are often required to classify patients in accordance with patterns recognized in their data. Uncertainty and missing information are an inherent characteristic of the medical domain. In contrast to rule-based systems, Bayesian systems are able to model uncertainty and missing information explicitly. The availability of large databases makes Bayesian systems attractive for creating decision support systems in the medical domain. The tutorial gives attendees a theoretical and practical introduction to Bayesian systems. Participants are provided with some basic theoretical background that is necessary for developing and understanding Bayesian systems. Theory will be balanced with hands-on experience in the construction of simple Bayesian systems (with an emphasis on Bayesian belief networks). Database requirements and evaluation techniques to assess the systems' accuracy will be discussed. A demonstration of more complicated Bayesian models as well as systems currently in use, gives participants an idea how and where systems can be applied. To participate in the hands-on exercises participants need to bring an IBM-compatible laptop.

By the end of the tutorial, participants will be able to:

• Understand the theoretical background of probabilistic reasoning
• Review of existing Bayesian systems and understanding their advantages and disadvantages
• Become familiar with the requirements for building, implementing and evaluating Bayesian systems

• Introduction to Bayesian systems
• Technical Background including Bayes theorem
• Definitions for common terms
• Introduction to Netica, a Windows-based application for building Bayesian systems
• Basic software functionality
• Different models of Bayesian systems
• Performance and accuracy of decision support
• Evaluation of Bayesian systems
• Using databases for creating applications with Bayesian systems

• Understand the theoretical challenges and concrete steps needed to create semantically interoperable health care instruments.
• Have an overview of which agencies and organizations are addressing which aspects of the problem space, and how their efforts are being aligned.
• Articulate, from first-hand experience, how rapidly certain aspects of this problem can be solved.
• Participate in on-going efforts to create national libraries of such instruments

• Scoping the Problem - Types of Instruments & Opportunities for Improvement from Standardization
• Theory: Sources of Complexity in Modeling Instruments
• Applied: How NY Addressed These Issues to Standardize Mental Health Tools
• Achieving Standardization: DHHS Sponsored Project to Standardize CMS Instruments
• Update on Standardization Efforts Along Many Axes: Content, Semantics, Messaging, Business Logic, Presentation Layer
• Lingering Challenges
• Demonstration: Using existing tools to fully standardize an paper instrument
• Hands-On Practice: Letting participants use same tools to standardize their own instrument.

• Describe the main components of public health practice
• Describe how local, state, and federal public health agencies work together and exchange information
• Describe the structure and function of a public health surveillance system
• Discuss at least two issues that are currently the focus of public health informatics research and practice

• The structure of public health
• A local health agency perspective on public health informatics
• A state health agency perspective on public health informatics
• A federal perspective on public health informatics
• Assessment/monitoring/surveillance systems in public health
• The future of public health informatics

• Recognize key concepts included in HL7 Version 3
• Understand the approach and objectives used in the creation of the standard
• Understand the overview of the standard, not sufficient for implementation but sufficiently detailed to enable the attendee to understand the scope and contents of the standard.

• HL7 Clinical Document Architecture
• HL7 Continuity of Care Document

• Define the process and role of evaluation within the field of informatics.
• Given an evaluation study, identify the approach that it employs.
• State specific evaluation questions, appropriate to an informatics project setting.
• Analyze evaluation studies with attention to issues of measurement and demonstration study design.

• What is evaluation, why do we do it and why is it difficult?
• Alternative approaches to evaluation, and their underpinnings
• The range of what can be studied in informatics
• Quantitative (objectivist) approaches in depth: measurement and demonstration studies.

• Define and describe three major categories of systems related to translational research
• Describe twelve success factors for implementing clinical systems
• Understand implementation issues specific to translational research systems
• Outline a set of evaluation methods for investigating these issue

• Definitions of types of translational research systems
• Overview of success factors for clinical systems implementation
• Differences between success factors for clinical and research systems
• Categories of issues specific to translational research systems implementation
• Evaluation methods for addressing these issues

T7 Saturday, November 10 8:30 am - 12:00 pm
Confidentiality and Privacy in the Context of RHIOs
Mark Frisse and Vicki Y. Estrin, Vanderbilt University, Nashville, TN

Successful exchange of health care information within a community is dependent as much on trust as it is on technology. Trust among stewards of personal health care information can be established if there is a formal organizational structure and set of policies and contractual arrangements among those who exchange data and those whose data are exchanged. In this tutorial we will describe how a large community health information exchange (the MidSouth eHealth Alliance) used the Markle Foundation's Connecting for Health Common Framework as the basis for forging such agreements in an operational exchange involving 19 major institutions and over 1 million records. This tutorial will be based on a 2006 workshop held at the Vanderbilt Center for Better Health.

By the end of the tutorial, participants will be able to:

• Describe the Markle Foundation's Connecting for Health Common Framework
• Know a basic approach to data sharing agreements and patient confidentiality
• Understand the important issues surrounding privacy and confidentiality when exchanging data across organizations
• Outline a process for creating data sharing agreements in their own communities

• Regional data exchanges - unique aspects
• The Markle Foundation Connecting for Health Common Framework
• Other national efforts, including the Health Information Security and Privacy Collaboration
• Application of the Markle Data Sharing agreements to the Memphis-based MidSouth eHealth Alliance
• Organization and governance
• Initial agreements
• A process for continual evolution and change
• Major challenges

1. Understand the motivation and challenges to standardized coding of clinical data from local, national, and international perspectives
2. Identify a minimum of five desiderata for high-quality controlled terminologies and describe the extent to which existing controlled terminologies meet these desiderata
3. Discuss the relationships among standards for terminologies, information models, messages, and document and record architectures and the role of advanced terminology tools in achieving semantic interoperability

• Types of terminology systems
• National and international contexts (motivations and challenges) for the development and dissemination of terminologies and classifications
• Desiderata for high-quality controlled terminologies
• Overview of selected terminologies such as ICD, SNOMED CT, LOINC, NANDA and application to a patient case study
• Relationships among standards for terminologies, information models, messages, and document and record architectures
• Demonstration of advanced terminology tools and discussion of their role in achieving semantic interoperability
• International and national initiatives

• Understand the complexities of using clinical data for research and be given methods and approaches for which to solve local problems.
• Understand the concept and value of structuring clinical data such that queries against disparate data can be performed.
• Understand the various solutions that currently exist for querying and visualizing clinical data.

• Principles and methods for transforming clinical data for use in clinical research
• Organizing clinical data into databases for use in clinical research
• Visualizing and querying clinical data to test hypothesis
• Insights and solutions from querying and visualizing clinical data
• Limitations in using this data for clinical research

• Identify quality sources of nursing knowledge;
• Apply state-of-the-science standards to selection of knowledge;
• Describe the relationship of a professional practice framework to developing referential and actionable evidence;
• Participate in modeling of an exemplar protocol to develop actionable evidence;
• Discuss the translation of nursing knowledge across education, practice, and industry environments and related standards.

• Sources of nursing knowledge
• Evidence grading
• Standards for selection of nursing knowledge
• State-of-the-science standards to selection of knowledge
• Relationship of a professional practice framework to developing referential and actionable evidence
• Modeling of an exemplar protocol
• Translation of nursing knowledge across education, practice, and industry environments and related standards

• Differentiate personal health records from other information processing tools used in health care
• Develop a strategy to appraise the clinical consequences of PHRs
• Evaluate the technical requirements, ethical considerations and social value of personal health records.

• Personal Health Records and E-health portals
• Basic Definitions
• Shared features
• Unique aspects
• Demonstration - Prototypes and early approaches
• Tethered and untethered systems
• Portals to health care systems
• Clinical considerations
• Fostering health goals with PHRs and eHealth Portals
• Health education
• Personal health monitoring
• Communication with professionals
• Creating a life-long health record
• View from the National Scene
• AHIC, & HITSP
• Consumer empowerment use case and associated standards
• Health Plans initiative
• Social Benefits of PHRs and eHealth Portals
• Surveillance
• Public Health Education
• Health Services Research
• Technical Considerations and Challenges
• Platforms and Devices
• Integration with clinical information systems
• Human-computer interaction
• Policy Considerations
• Privacy
• Impact on clinician workload
• Burden on patients and families