AMIA 2011 Tutorials

Saturday, October 22, 2011, 8:30 am to 12:00 pm

Travis Good, HISTalkMobile, access.health, access.mobile, CarePilot, Seth Watkins, Steptoe & Johnson, Duke University, Whitney Winston, Steptoe & Johnson, Warren Hogarth, Sequoia Capital

This tutorial attempts to cover the entire venture creation process, from idea generation to business organization, with special emphasis on the unique perspective of the Informatician. Whether attendees have already launched a successful venture, and need to think critically about next-generation opportunities, or have ideas requiring further evaluation and development, all will learn how to protect IP and fund a start-up in an engaging, interactive experience. Participants will will learn about different types of money, the difference between angel investors and VCs and how to find both, at what stage and under what circumstances entrepreneurs should consider seeking investment. Tactics from our expert faculty will focus on:

• Exploring market opportunities surrounding your ideas and your research
• The tools to communicate the broader potential of your research and develop a presentation pitch about your idea
• Immersing in professional networks in the biomedical and health informatics fields

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

• Deconstruct tech transfer and the process of translating opportunities and solutions into something of value
• Uderstand the differences in evidence requirements in the peer reviewed world and the marketing world
• Articulate why entrepreneurship is valuable to their healthcare organizations and should be encouraged

Outline of Topics:

• The Entrepreneurial Career Path
• Identifying potential opportunities
• Gaining the right to use and protect the key resources
• Developing strategies to generate market interest
• Building organizations
• Protecting your Intellectual Property and Avoiding Legal Risk
• How to Win Financing (and Influence People)

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals; and computer scientists, system developers, and programmers.

Content level: 20% basic; 30% intermediate; 50% advanced

Saturday, October 22, 2011, 8:30 am to 12:00 pm

Shawn Murphy, Massachusetts General Hospital

Using data collected in the clinical care domain for clinical research poses many challenges. Clinical data is diverse in structure and reliability. It is generated in truly massive quantities, but for consumption mostly by human eyes, not by machines. To be useful for clinical research, the data must usually be transformed to a machine readable format. Considerations of sensitivity and specificity must be considered when performing these transformations. One then needs a systematic approach to organizing the data such that queries can be generated against seemingly disparate data. This usually translates into finding a suitable "atomic fact" and organizing the data into these discrete pieces. Finally, the data must be shown to clinical researchers and allowed to be queried in a format that provides insights into and hypothesis testing of the data.

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

• 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.

Outline of Topics:

• 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

Intended Audience: Scientists, clinical researchers, people working in safety and quality research, biomedical engineers and workers in bioinformatics, and programmers.

Content level: 100% Intermediate

Saturday, October 22, 2011, 8:30 am to 12:00 pm

Stanley Huff, Intermountain Healthcare

This tutorial provides models for flexible representation of patient data; the proper roles for standard terminologies like LOINC, SNOMED CT, First DataBank, and RxNORM; approaches to handling pertinent negative findings and negation; support for precoordinated data entry while storing the data in a post coordinated database; and storage of data that belongs to another patient in the patient record.

The tutorial describes the need for formal data models for the EHR and how standard terminologies are used in the models. Starting with use cases encountered while developing EHR systems at Intermountain Healthcare, the instructors will discuss the basic name-value pair paradigm for flexible representation of patient data; the proper roles for standard terminologies like LOINC, SNOMED CT, First Data Bank, and RxNORM; approaches to handling pertinent negative findings and negation; support for precoordinated data entry while storing the data in a post coordinated database; and storage of data that belongs to another patient (baby or donor) in the patient record.

There are no absolute prerequisites for this tutorial. However, those who have experience in designing, developing, configuring, and implementing EHR systems will find the tutorial more meaningful. Experience in modeling of medical data and knowledge of standard coded terminologies like SNOMED CT, LOINC, and RxNORM will also be very helpful.

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

• 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

Outline of Topics:

• 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

Intended Audience: Designers, developers, implementers of EHR systems, scientists, educators, researchers, and biomedical engineers interested in clinical data modeling and interoperability of EHR systems.

Content level: 50% Intermediate, 50% Advanced

Saturday, October 22, 2011, 8:30 am to 12:00 pm

Sponsor: Academic Forum

Vimla L Patel, School of Biomedical Informatics, UTHealth; Mark Carroll, Health Informatics, University of California, Davis; Judith J. Warren, University of Kansas School of Nursing; Michael F. Chiang, Oregon Health & Science University

The practices of teaching and learning are intimately related. The best practices in teaching relate to the best learning outcomes, and they follow from a combination of activities: encouraging faculty development as teachers; engaging students with high levels of thinking in their studies, using most current instructional methods available; and implementing regular, thoughtful, and periodic assessment procedures to provide ongoing feedback: to students about the progress of their learning, and to program faculty about how well their program is meeting its objectives. The best teaching, just like the best science and the best medicine, is a moving target and so the process of pursuing best practice is just a process, something fluid and dynamic that we all try to stay actively involved with as much as we possibly can.

Informatics is a multidisciplinary field and it lives equally in both the world of practice and the world of science. This is what makes the filed complex in terms of training. As a science, it is concerned with the structuring and representation of knowledge and models of information processing in human beings and computers. Practice in informatics focuses on the design and implementation of systems and tools that facilitate the delivery of information, such as health care, and can be used to train practitioners as well as to support research.

This tutorial will attempt to capture the current status of the field in terms of instruction in Informatics, and the nature of what makes a successful training program, successful. Lectures and discussions will be lead by four faculty members, who have expertise in teaching and learning in informatics from variety of perspectives.

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

• Identify the relationship between the theoretical foundation and the evaluation of practical problems in informatics
• Identify and approach challenges related to teaching introductory biomedical informatics courses to diverse groups of students
• Describe the selection of content and assignments for informatics courses and curricula
• Structure their program to the population of interest: researchers, IT professionals, clinicians, industry, and population health.

Outline of Topics:

• Overview of concepts from learning and cognitive sciences
• Informatics as a diverse discipline
• Informatics as science and as practice
• Basic understanding of best practices in teaching
• Lessons from teaching introductory biomedical informatics
• Challenges in teaching to diverse students
• Open-ended discussions with audience about problems in teaching Informatics course
• Review of principles of good practice in education.
• Approaches for selecting courses, assignments and evaluation strategies
• Demonstrate the assignments for teamwork as mentioned in the IOM reports
• Learning and evaluating informatics knowledge, skills, and abilities
• Similarities and differences: Training for Industry, academia and practice

Intended Audience: Informatics educators; Training directors, Industry with interest in informatics, health care professionals, informatics researchers

Content level: 80% basic; 10% intermediate; 10% advanced

Saturday, October 22, 2011, 8:30 am to 12:00 pm

Patricia Flatley Brennan, University of Wisconsin-Madison; Jonathan Wald, Partners HealthCare System; Stephen Ross, University of Colorado Denver

As the HIT landscape continues to differentiate, consumer facing health information technology solutions are assuming increasing importance in engaging people in self care and disease management. Personal health information tools provide lay people with access to subsets of their clinical records and with the health information management tools needed for self-care and effective health care utilization. Taking on many forms, including PHRs, iPhone apps, patient portals, stand-alone applications, and Web 2.0 services, these innovative IT tools may also enable better access to the health care systems resources, including health information, appointment scheduling and provider communication, and personal health tracking. Through case studies this tutorial will introduce clinicians, systems administrators, and IT developers to critical issues regarding the design and deployment of PHRs and other personal health information management tools. During the tutorial, participants will have an opportunity to examine and critically evaluate existing tools & applications, explore patient portals, and discuss technical, ethical and policy considerations related to the deployment of personal health records tools. An update of the national environment and trends enabling (or interfering with) deploying IT tools for direct-to-consumer will be provided: meaningful use, privacy policies, payment schemes and health reform. Participants are encouraged to appraise their institutions' current plans for deploying consumer facing HIT and to come prepared to engage in discussions regarding implementation challenges and anticipated benefits.

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

• Determine how consumer-facing health information technologies, including PHRs and patient portals could achieve practice and agency goals
• Pose solutions to the clinical and usability challenges of effective consumer-facing health information technologies
• Evaluate the technical requirements, ethical considerations and social value of personal health records

Outline of Topics:

• Personal health information management tools
• Personal Health Records, patient portals, iPhone apps for health
  • Web 2.0, social media & health 2.0 – what does it offer personal health information management
  • Microsoft HealthVault and Google Health - Where do they fit in?
  • Clinical Uses
    • Self-management—observations in daily living
    • Care coordination
    • Life-long records
• Design
  • Technical Considerations and Challenges
  • Platforms and Devices
  • Integration with clinical information systems
  • Human-computer interaction
  • Clinical considerations
  • Fostering health goals with PHRs and patient portals
  • Personal health monitoring
• Health Education
  • Communication with professionals
• Policy and the View from the National Scene
  • View from the National Scene
  • Meaningful Use
  • Privacy
  • Policy: Payment schemes and health care reform
  • Ethical Issues
  • Social benefits & challenges of consumer-facing health IT
• Public Health
  • Surveillance
  • Public Health Education
• Health Services Research

Intended Audience: Clinicians, managers of patient portals, health educators, public health practitioners, engineers and computer scientists who work with distributed information systems, integration of disparate data bases or network-level authorization, authentication, or privacy policies.

Content level: 50% Basic, 30% Intermediate, 20% Advanced

Saturday, October 22, 2011, 8:30 am to 12:00 pm

Sponsor: NLP WG

Leonard D'Avolio, VA Boston Healthcare System, Harvard School of Medicine, Dina Demner-Fushman, National Library of Medicine, Wendy Chapman, University of Pittsburgh, John Pestian, Cincinnati Children's Hospital Medical Center, University of Cincinnati

Natural language processing is the umbrella term used to describe the automated structuring and extraction of information formatted as free text. The demand for natural language processing technologies in medicine will grow significantly in the coming years. This growth will be fueled by the continuing adoption of the electronic medical record, increasing emphasis on quality measurement and improvement initiatives, and the growing need for evidence to be used as part of evidence-based medicine. This half-day tutorial is designed to introduce clinicians and informaticians to the practice, tools, techniques, and science of clinical natural language processing.

Instruction will be hands on, inter-active, and case driven. The tutorial will focus primarily on clinical NLP, although related uses and methods such as literature-based NLP and text mining will be discussed to lend context. Topics covered include: an overview of clinical NLP and its uses in medicine; a brief history of clinical NLP and the evolution of NLP methods; the challenges to NLP; the number of approaches used to process natural language and the strengths and weaknesses of each; implementation considerations, creating annotated corpora as training / test sets, evaluation of NLP, and a review of open source tools for natural language processing. Demonstrations and in-class exercises will be used to help tie the theory of NLP to everyday research problems addressed by these technologies. The tutorial will be taught by four instructors experienced as researchers, developers, and users of a variety of tools and approaches to clinical NLP. Users will also be exposed to several open source technologies for clinical NLP including the Unstructured Information Management Architecture (UIMA) and Knowtator for manual annotation. They will also experience, first hand, the challenges of clinical NLP through manual annotation of de-identified patient records.

Outline:

• Overview: What is NLP and how is it being used in medicine?
  • Literature
  • Clinical reports
  • Applied to bioinformatics
• What makes clinical NLP so difficult?
• Overview of policies affecting NLP
• Characteristics of the clinical documentation environment
• Different approaches to clinical NLP
  • Simple rules-based (information extraction)
  • Statistical
  • Symbolic or grammatical
  • Hybrid approaches
• The clinical NLP process
  • The various components of clinical NLP
  • Annotated corpora for training \ testing
  • The pipeline for clinical NLP software
  • Evaluation (its role in the process)
• Available open source tools and components
• Implementation considerations
• Evaluating clinical NLP (in greater detail)

By the end of this tutorial, attendees should be capable of:

• Describing the current uses of clinical NLP
• Describe the relationship between clinical NLP and related
techniques such as text and data mining
• Understand the challenges to clinical NLP
• Describe the various approaches to clinical NLP and their strengths and weaknesses
• Understand the process of clinical NLP and its various components
• Find available open source clinical NLP components, frameworks, and packages
• Identifying potential implementation concerns and challenges
• Understand the process of creating and using annotated corpora
• Interpret the performance of published clinical NLP research

Intended Audience: Any clinician or medical informatician with an interest in learning more about clinical NLP.

Content Level: 70% Basic, 30% Intermediate

Saturday, October 22, 2011, 8:30 am to 4:30 pm

Christopher G. Chute, Mayo Clinic, James J. Cimino, National Library of Medicine, and Mark Musen, Stanford University

Standardized terminologies and classification systems are an essential component of the information infrastructure that supports healthcare delivery and evaluation. Despite significant advances and increased motivation for the use of terminology systems, widespread integration of standardized terminologies into computer-based systems has not yet occurred. In this tutorial, we provide an overview of the state of the science related to terminologies and classification systems and demonstrate application of selected terminologies to a patient case study to highlight the strengths and weaknesses of various terminologies. Standardized terminologies alone are insufficient to achieve semantic interoperability. Consequently, the tutorial will include content designed to elucidate the relationships among standards for terminologies, information models, messages, and document and record structures. In addition, we will demonstrate the use of advanced terminology tools that facilitate the use of standardized terms in computer-based systems and provide an overview of significant international and national initiatives related to terminology systems.

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

• Understand the origins and evolution of terminologies and ontologies
• Appreciate the present state of the art in health terminology development and deployment
• Articulate the dependencies within Meaningful Use standards on ontologies and vocabularies
• Demonstrate practical access methods to many terminologies and ontologies

Outline of Topics:

• Historical appreciation of the evolution and development of terminology and ontologies
• An overview of current terminologies and ontologies used in clinical practice
• The relationship of terminologies and ontologies to Meaningful Use Standards
• Speculations about the future trends and current developments in health related terminologies and ontologies
• A laboratory practicum on accessing and using clinical terminologies
• Desiderata for practical and effective terminologies and ontologies
• Practical examples and demonstrations about current terminologies and ontologies

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals; computer scientists, system developers, and programmers.

Content level: 75% Basic; 25% Intermediate

Saturday, October 22, 2011, 8:30 am to 4:30 pm

Dominic Covvey, University of Waterloo; John Holmes, University of Pennsylvania; Christopher Cimino, Albert Einstein College of Medicine

This tutorial gives the 30,000-foot view of healthcare informatics through a combination of presentations and audience discussions. Experts in the field will describe the general principles, jargon, and major problems in each of a half dozen healthcare informatics domains. The audience will be given a chance to struggle with some of these problems to gain a sense of the underlying intricacies.

The session will orient participants as to the content of the major healthcare informatics domains and how they interact. While participants should not expect to be able to start solving informatics problems based on this tutorial, they should have an understanding of what the problems are, which ones are attractive to them, and how they can acquire more knowledge and training to enter into the domain.

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

• Attend any of the AMIA scientific sessions and have a basic understanding of what is being presented and why it is important,
• Make an informed choice of a healthcare informatics domain which they would like to learn more about,
• Know about several options for training opportunities to acquire that learning.

Outline of Topics:

• Human and Social Aspects of Systems and Usability
• Evaluation
• Nature and Structure of Health Information
• Bioinformatics
• Information Retrieval
• Public Health Informatics
• The Electronic Health Record
• Workflow Analysis

Intended Audience: Anyone new to healthcare informatics who is looking for a broad overview of the field. Informatics workers who are familiar with one domain but are looking to become familiar with other domains.

Content level: 90% Basic; 10% Intermediate

Saturday, October 22, 2011, 1:00 pm to 4:30 pm

Doug Fridsma, US DHHS Office of the National Coordinator for Health Information Technology and Mark Frisse, Vanderbilt University

As the complexity and expense of health care services grows, new means must be identified to ensure that information necessary to support health care is available wherever and whenever decisions must be made. A shift in focus from a provider-centric perspective to a patient-centric perspective is an essential part of a broader effort to provide more effective care. To support high-quality patient-centered care, information must be exchanged among all parties involved in decision-making and care provision. Such exchange often runs counter to prevailing data management and control paradigms.

This session will review how health information exchange can impact the American care delivery system. It will address the rationale for exchange, means of realizing exchange, and methods to demonstrate impact. Beginning with an historical overview, the session will emphasize Federal initiatives to promote the exchange of information, lessons learned from pioneering efforts, new approaches and emerging trends. Specific federal, state, and private-sector initiatives will be emphasized. Standards adoption, project initiation, governance, management, evaluation, privacy, security, and sustainability issues will be discussed in detail. The sessions are designed to be highly interactive.

On completing this tutorial, participants will be able to:

• Understand the rationale for health information exchange
• Develop a framework for understanding how information can be exchanged in different environments for different purposes.
• Review the impact exchange can have on patient care, health care costs, public health, biomedical research, secondary data use, and other pressing areas.Beacon communities and other initiatives will be discussed as exemplars.
• Identify the key barriers to health information exchange and, through informal case discussion, develop risk-mitigation strategies.
• Explore strategic means of developing sustainable exchange activities suitable to specific needs in regions, state and federal government, and the private sector.

Outline of Topics:

• Defining terms. What is HIE?
• Exploration HIE aims and economic frameworks. What is HIE “about”?
• A brief history of health information exchange.
• Representative HIE efforts. Local, regional, state, federal, private sector
• Approaches to HIE. Health information organizations, regional efforts, institutional efforts, health plan and other health information intermediary initiatives, federal efforts.
• A review of technologies required to achieve HIE.
• The critical role of standards.
• Applications for HIE. health care public health, secondary data use
• The critical role of trust. Governance, transparency, privacy, and security.
• Evaluation of the impact of HIE.
• Sustainability models for HIE.
• An exploration of possible immediate next steps.
• An overview of HIE "grand challenges."

Intended Audience: Health care administrators, researchers, and providers interested in a broad overview of HIE from the perspective of both Federal and private sector initiatives. This will not be a comprehensive tutorial of federal or state initiatives but instead will address how these and related efforts can be combined to achieve measurable and substantive impact on care and data use.

Content level: 0% basic; 75% intermediate;25% advanced

Saturday, October 22, 2011, 1:00 pm to 4:30 pm

Sponsor: Evaluation WG and ELSI WG

Bonnie Kaplan, Yale University and Annette L. Valenta, University of Illinois at Chicago, James G. Anderson, Purdue University

Successful implementation depends on understanding how health information technologies actually are used in practice. Sociotechnical approaches are grounded in theory and are evidence-based. They provide a way to analyze what people actually do when working with these technologies and why they do it. They assess how an application and workflow influence each other, how clinical and patient roles relate to system use, and what unintended consequences, patient safety issues, or user responses might occur. On-going, in situ sociotechnical evaluation can identify and forestall problems. The methods also can help prevent difficulties through better system design and implementation practices.

The tutorial will address how to identify challenges associated with designing and implementing both clinician-facing and patient-facing health information technologies. The presenters will draw on their own work and the experience of participants to engage participants in designing in situ evaluation for application development, implementation, and continued use. After some introductory didactic presentation, presenters and participants will discuss and design sociotechnical evaluations.

The tutorial presenters, Dr. Kaplan and Dr. Valenta, each have many years of experience in sociotechnical evaluation. Both are past chairs of the People and Organizational Issues Working Group. Dr. Kaplan authored chapters on qualitative evaluation in they key evaluation books and has published seminal methodological papers as well as evaluation studies. She has presented evaluation tutorials at AMIA, Medinfo, and other conferences. Dr. Kaplan currently is chair of the Ethical, Legal, and Social Issues Working Group. Dr. Valenta co-published the seminal paper on “Q,” which introduced this method to study human subjectivity to the biomedical and health informatics discipline. She created and has taught the course on “Social and Organizational Issues in Health Informatics” in UICs graduate curriculum for nearly 20 years. Dr. Valenta leads the AMIA 10x10 at UIC, for which Dr. Kaplan is a co-facilitator, and covers both sociotechnical theory and evaluation. Dr. Anderson has edited three books on evaluating the organizational impact of healthcare information systems and coauthored a book on ethics and information technology. He is a past chair of the Ethical, Legal and Social Issues Working Group and past chair of the Quality Improvement Working Group. He has been a member of the editorial board of the Journal of the American Medical Informatics Association since 2000. He has presented tutorials at six previous AMIA conferences.

Topics will include:

• Sociotechnical theory
• Why do evaluation
• Sample evaluation designs and what was learned from them
• Frameworks for evaluation
• Sociotechnical approaches to HIT design and on-going evaluation

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

• Describe key concepts in sociotechnical theory
• Employ sociotechnical evaluation frameworks
• Articulate the importance of on-going, in situ evaluation
• Design HIT projects and evaluations that include people, organizational, social, and ethical issues

Intended Audience: Clinicians, designers, researchers, scientists, managers, health care professionals, executives, and others involved in research, development, or deployment of information systems in health care.

Content level: 40% basic; 40% intermediate; 20% advanced

Saturday, October 22, 2011, 1:00 pm to 4:30 pm

Succeeding as an Accountable Care Organization (ACO) or Medical Home will require healthcare organizations to build an infrastructure capable of supporting care delivery and cost management across the continuum. This tutorial will examine the key components of these new healthcare delivery and cost models, highlighting the importance of health IT systems to support ongoing patient management, knowledge management and performance monitoring.

Hear about obtaining NCQA Patient Centered Medical Home recognition by following their designated standards to organize care around patients, work in teams and coordinate and track care over time. This partnership between the patient and their healthcare team is facilitated by registries, information technology, and health information exchange to assure that patients get the indicated care when and where they need and want it in an appropriate manner.

Similarly, ACOs create incentives for health care providers to work together to treat an individual patient across care settings – including ambulatory settings, hospitals, and long-term care facilities. The Medicare Shared Savings Program will reward ACOs that lower growth in health care costs while meeting performance standards on quality of care and putting patients first and at the center of all care. Again, hear how this is facilitated through the use of registries, information technology, and health information exchange. The proposed ACO regulation from CMS/HHS published in March 2011 will also be discussed.

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

• Discuss the characteristics, key components, and costs of new healthcare delivery models
• Describe the importance of health IT systems that support patient management, knowledge management and performance monitoring
• Explain the Medical Home partnership and its emphasis on providing patient-centered care
• Understand ACOs and the proposed regulatory framework from CMS

Outline of Topics:

• Infrastructure requirements for new models of care
• Components of ACOs and Medical Home
• Health IT systems to support
  • Patient management
  • Knowledge management
  • Performance monitoring
• Medical Home
  • Role of NCQA
  • Patient-provider partnership
  • Standards and Health Information Exchange
  • Registries
  • Team-based Care
• Accountable Care Organizations
  • Incentives for treatment
  • Medicare shared savings program
  • ACOs in Action
  • Performance Standards
  • Regulatory and policy issues

Intended Audience: Any clinician, informatician, or other healthcare professional with an interest in learning more about new healthcare delivery organizations.

Content level: 40% basic; 40% intermediate; 20% advanced

Saturday, October 22, 2011, 1:00 pm to 4:30 pm

Samson Tu, Stanford University, Mor Peleg, University of Haifa

This tutorial gives an overview of the issues involved in, methods for, and examples of implementing clinical decision support systems for guideline-based care.

Clinical practice guidelines, or more generally clinical recommendations, are summaries of evidence-based best practices. In recent years, there has been an explosion of published guidelines. Computer-based decision-support tools can enhance the implementation of these guidelines by bringing focused recommendations to care providers at the point of decision-making. This tutorial will first give a general introduction to the history and practice of clinical decision-support systems, and then look at alternative methods for representing and delivering clinical recommendations.

We will use examples of guideline-based knowledge-based systems that have been implemented to illustrate both technical aspects of system development and organizational aspects of deployment and integration into clinical workflow. The technical aspects will include the steps and problems involved in formalizing guideline recommendations in computable format, system architecture, and technical challenges of integrating an external application into a continually-changing IT environment. The organizational aspect will address successful strategies for implementing the system into multiple medical centers of a large health care network. Presentation will be mixed with exercises and demonstrations of actual clinical systems that can provide decision support to primary care clinicians.

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

• Discuss characteristics of CDSS that help or hinder their acceptance
• Describe alternative methods for representing computable CPGs
• Understand the steps and issues involved in encoding guideline knowledge
• Outline the issues involved in deploying, integrating, and maintaining a knowledge-based DSS for implementing guidelines

Outline of Topics:

• Introduction to CDSS
• Alert and reminder systems
• Alternative computable models of CPG
• The roles of standards
• Knowledge acquisition and maintenance for guideline-based CDSS
• Sociotechnical issues of deploying CDSS

Intended Audience: researchers; physicians, nurses, and other healthcare professionals; computer scientists, system developers, and programmers.

Content level: 20% Basic, 60% Intermediate, 20% Advanced

Saturday, October 22, 2011, 1:00 pm to 4:30 pm

Sponsor: NLP WG

Leonard W. D’Avolio, Mass. Veterans Epidemiology Research and Information Center (MAVERIC) and Harvard Medical School, Wendy W. Chapman, University of California San Diego, Dina Demner-Fushman, U.S. National Library of Medicine, National Institutes of Health, Guergana Savova, Children’s Hospital Boston and Harvard Medical School, Brett R. South, VA Salt Lake City Health Care System and University of Utah, and Scott L. DuVall, VA Salt Lake City Health Care System and University of Utah

In “Introduction to Clinical NLP” Part 1, the fundamental concepts of natural language processing are described. Part 2 advances attendees’ understandings by walking through each of these fundamental concepts as part of performing end-to-end applications using available open source NLP tools. The tutorial will follow a single clinical use case with variations provoking the use of several approaches to NLP. Demonstrations will be step-by-step and taught by NLP developers and researchers including creators of some the tools demonstrated.

The tasks in the exercise will include:

• Creation and annotation of training and test sets using eHOST
• Development and use of regular expressions for rules-based information extraction
• Use of UMLS knowledge bases & tools
• Creation and deployment of a grammatically-based concept-mapping pipeline using cTAKES
• Creation and deployment of machine learning-based document and concept-level extraction using ARC.
• Evaluation of results and pros and cons of various approaches will be discussed

By the end of this tutorial, attendees should be capable of:

• Understand the different types of NLP tools available
• Choose the appropriate tool for the clinical NLP task at hand
• Understand the process of creating and using annotated corpora
• Understand the process of clinical NLP and its various components
• Find available open source clinical NLP components, frameworks, and packages
• Describe the various approaches to clinical NLP and their strengths and weaknesses
• Identifying potential implementation concerns and challenges
• Interpret the performance of published clinical NLP research

This session is not designed to be training on any one specific tool but will give users a solid foundation for participating in projects that employ natural language processing.

Intended Audience: Any clinician or medical informatician with an interest in learning more about clinical NLP. Anyone that previously attended the Introduction to Clinical NLP tutorial is likely to benefit from this extension. This is not a training session on any one of the tools.

Content Level: 50% basic, 50% intermediate

Saturday, October 22, 2011, 1:00 pm to 4:30 pm

To analyze multiple different genomic data types. Bioconductor, a package repository for bioinformatics, contains 467 packages in addition of the 3128 general-purpose packages from R. The wide array of possibility make R a platform particularly suited for translational bioinformatics research. However, like other statistical software, the learning curve can be steep for some of us less versed in computer science. This tutorial is based on the successful workshop “Introduction to R programming” taught at Stanford.Participantswill be introduced to the basic ofthe R language through practical examples from real biomedical research projects.We will showadvance techniques on how different resources can be plug into R to perform an analysis and produce publication ready graphics.

At the end of this tutorial, participants will be able to:

• To import and export data from different resources, including databases.
• Use R to transform and manipulate their data and perform exploratory statistical graphs.
• Pre-process raw DNA microarray data and extract gene significantly regulated.
• Explore their gene list using supervised and unsupervised clustering algorithms
• Interpret their results using metadata from KEGG database.

Outline of topics:

• Introduction to the R console and interactivity concept
• How R represents objects
• Using the help function
• Producing publication grade quality graphics easily
• Directly downloading raw data from public microarray repositories
• Quality assessment of DNA microarray
• Clustering solution available in R
• Knowledge database and metadata accessible through R package repositories

Intended audience: Academic and professional wanting to gain hands-on skills to analyze biomedical or clinical data as well as an overview of R possibilities. Translational scientists and studentsinterested in analyzing their genomic data and to learn how to integrate them with external resources.

Content level: 30% Basic, 50% Intermediate, 20% Advanced

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Charles Jaffe, HL7, Blackford Middleton, Harvard-Partners, Chris Chute, Mayo Clinic, Stanley Huff, Intermountan Healthcare, Robert Dolin, Semantically Yours, LLC, Douglas Fridsma, Office of the National Coordinator for HIT/HHS, and Ed Helton, NCI/NIH

Healthcare IT Standards have often been viewed with only passing interest in the medical informatics community. The HITECH provisions of the ARRA legislation have brought their importance to the fore. These standards are essential if we are to achieve any of the regulatory provisions that require reuse of healthcare data. At the top of anyone's list, the essential elements would include decision support, vocabulary binding, privacy and security, quality measurement, and clinical research integration. In the end, successful implementation of any solution is predicated on collaboration across standards developers, realizing both quality improvement and cost effectiveness.

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

• Identify the key standards specified in the meaningful use final rule.
• Define the standards requirements for security and privacy
• Understand the specific vocabulary standards and their binding to transmission specifications
• Establish metrics underlying the business case of standards requirements
• Recognize the value of standards development for the integration of patient care and clinical research data
• Leverage the underlying HL7 standards for messaging and the key components of Clinical Document Architecture
• Appreciate the value basis of international standards development
• Integrate the key components of the National Health Information Network
• Develop a comprehensive view of the standards required for (semantic) interoperability

Outline of Topics:

• Standards for healthcare as keystone for interoperability
• Standards for security and privacy
• Vocabulary standards
• Return on investment for standards adoption and deployment
• Integration of standards for clinical research and patient care
• HL7 messaging and Clinical Document Architecture (CDA)
• NHIN Architecture and the evolution of the NHIN Direct
• ISO and the international community of standards development

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals; computer scientists, system developers, programmers, and CFOs

Content level: 30% Basic; 40% Intermediate; 30% Advanced

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Valerie Florance, National Library of Medicine, Eneida A Mendonca, University of Wisconsin Madison, and Justin B. Starren, Northwestern University

Success in obtaining research funding depends on many things, but especially on understanding the priorities of the funding agency and preparing an application that addresses those priorities effectively. This tutorial will provide a broad overview on the grant process, from topic development to application submission to peer review and award decisions. Topics will include fundamentals of good grant writing, interpretation of a funding announcement or RFA, preparation of a grant application, different funding mechanisms, roles and responsibilities of a principal investigator and key personnel, how to interpret and respond to reviewer’s comments, communication with grant program officers, analysis of reviews and strategies for response and re-application. The tutorial will cover general aspects of federally funded grants as well as grant opportunities provided by Foundations, but NIH will be the source of many examples. Faculty will share thoughts derived from their own experiences and from what they learned over the years writing and reviewing grant proposals. The faculty bring together many years experience spanning the roles of grant writer, grant reviewer, and NIH grant program officer.

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

• Understand the fundamental components of a research grant application
• Identify pitfalls to avoid in the application process
• Identify proposal format used by the majority of public funding agencies and how to use them
• Identify the best funder and funding mechanism for a proposal
• Prepare a budget and budget justification
• Identify key resources available to researchers (online tools, databases, etc.)
• Understand the funding announcement and criteria that will be used for review of scientific merit
• Identify issues that are appropriate to discuss with Program Directors and how to approach them
• Discuss ways to frame an informatics research project

Outline of Topics:

• Overview of funding mechanisms (grants, contracts, cooperative agreements) and announcement types
• Overview of research grant structure
• Grant preparation steps
• Personnel, budget and budget justification
• Grant review criteria—understanding “review speak”
• Communication with funding agency
• Useful links for grant related information

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals; Fellows and graduate students.

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Daniel Z. Sands, Cisco Internet Business Solutions Group, and Harvard Medical School

An important part of any career is giving presentations, yet many do it poorly, either ineffectively communicating the message, boring the audience, or both. And yet, presentation skills can be learned. Participants in this tutorial will learn effective presentation skills, learn best practices for slide design, and have the opportunity to try out skills. At some point, everyone needs to present their work, either orally or in written form. And surveys show that public speaking is a common phobia, and in some is more feared than death itself. Although writing for publication is taught at many stages of our careers, oral presentation skills get little attention. These skills are especially important since many people present more than they write for publication, and subsequently have many more opportunities to make an impression (either good or bad) and convey your ideas. As a result, even many experienced veterans in the field give poor presentations. Yet presentation skills can be taught, practiced, and learned. The purpose of this tutorial is to raise the quality of presentations in our field which will benefit both presenters and their audiences.

The format of the seminar will be a lecture and demonstration consisting of concrete advice, real-world examples and opportunities for attendee interaction. The presentation itself will incorporate principles being discussed, so the participants can better understand their application. After discussing presentation skills, there will be a discussion of the technologies that can be used, including some comments related to slide design and layout. Also in this tutorial, participants will be invited to do exercises to try what they have learned in a non-threatening environment. Finally, those who wish to bring their PowerPoint presentations can receive constructive critique from the instructor and class.

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

• Explain three parallels between oral presentation and performance
• Feel greater comfort speaking before audiences, both large and smal
l
• States three ways people hide when they present
• Explain the most important factor in connecting with your audience
• Describe three principles of effective use of slides

Outline of Topics:

• Why talk about this?
• Essential Elements
  • You!
  • Content
  • The show
• Audience interaction
• The medium
• Humor
• Handouts
• Design:
  • Fonts
  • Format
  • Color
  • Charts and Diagrams
• Animation
• Projectors
• Digital Video
• Student exercises
• Tips and final comments

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals.

Content level: 50% basic; 50% intermediate

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Faculty: John H. Holmes, University of Pennsylvania

This interactive tutorial introduces attendees to the theory, tools, and techniques for discovering knowledge in biomedical data. Using a well-known data mining life cycle as a conceptual framework, attendees will experience first-hand, thorough demonstration and direct participation, the techniques of mining clinical data. These techniques include data preparation, description and visualization, feature selection, mining association, classification, prediction rules, and clustering. A variety of mining algorithms will be explored with each technique. The capstone of the tutorial will be the application of mined data to informing traditional statistical analysis. The tutorial will include hands-on experience in using Weka, a well-known open-source data mining software suite. Although not required, attendees will get the most out of the tutorial if they bring a laptop to the session to participate in the hands-on sessions. Instructions for downloading and installing Weka will be sent to registrants approximately one week prior to the tutorial.

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

• 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

Outline of Topics:

• 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

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals; computer scientists, system developers, and programmers.

Content level: 70% Basic, 30% Intermediate

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Atul Butte, Stanford University

In 2005, Dr. Elias Zerhouni, Director of the National Institutes of Health (NIH), wrote "It is the responsibility of those of us involved in today’s biomedical research enterprise to translate the remarkable scientific innovations we are witnessing into health gains for the nation... At no other time has the need for a robust, bidirectional information flow between basic and translational scientists been so necessary." Clearly evident in Dr. Zerhouni’s quote is the role biomedical informatics needs to play in facilitating translational medicine. American Medical Informatics Association (AMIA) now hosts the Joint Summits on Translational Science of which the Summit on Translational Bioinformatics is one of the two components. This tutorial is designed around the successful curriculum used in Stanford's course in Translational Bioinformatics, one of the first courses to be offered in this field. This tutorial is designed to teach the basics of the various types of molecular data and methodologies currently used in bioinformatics and genomics research, and how these can interface with clinical data. This tutorial will address the hypotheses one can start with by integrating molecular biological data with clinical data, and will show how to implement systems to address these hypotheses. The tutorial will cover real-world case-studies of how genetic, genomics, and proteomic data has been integrated with clinical data.

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

• 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.

Outline of Topics:

• Basic understanding of various genome-scale measurement modalities: sequencing, polymorphisms, haplotypes, proteomics, gene expression, metabolomics, and others
• Crucial difference between genetic and genomic data
• Nature and format of expression, polymorphism, proteomics, and sequencing data
• Overview of the most commonly used structured vocabularies, taxonomies, and ontologies used in genomics research
• Description of the most frequently used analysis and clustering techniques
• How the genetic predisposition to disease is studied
• Use of genetic information across medical specialties
• How to find clinical genetic tests
• Genomic and clinical data to study patient disease-free status and survival
• How informatics can be used to identify potential drug targets
• Types of biomarkers
• Parallels between research methods in medical informatics and bioinformatics
• Relating clinical measurements with molecular measurements

Intended Audience: Academic faculty or professionals setting up bioinformatics facilities and/or relating these to clinical data repositories, or to data from General Clinical Research Centers or Clinical and Translational Science Awards; health information professionals responsible for clinical databases or data warehouses and tying these to researchers; informaticians, clinicians, and scientists interested in genetics, functional genomics, and microarray analysis; physicians interested in how medicine is advancing through the use of genomics and genetics; and students.

Content level: 20% Basic, 50% Intermediate, 30% Advanced

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Robert A. Jenders, US National Library of Medicine and Georgetown University, Bethesda, Maryland; Jerome A. Osheroff, TMIT Consulting, LLC and University of Pennsylvania, Cherry Hill, New Jersey; Jonathan M. Teich, Elsevier Health Sciences and Harvard University, Newton, Massachusetts; Dean F. Sittig, UT – Memorial Hermann Center for Healthcare Quality & Safety, University of Texas Health Science Center at Houston, Houston, Texas; and Robert E. Murphy, Memorial Hermann Healthcare System and University of Texas Health Science Center at Houston, Houston, Texas.

This tutorial will provide attendees with a practical approach to developing and deploying clinical decision support (CDS) interventions that measurably improve outcomes of interest to a health care delivery organization. The following key steps, including overcoming barriers, will be examined in detail: initiating an overall CDS program, including selecting appropriate CDS goals and enhancing organizational structures needed for CDS success in the context of current health care drivers and enablers; selectively implementing CDS technology to achieve a specific goal, with a focus on stakeholder and process analysis; knowledge management; and following up and monitoring CDS interventions. The role of national programs relevant to CDS, including knowledge sharing, structured guidelines and meaningful use, also will be explored. Special considerations in CDS for small clinical practices, for hospitals and health systems and for vendors will be explored. The systematic approach to CDS implementation will be presented in an interactive, case-oriented fashion, incorporating examples provided by tutorial leaders and participant's experiences. The course content is drawn from the tutorial leaders' popular and award-winning guidebook series on improving outcomes with clinical decision support, with newly revised material published this year.

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

• Follow a systematic process for developing, implementing and analyzing the effect of a clinical decision support program.
• Understand the types of CDS technology available for realizing desired outcomes.
• Detail factors both external and internal to a health care organization that drive CDS initiatives.

Outline of Topics:

• Selection of CDS goals.
• National programs relevant to CDS, including knowledge sharing, clinical guidelines and meaningful use.
• Developing organizational structures for implementing a CDS program.
• Selective implementation of goal-directed CDS interventions.
• Monitoring CDS interventions.

Intended Audience: Clinicians and administrators interested in quality improvement and patient safety; physicians, nurses and other health care professionals; and computer scientists, system developers and programmers interested in understanding applications of health information technology to clinical decision support.

Content level: 60% basic; 40% intermediate

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Soumitra Sengupta, Associate Clinical Professor, Dept of Biomedical Informatics, Columbia University, Information Security Officer, New York-Presbyterian Hospital & Columbia University Medical Center, New York, New York

Privacy and security of health care information were originally proposed under HIPAA, and were then revised under HITECH Act in 2009. In parallel, information technology and threats to the information have evolved significantly with the advent of mobility, cloud computing, wireless and health care systems and devices. This tutorial considers these modern regulations and threat concerns, discusses associated risks, and proposes balanced and practical methods to address them. Examining information system components and divided but shared responsibilities of all stake holders, an approach to privacy and security management is presented that is both reasonable and flexible.

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

• Understand the privacy and security principles
• Express risk management concepts and framework for information security
• Identify information systems’ stake holders and their responsibility
• Classify information assets, threats, risks and controls
• Learn from examples of security incidents; develop procedures to address them

Outline of Topics:

• Federal regulations and governance of privacy and security
• Health care privacy and security principles
• Risk management framework
• Security management organization and stake holder responsibility
• Information assets, classification, threats, controls
• Risk assessment methodology (HITRUST)
• Examples of security incidents
• Security controls

Intended Audience: Healthcare operations professionals; privacy and security professionals; researchers; physicians.

Content level: 25% basic; 50% intermediate; 25% advanced

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Sponsor: CRI-WG

Philip Payne, The Ohio State University; Peter Embi, University of Cincinnati

This tutorial provides participants with a unique opportunity to increase their knowledge and understanding of core Clinical Research Informatics (CRI) theories and methods, as well as recent policy and funding developments, in the context of a rapidly growing and increasingly high-demand informatics practice domain.

Clinical research is critical to the advancement of medical science and public health. Conducting such research is a complex, resource intensive endeavor comprised of a multitude of actors, workflows, processes, and information resources. Recent national-level research and policy efforts have explicitly focused on increasing the clinical research capacity of the biomedical sector, largely through fostering improvements in both workflow and information management infrastructure. These efforts have served to increase attention on clinical research throughout the governmental, academic, and private sectors. In the specific context of the intersection between biomedical informatics and clinical research, the emergence of both a notable body of literature and a set of targeted funding mechanisms such as the National Cancer Institute’s (NCI) Cancer Biomedical Informatics Grid (caBIG) and National Center for Research Resources (NCRR) Clinical and Translational Science Award (CTSA) programs have served as significant catalysts for the emergence of a robust sub-discipline of informatics focusing on clinical research applications, known as Clinical Research Informatics (CRI).

In this tutorial, we provide researchers, technical leaders, and technical staff with an overview of the core definitions and informatics theory that collectively contribute to the successful practice of CRI. We use a set of research vignettes to illustrate common challenges and opportunities in the CRI space and best-practice approaches to such scenarios, including: 1) the design and implementation of integrative clinical research information management systems; 2) the query of disparate enterprise and research information systems to support clinical research activities and information dissemination/reporting; and 3) the identification and recruitment of clinical research participants via multiple retrospective and prospective modalities.

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

• Define clinical research informatics and understand its relationship with other biomedical informatics sub-disciplines as well as the clinical/translational sciences
• Synthesize the role of current healthcare and informatics policy and standards setting developments relative to the practice of CRI
• Identify and apply core informatics theories, methods, and best practices in order to analyze and plan solutions to common clinical research information management challenges
• Plan for and implement complex information management architectures in order to support a full spectrum of clinical research activities

Outline of Topics:

• Clinical Research Informatics (CRI) definition and relationship(s) to other biomedical informatics sub-disciplines and the clinical/translational sciences
• Current CRI-relevant funding, policy, and standards-setting efforts or initiatives
• Enterprise architectures for integrative clinical research information management
• Semantic interoperability and knowledge engineering in the clinical research domain
• The relationship of human factors and/or workflow optimization to the effective deployment and utilization of clinical research information management systems
• Common CRI challenges and their solutions:
  • Integrating enterprise systems and CRI platforms
  • Querying disparate data sources in support of clinical research related analyses and/or information dissemination
  • Clinical research participant identification and recruitment

Intended Audience: Scientists; researchers; physicians, nurses, and other healthcare professionals; computer scientists, system developers, and programmers.

Content Level: 20% Basic; 50% Intermediate; 30% Advanced

Sunday, October 23, 2011, 8:30 am to 12:00 pm

Nigam H. Shah and Mark A. Musen, Stanford University

The National Center for Biomedical Ontology (NCBO) offers a range of Web services that allow users to access biomedical terminologies and ontologies, to use ontology terms to create pick lists and lexicons, to identify terms from controlled terminologies and ontologies that can describe and index the contents of online data sets (data annotation), and to recommend particular terminologies and ontologies that would be appropriate for data-annotation tasks. The tutorial will demonstrate the use of NCBO resources to facilitate tasks such as semantic data integration, information retrieval, structured data entry, and knowledge management. This tutorial will provide participants with in-depth understanding of how ontologies and terminologies are used to execute diverse research use cases in clinical and translational research. We will review example use cases for analyses using disease ontologies and for applying NCBO tools to compute the risk of having a myocardial infarction on taking Vioxx (rofecoxib) for Rheumatoid arthritis.

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

• Understand the biomedical ontology landscape
• Understand the national infrastructure available for data annotation and knowledge management
• Learn about NCBO supported Web service workflows for clinical and translational research.

Outline of Topics:

• Overview of NCBO key activities
• Ontologies available in Biomedicine
• Web-based tools for Ontology search, visualization and review
• Tools and Web Services for data annotation and integration
• Design of custom workflows to utilize national ontology-resources for research

Intended Audience: Scientists and researchers seeking to understand how to optimally use ontologies for problem solving. Health IT System developers and CIOs seeking to understand how to leverage NIH-funded infrastructure for using Ontologies.

Content level: 20% Basic; 60% Intermediate; 20% Advanced

Sunday, October 23, 2011, 8:30 am to 12:00 pm

E. Coeira, , Australian Institute of Health Innovation, D. Covvey, National Institutes of Health Informatics and University of Waterloo, R. Kolodner, Collaborative Transformations, LLC, and Open Health Tools, Inc., H. Lehmann, Johns Hopkins University

Introducing ehealth into our health system is a world-class challenge. Right now we are investing heavily in ehealth. This increases the risk that we are pursuing a rate of change that our health system cannot safely attain, especially given a limited complement of competent informatics human resources, the possible underestimation of needed effort and investment, and our understanding of the complexity of the health system. This could set the stage for failure.

One challenge for informatics solutions is that healthcare delivery systems are complex adaptive systems. To appreciate the implications of this, we will explore the nature of complexity and what it implies for developing, introducing and managing informatics interventions. In particular, we will question the current assumption that health care is a linear, non-interacting, predictable system and we will explore how complexity impacts our interventions. Then we will provide aides that will better equip us to deal with the challenges we face.

On completing this tutorial, participants will be able to:

• Understand the nature of complex adaptive systems and incorporate the lessons of Complexity Theory into their work.
• Conceptualize and implement new approaches to planning, development, implementation, management, and budgeting that are sensitive to the true nature of complex adaptive systems.
• Avoid the dead ends, traps, and failure modes that derive from our misconstruing health care as a linear, predictable system.
• Refocus their further study so as to more deeply appreciate and be able to apply Complexity Theory to their work.

Selected Topics Addressed in the Tutorial

• The nature of complexity and of complex adaptive systems.
• Nonlinearity and its implications.
• Human health and the health system as dynamic complex adaptive systems.
• Comparison the nature of healthcare to the nature of other industries regarding complexity.
• Aids for dealing with complexity.
• The implications of complexity related to developing, deploying and managing ehealth solutions.
• What we have learned about planning, development, implementation and management of complex adaptive systems and how this applies to healthcare.
• Lessons that we can draw from studies that change our view of what we currently do.
• Seeing where our implicit assumptions of low complexity come back to bite us.
• Better equipping ourselves to address the true nature of the challenges we face in incorporating ehealth into the health system.

Intended Audience: Health/Biomedical Informaticians, scientists, researchers, physicians and other healthcare professionals, system developers, management professionals and CIOs.

Content level: 25% basic; 50% intermediate; 25% advanced