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Topics in BMI: Course Objectives

Topics in BMI: Course Objectives. Prof. Steven A. Demurjian, Sr. Computer Science & Engineering Department The University of Connecticut 371 Fairfield Road, Box U-255 Storrs, CT 06269-2155. steve@engr.uconn.edu http://www.engr.uconn.edu/~steve (860) 486 - 4818. What is Informatics?.

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Topics in BMI: Course Objectives

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  1. Topics in BMI: Course Objectives Prof. Steven A. Demurjian, Sr. Computer Science & Engineering Department The University of Connecticut 371 Fairfield Road, Box U-255 Storrs, CT 06269-2155 steve@engr.uconn.edu http://www.engr.uconn.edu/~steve (860) 486 - 4818

  2. What is Informatics? • Informatics is: • Management and Processing of Data • From Multiple Sources/Contexts • Involves Classification (Ontologies), Collection, Storage, Analysis, Dissemination • Informatics is Multi-Disciplinary • Computing (Model, Store, Process Information) • Social Science (User Interactions, HCI) • Statistics (Analysis) • Informatics Can Apply to Multiple Domains: • Business, Biology, Fine Arts, Humanities • Pharmacology, Nursing, Medicine, etc.

  3. What is Informatics? Informatics People Information Technology Adapted from Shortcliff textbook • Heterogeneous Field – Interaction between People, Information and Technology • Computer Science and Engineering • Social Science (Human Computer Interface) • Information Science (Data Storage, Retrieval and Mining)

  4. What is Biomedical Informatics (BMI)? • BMI is Information and its Usage Associated with the Research and Practice of Medicine Including: • Clinical Informatics for Patient Care • Medical Record + Personal Health Record • Bioinformatics for Research/Biology to Bedside • From Genomics To Proteomics • Public Health Informatics (State and Federal) • Tracking Trends in Public Sector • Clinical Research Informatics • Deidentified Repositories and Databases • Facilitate Epidemiological Research and Ongong Clinical Studies (Drug Trails, Data Analysis, etc.)

  5. What are Key BMI Focal Areas? • T1 Research • Transition Bench Results into  Clinical Research • Clinical Research • Applying Clinical Research Results via Trials with Patients on Medication, Devices, Treatment Plans • T2 Research • Translating “Successful” Clinical Trials into Practice and the Community • Clinical Practice • Tracking all of the Information Associated with a Patient and his/her Care • Integrated and Inter-Disciplinary Information Spectrum

  6. Where/How is BMI Utilized? T1 Research (Bench  Clinical) • Transfer of Knowledge from Laboratory or Bench to Clinical Trials • Move Genomic Research from Bench (Lab) to Clinical Trial (or Genetic/Test Intervention) • Transfer in Lab/Bench Research to Pre-Clinical and Early Clinical Human Subject Research • Exs: • New Genetic Test for Autism • Tested on Samples from DNA Repository • Transition to Actual Patient Population • Growing new Jaw Bone in Mice for Dental Implants – Transition to Human Tissue

  7. Where/How is BMI Utilized? Clinical Research (Trials) • Wide Range of Implications from Medical Treatment to Medication Regime • Multi-Phased Process for Clinical Trials: • Phase I: First Stage – 20-80 Healthy Patients • Phase II: Second Stage – 20-300 Patients • IIA – Dosing – How Much of Drug Should be Used • IIB – Efficacy – How Well Does Drug Work • Randomized Clinical Trials (Not all Get Drug) • Phase III: Multi-Center Trials – 300-3000 • Longer Term, Data Collected, Multiple Locations • Preparation of Data for Regulatory Approval (FDA) • Phase IV: Ongoing Monitoring of Drug After Approval

  8. Where/How is BMI Utilized? Clinical Research (Trials) • Differing Perspectives for Carrying out Research: • Patients: Drug, Treatment Regime, or Device • Increased Dose of Existing Drug (Safety/Effective) • Applying Drug to New Disease • Compare Two or more Treatments • Epidemiological • Study Existing Data for Trend • Against Existing Data Repositories • Patients with CHF and Diabetes Taking Statins • Tracking Communicable Disease/Outbreaks • Phases I, II, III, and IV Apply • Bad Results in IV – Pull Drug (Vioxx)

  9. Where/How is BMI Utilized? T2 Research (Clinical Research Practice/Community) • Practice-Oriented Translation Research • Results: Clinical Trails  Clinical Practice • Strategies for Establishing/Implementing New Technologies • Improvements in Practice • New Evidence-Based Guidelines • New Care Models • Phase III Success Translated to Health Providers • Examples • Statin Drugs (Lipitor) and Exercise • New Treatment Regime for Chronic Disease

  10. Where/How is BMI Utilized? Clinical Practice • Dealing with Patients – Direct Medical Care • Hospital or Clinic • Physician’s Office • Testing Facility • Insurance/Reimbursement • Tracking All Data Associated with Patients • Medical Record • Medical Tests (Lab, Diagnostic, Scans, etc.) • Prescriptions • Stringent Data Protection (HIPAA) • Distributed Repositories, Inability to Access Data in Emergent Situations, Competition, etc.

  11. What is Medical Informatics? • Clinical Informatics, Pharmacy Informatics • Public Health Informatics • Consumer Health Informatics • Nursing Informatics • Systems and People Issues • Intended to Improve Clinical outcomes, Satisfaction and Efficiency • Workflow Changes, Business Implications, Implementation, etc… • Patient Centered – Personal Health Record and Medical Home • Care Centered – Pay for Performance, Improving Treatment Compliance

  12. What is Bionformatics? • Focused on Research Tools for T1: • Genomic and Proteomic Tools, Evaluation Methods, Computing And Database Needs • Information Retrieval and Manipulation of Large Distributed (caBIG) Data Sets (cabig.cancer.gov/index.asp) • Often Requires Grid Computing • Includes Cancer and Immunology Research • Increasing Need to Tie These Separate Types of Systems Together = Personalized Medicine • Biology and the Bedside (www.i2b2.org)

  13. Where is Data/How is it Used? • Medical And Administrative Data Found in Clinical Information Systems (CIS) Such As: • Hospital Info. Systems Electronic Medical Records • Personal Health Records such as Google Health and Microsoft Healthvault • Pharmacy, Nursing, Picture Archiving Systems • Complex Data Storage and Retrieval – Many Different Systems • T1 Research Increasingly Reliant on CIS • T2 Research is Reliant on: • End Systems for Embedding EBM (Evidence-Based Medicine) Guidelines • Measuring Outcomes, Looking at Policy

  14. What are Major Informatics Challenges? • Shortage of Trained People Nationally • Slows adoption of Health Information Technology • Results in Poor Planning and Coordination, Duplication of Efforts and Incomplete Evaluation • What are Critical Needs? • Dually Trained Clinicians or Researchers in Leadership of some Initiatives • Connect all folks with Informatics Roles across Institutions to Improve Efficiency • Multi-Disciplinary: CSE, Statistics, Biology, Medicine, Nursing, Pharmacy, etc. • Emerging Standards for Information Modeling and Exchange (www.hl7.org) based on XML

  15. What is UConn Doing in this Area? NIH’s CTSA Program: Transform the Way Clinical and Translational Science Research is Conducted From Bench to Clinical Research to Translational Research to the Bedside and Back Again 45+ Academic Medical Centers Awarded to Datesee: http://www.ctsaweb.org/ Under President Mike Hogan’s Leadership UConn Submitted a CTSA Proposal in Oct 2008 Formed CICaTS: Connecticut Institute for Clinical and Translational Science (Sept. 29th 09) University Initiative with Partners John Dempsey, St. Francis, Hartford Hospital, CCMC, Hospital for Central CT, Institute for Living, etc. http://cicats.uconn.edu/

  16. CICATS Official Launching: Tuesday September 29, 10:30am-1:30pm UConn Global Business Learning Center, Hartford Speakers Include: Pres. M. Hogan, Provost P. Nichols, and Dean Cato Laurencin (Med School) Mission: to educate and nurture new scientists toincreaseclinical and translational research being conducted at UCHC, regional hospitals, UConn Storrs, and healthcare organizations throughout greater Hartford  to work collaboratively with regional stakeholders to combat the leading causes of morbidity, mortality, disability, and health disparities CICATS will have Biomedical Informatics Center

  17. Biomedical Informatics in CICATS

  18. Summary of Web Sites of Note: • AMIA (www.amia.org) • IHE (http://www.ihe.net/) • Smartplatform (http://www.smartplatforms.org/) • Mysis MOSS (http://www.misys.com/OpenSource) • NSF Clinical and Translational Science Program • http://www.ctsaweb.org/ • Emerging Patient Data Standard • http://www.hl7.org/ • Informatics for Integrating Biology & the Bedside. • https://www.i2b2.org/ • Cancer Biomedical Informatics Grid • http://cabig.cancer.gov/index.asp

  19. Semester Topics (weeks) • Four Core Topics: • Semester and Course Overview (0.5) • Informatics/Information Engineering (1.5) • Software Architectures (2) • Security and Dynamic Coalition Problem (2) • Service Based Computing (2) • CORBA, JINI, .NET, Interoperability, Web • Security • Discussion of Semester Project (0.5) • Presentations by Outside Speakers (2.5) • Student Presentations on Biomedical Informatics Materials (3)

  20. Planned Speakers • Dr. L. Fagan, Co-Director, Stanford Biomedical Informatics Training Program, March 31 • Dr. M. Smith, Pharmacy Practice, UConn, April 5 • Dr. T. Shortliffe, President, AMIA, April 28 • Others to be Scheduled: • Dr. Thomas Agresta • Dr. Michael Blechner • Dr. Xiaoyan Wang

  21. Class Materials, Textbook, Projects, etc. • Course Web Site: http://www.engr.uconn.edu/~steve/Cse300/cse300.html • Reading List • Constant Updates and Changes • Textbook • Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics), Edward H. Shortliffe (Editor), James J. Cimino (Editor), ISBN-10: 0387289860 • Project 1 – Due in 2 weeks • Project 2 – Out in 2 weeks • Team Project – Out in 2 weeks as well • Questions? Comments? Suggestions?

  22. Course Projects and Exam (???) … • Individual/Team Course Project(s) Throughout the Semester • Individual Projects have two Goals • Increase Student Knowledge on BMI • Assist in Creating Courseware • Project will be the Entire Class • Explore and Learn about BMI Technologies • Span Subset of: T1 Research - Clinical Research - T2 Research - Clinical Practice • Explore Open Source and Other Solutions • Develop Extensible Plug and Play Framework • Exam – At MOST Final Exam (Still open to debate!)

  23. Individual Semester Projects • Readings, Readings, and More Readings • Project 1: Annotated Bibliography • Accumulate Web/Hard Links on T1 Research - Clinical Research - T2 Research - Clinical Practice • Read 7 Papers on Clinical & Translational Science • Project 2: Courseware Materials • Choose two Different Areas for Indepth Examination • Topics include (but not Limited to): • HIE I2b2 • Standards (HL7, Common Data Architecture CDA) • caBIG • BIRN (Biomedical Informatics Research Network) • Another NIH Computing Initiative

  24. Semester Project • Still Evolving – Possible Projects Include: • Usage of SmartPlatform • Utilization of Personal Health Records (PHR) Such as Google Health and/or MS Healthvault in New or Extended Context • Interoperability with EMR • Google Health Hibernate API Available • XML (HL7/CDA) to i2b2 DB Translation • Supervised by M. Blechner (UCHC BMI Faculty) • Extending Cell Phone Applications (iphone, blackberry, and android) for • Maintaining Prescriptions • Observations of Daily Living • Prior Work by Undergraduate Teams (with Source)

  25. Semester Project Objectives • Objective – Wide Scale Open Source Framework • Envision Plug and Play Architecture • High Reliance on Open Source Solutions for PHR and EMR • Support Interoperability to Components via XML and Standards • Develop Complete, Integrated, and Extensible Framework

  26. SmartPlatform • Substitutable Medical Apps, reusable technology • (http://www.smartplatforms.org/) • NSF/NIH Funded SHARP Proposal at Harvard • Intended to:“A platform with substitutable apps constructed around core services is a promising approach to driving down healthcare costs, supporting standards evolution, accommodating differences in care workflow, fostering competition in the market, and accelerating innovation” • Likely Led by Timo Ziminski

  27. Personal Health Records • Google Health • Detailed Hibernate API to Allow Programmatic Transfer of Information to/From Google Health • Utilized in Web-Based Application • Utilized by Cell Phone Projects (see later slides) • Existing Platform Available for Future Design, Development, and Usage • Explore EMR/PHR Interoperability

  28. TMR Architecture

  29. XML (HL7/CDA) to i2b2 DB Translation • Work with Dr. Michael Blechner (UCHC BMI Faculty Member) • Explore a Prototype that can take: • HL7/CDA Data (Simulated from an EMR) • Store in a i2b2 Compatible Database • Utilization of Standards, New Technologies, etc.

  30. Cell Phone Applications • RWJ Project Health Design • Observations of Daily Living and PHRs • Passive – Once Initiated, Collects Data • Accelerometer • Pedometer • Pill Bottle that Sends a Time Stamp Message (over Bluetooth?) to SmartPhone • Active – Patient Initiated • Providing Information via Smartphone on: • Diabetes (Glucose, Weight, Insulin) • Asthma (Peak Flow, use of Inhaler) • Heart Disease (Pulse, BP, Diet) • Pain, Functional status, Fatigue, etc. • http://www.engr.uconn.edu/~steve/Cse4904/cse4904.html

  31. Focus of Grant • Management of Two Diseases in Women of Color • Obesity and Osteoarthritis • Team • TRIPP (Crowell, Fifield) and AHFP (Agresta) • SisterTalk (Headley) and CHCAT (Granger) • UConn Storrs (Demurjian) and Netsoft (Collins)

  32. CSE4904 – Spring 2010 • Smartphone Projects on ODLs and Other Medical Data Tracking and Alerts • Three Platforms: • Google’s Android (Java) • Blackberry (Java) • iPhone (Objective C) • Three Teams of Three Students Each

  33. Blackberry Team • Ability to Track Information on ODLs and Prescriptions • Login Screen • Connection to Google Health • Health Screen to Track ODLs • Charting of ODLs over Time • Loading Scripts from Google Health • Prescription Alarms • Adam Siena, Kristopher Collins, William Fidrych

  34. Screen Shots

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  39. Android Team • Similar Capabilities to Blackberry Project • Wellness Diary and Medication Alarm • Integration with Google Health • Much Improved ODL Screens • Male and Female Faces • Change “Face” Based on Value • Tracking Prescriptions and Alarms • Reports via. Google Charts • Ishmael Smyrnow, Kevin Morillo, James Redway

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  44. iPhone Team • Similar Capabilities to Blackberry Project • Tracking of Conditions, Medications, and Allergies • ODLs for: • Blood-Glucose, Peak-Flow, and Hypertension • Generation of Reports • Synchronization with Google Health • Brendan Heckman, Ryan McGivern, Matthew Fusaro

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  49. Questions?

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