1 CSE 4939 What is BMI? Prof. Steven A. Demurjian, Sr. Computer Science & Engineering Department The University of Connecticut 191 Auditorium Road, Box U-155 Storrs, CT (860)

2 CSE 4939 Expand Knowledge on Emerging Disciplines  Biomedical Informatics/Health Information Technology Rapidly Emerging Discipline  Cutting Edge, Incredible Career and Research Opportunities  Improve Practice of Medicine Through Informatics  Patient Managed  Patient Care  Hospital Based  Research (Genomics/Trials)  What is Biomedical Informatics?  Where is the Future?

3 CSE 4939 What is Informatics?  Informatics is:  Management/Processing of Data  From Multiple Sources/Contexts  Classification (Ontologies), Collection, Storage, Analysis, Dissemination  Informatics is Multi-Disciplinary  Computing (Model, Store, Mine, Process Information)  Social Science (HCI)  Statistics (Analysis)  Informatics Can Apply to Multiple Domains:  Pharmacology, Nursing, Medicine, Biology, etc.  Business, Fine Arts, Humanities People Information Technology Informatics Adapted from Shortcliff textbook

4 CSE 4939 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.)  Clinical Informatics, Pharmacy Informatics, Consumer Health Informatics, Nursing Informatics

5 CSE 4939 BMI & Clinical Practice  Tracking all Information for Patient and his/her Care  Medical Record, Medical Tests (Lab, Diagnostic, Scans, etc.), Prescriptions  Dealing with Patients – Direct Medical Care  Hospital or Clinic, Physician’s Office  Testing Facility, Insurance/Reimbursement  Informatics Support via:  Electronic Medical Record  Linking/Accessing Data Repositories  Collaborative and Secure (HIPPA) Web Portals

6 CSE 4939 Learn about New/Emerging Technology  Explore Smartphone Technologies and Applications  Four Smartphone Platforms  Android  Blackberry  iPhone  Microsoft  All with Differing APIs  Java  Objective C .NET  How do we Develop Applications?  How can we Link to Web and Existing BMI Apps?

7 CSE 4939 Learn about New/Emerging Technology  Personal Health Records (PHR) are Patient Controlled Repositories  Google Health (  Accessible via Java API  XML-Based Interface  Microsoft HealthVault (  Accessible via.Net Infrastructure  Electronic Medical Records (EMRs) are Health Provided Controlled Repositories  General Electric Centricity EMR  Version 9.2 – Secure Web Services

8 CSE 4939 Project Focus this Semester  Smartphone Applications that Interact with Google Health (or MS Health Vault) and GE Centricity  Focus on Observations for Daily Living (ODLs)  What are ODLs?  Patient Provided Information  Related to their Chronic Diseases or Health Goals  Augment Typical Information Provided at MD Visit  Continuous Input  Clinical Decision Support to Spot Problem Trends  Intervene Before Event Occurs  Monitor Progress Towards Goal (e.g., weigh loss)

9 CSE 4939 Two Types of ODLs  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.  From Basic to Sophisticated!  All ODLs will have Help (Usability) and Education (Disease) Capability Built in.

10 CSE 4939 Overall Architecture

11 CSE 4939 Possible ODLs  Multi-Media Support Repository: It has been found in a number of settings, that people with chronic diseases may be able to cope with their pain, fatigue, etc., through the use of audio clips, video clips, or pictures that mean something too them. For example, for one person it may be pictures and clips of family and loved ones, for another person it may be popular music, for yet another inspirational speeches, and so on. The intent is to develop a Smartphone application that is capable of tracking a repository of audio, video, and pictures, categorized by Topic, Title, and/or Keywords. The system will track a complete historical record for each participant, noting the selections that are being utilized along with their date-time stamp and frequency. There will be the ability to have a favorites list of most frequently used selections, as well as for each participant to upload their own audio/videos for her own use. The intent is to also have a version of this application that could cache selections with the memory of the Smartphone to reduce download times, particularly for those selections chosen most frequently.

12 CSE 4939 Possible ODLs  Pedometer or Accelerometer: For either of these applications, you will need to have an actual Smartphone that has motion sensors. The idea would be that these applications would be initiated by a patient to collect information associated with walking (pedometer) or movement (accelerometer) for a fixed period of time.

13 CSE 4939 Possible ODLs  Discrete Measurement of Symptom/Condition: Historically, pain scales have been used extensively in medical settings (just to a Google Search on “pain scale” images). This type of scale can be generalized to collect information related to pain, fatigue, mobility, adherence to medication, and so on. Note that some of these ODLs may be regularly schedule (e.g., the smartphone beeps a reminder), triggered as the result of a contact to the patient (e.g., an automated call or to the smartphone), or initiated by the user. The numerical values are tracked for each individual to capture all of the values entered. This would be a simplistic ODL based on a scale (1 to 10, Good to Bad, etc.) rather than any actual collection of medical/personal data.

14 CSE 4939 Possible ODLs  Discrete Measurement of Symptom/Condition: Historically, pain scales have been used extensively in medical settings (just to a Google Search on “pain scale” images). This type of scale can be generalized to collect information related to pain, fatigue, mobility, adherence to medication, and so on. Note that some of these ODLs may be regularly schedule (e.g., the smartphone beeps a reminder), triggered as the result of a contact to the patient (e.g., an automated call or to the smartphone), or initiated by the user. The numerical values are tracked for each individual to capture all of the values entered. This would be a simplistic ODL based on a scale (1 to 10, Good to Bad, etc.) rather than any actual collection of medical/personal data.

15 CSE 4939 Possible ODLs  Synching Information with PHR/EMR: For this application, you need to consider the information that is stored in a PHR and/or EMR, and develop Smartphone applications that provide a means for patients to enter the information which can then be synchronized with the PHR/EMR. For example, Google Health lets a user maintain his/her prescriptions, but it is not set up to handle nutritional supplements and other home remedies. A application could support the data entry of this information, which would then be synchronized into Google Health, and if the user is also a patient with data in the EMR Centricity, a second step would synchronize to this repository using its secure web services. A different application could also be considered to handle side effects and reactions to medications, food, allergens.

16 CSE 4939 Possible ODLs  Scanning/Recognition: For this application, it may be possible to leverage the digital camera in a cell phone to take a “picture” of a medication and/or nutritional supplement label that can be then uploaded to the web into the PHR or EMR. The idea would be for the patient to be able to create a pictorial representation of medications/supplements, that would also be supplemented with their complete dosing information (size, frequency, etc.). This would involve being able to capture perhaps multiple images from the same medication/supplement and meld them together.

17 CSE 4939 Possible ODLs  Futuristic: Are you really Ambitious?  Link Commercial Glucose Meter to SmartPhone  Digital Camera on Smartphone to Scan Bar Codes on Supplements and/or Medications  May Involve OCR  Hooking up Sensors through Smartphones  Pulse, BP, etc.  Treadmill or Exercise Equipment  GPS and Smartphones? For Movement?  Many of these will need to store data in PHR/EMR