Download bmiintro - University of Connecticut

What is BMI?
CSE
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Prof. Steven A. Demurjian, Sr.
Computer Science & Engineering Department
The University of Connecticut
191 Auditorium Road, Box U-155
Storrs, CT 06269-2155
[email protected]
http://www.engr.uconn.edu/~steve
(860) 486 - 4818
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Expand Knowledge on Emerging Disciplines
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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?
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What is Informatics?
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Informatics is:
 Management/Processing of Data
 From Multiple Sources/Contexts
Informatics
 Classification (Ontologies),
Collection, Storage, Analysis,
People
Dissemination
Informatics is Multi-Disciplinary
 Computing (Model, Store,
Mine, Process Information)
Information
Technology
 Social Science (HCI)
 Statistics (Analysis)
Informatics Can Apply to Multiple
Domains:
Adapted from Shortcliff textbook
 Pharmacology, Nursing,
Medicine, Biology, etc.
 Business, Fine Arts, Humanities
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What is Biomedical Informatics (BMI)?
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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
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Bioinformatics for Research/Biology to Bedside
 From Genomics to Proteomics
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Public Health Informatics (State and Federal)
 Tracking Trends in Public Sector
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Clinical Research Informatics
 Deidentified Repositories and Databases
 Facilitate Epidemiological Research and Ongong
Clinical Studies (Drug Trails, Data Analysis, etc.)
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Clinical Informatics, Pharmacy Informatics,
Consumer Health Informatics, Nursing Informatics
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BMI & Clinical Practice
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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
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Learn about New/Emerging Technology
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Explore Smartphone Technologies and Applications
Four Smartphone Platforms
 Android
 Blackberry
 iPhone
 Microsoft
All with Differing APIs
 Java
 Java
 Objective C
 .NET
How do we Develop Applications?
How can we Link to Web and Existing BMI Apps?
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Learn about New/Emerging Technology
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Personal Health Records (PHR) are Patient Controlled
Repositories
 Google Health (www.google.com/health)
 Accessible via Java API
 XML-Based Interface
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Microsoft HealthVault (www.healthvault.com/)
 Accessible via .Net Infrastructure
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Electronic Medical Records (EMRs) are Health
Provided Controlled Repositories
 General Electric Centricity EMR
 Version 9.2 – Secure Web Services
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Project Focus this Semester
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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)
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Two Types of ODLs
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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:
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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.
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Overall Architecture
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Providers
Centricity EMR
Web/Application
Server
SQL Server
Database
Patients
Client Side Technologies
https, html, Ajax, XML
Server Side Technologies
Java, JSP, Hibernate,
Relational Database, XML
Database
Repository
Google
Health
Patient Demographics
and ODLs
Figure 1: Architecture Diagram of the Proposed System.
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Possible ODLs
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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.
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Possible ODLs
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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.
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Possible ODLs
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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
email 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.
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Possible ODLs
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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
email 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.
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Possible ODLs
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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.
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Possible ODLs
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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.
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Possible ODLs
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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
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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
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