IEEE - Personalized Electronic Health Record System for Monitoring Patients With Chronic Disease
Transcript of IEEE - Personalized Electronic Health Record System for Monitoring Patients With Chronic Disease
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Proceedings of the 2013 IEEE Systems and InformationEngineering Design Symposium, University of Virginia,Charlottesville, VA, USA, April 26, 2013
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978-1-4673-5663-3/13/$31.00 2013 IEEE 127
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This research involves the development of a personalized
electronic health record system for monitoring patients with
chronic conditions, that (a) allow for relevant data to be
entered by the patient, (b) make relevant data available to
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will generate reports and graphs for the data and (d) will
provide secure storage of the data.
The app is a HIPAA-compliant medical research tool able to
collect data from patients, store it conveniently for review,
and send it to healthcare providers; it is not limited to
chronic disease. Therefore, the app created has a potential as
a much larger commercial system that would help
companies, hospitals and clinics provide a more effective
care for their patients by controlling costs while improving
the quality of life and patient satisfaction.
A.Literature ReviewMany studies performed within US health-care system
have repeatedly shown that web-based technology can be
used to assist patients in taking an active role in monitoring
their health and self-manage their condition [3]. These web-based apps have the potential of increasing patient self-
management knowledge, skills in disease control and their
confidence in managing their health; especially in the case of
patients with chronic disease [3]. Furthermore, these apps
actively monitor the progress of diseases and provide
feedback to the care giving team that effectively reduces
medical errors and costs [4].
Prior to designing a new product, research needs to be
conducted to analyze the availability of comparative
products. Many versatile, customized applications (apps) are
currently used for monitoring patient care. Most apps are
first used on a small scale for testing the design and usability,
and then provide background for the design of a new,
improved app.
Researchers at Stanford used Tele-health technology to
improve coordination of care [5]. Researchers examined two
clinics in the Northeast US that had implemented the tele-
health Buddy program using an experimental and control
group, and studied the effect of the program on quality and
spending for patients. When the tele-health Care Buddy
Program was compared to a control group, the tele-health
program had reduced spending of 7.7% to 13.3% or $312 -
$540 for each person per quarter. Mortality differences were
also noted in treatment and control groups. Utilizing both
tele-health technology and managed care has potential forreducing health care cost and improving care for persons
who suffer from chronic diseases. This study suggests that
carefully designed tele-health programs that are properly
implemented can reduce the cost of health care and
significantly reduce mortality rate.
New Technology has also been used effectively in
diabetes management [6]. Patient monitoring, particularly
among patients on insulin is important in limiting disease
progression, but can be labor intensive, costly and
cumbersome therefore there is a need for improved
monitoring systems. In a recently conducted study published
inJournal of Diabetes Science and Technology, Dr. Rao and
his colleagues compared the effects of three iPhone diabetes
data management applications; the Diamedic diabetes
logbook, the blood sugar diabetes control and the wave-
sense diabetes manager [7]. Surveys sampled 23 individuals,
who entered data manually based on self-reports on variables
like ease of life, time to enter, request for help, data sharing,
and application trustworthiness. Patients found the WDM
application easiest to use, fastest and most trustworthy. The
study provides important guidelines for monitoring
symptoms of patients; however, the manual data entry was
cited as a weakness. Another study conducted by Roy et al.,
[8] researchers in the area of ParkinsoQV GLVHDVH XVHG D
wearable sensor-based system to assist with assessment of
motion disorders. This system was used to continuously
monitor PD disorders to distinguish between normal tremors
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from their study indicated that sensor technology and
software processes could be used to improve the function ofwearable sensor-based application used for monitoring PD
disorders during unrestricted activities.
In another study, researchers from the University of
Denmark in Vienna, Austria, have been testing a new
wireless medical sensor to study fatigue in MS patients [9].
The researchers wanted to prove that they could find more
indicators and warning signs of fatigue using their wireless
sensor than those perceived after the usual measurement tests
for physiological parameters in MS patients. They planned to
recruit three groups (10 fatigued MS patients, 10 non-
fatigued MS patients, 10 age-matched healthy control) of ten
persons each between ages 20-65. Groups were to bemonitored continuously for 24 hours after undergoing
memory and fitness test. A wireless data acquisition system
converted signals and send them to a wireless router, then to
a computer. Devices were used to measure ECG signs
continuously, EMG modules for measuring activity of
muscles, body skin temperatures, eye movement and motions
signals. Data accumulated is to be related to physiological
differences in the groups. However, no final results were
reported as researchers are still conducting trials.
The same researchers from the University of Denmark
also recently tested a wireless body measurement system
designed to study fatigue in MS patients [10]. Their aim was
to set boundaries and to define the functions that are related
to fatigue in patients suffering from MS. Their wireless
system used to measure fatigue is called FAMOS. It is
designed to identify fatigued MS patients from subjects who
are healthy, and to provide feedback continuously on ECG,
body-skin temperatures, EMG and feet motions. The study
presented the design of the hardware and the procedures
utilized. The researchers concluded that the FAMOS could
determine healthy subjects from fatigued MS patients and
provide data continuously on the capabilities and limitation
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