Mobile Health Data
In
healthcare, the recording of the vital signs of elderly people is crucial to
catch early warning signs and take preventative measures, more specifically
monitoring Electrocardiogram (ECG), body temperature, and blood pressure data
(Schilling and Klingeberg, 2012). Paper thin sensors are becoming so ubiquitous
that they may soon be embedded in clothing (Bilton, 2011). If physicians could
access this data and were provided easy statistical analysis through a software
interface, this could provide a positive social change through early detection.
Much research is additionally required to analyze the effectiveness of mobile
health interventions, or the positive social change enabled through the
collection and analysis of mobile health data (Free et al., 2013).
Digitizing Existing Data
Before
this advanced collection and analysis of mobile health data occurs, existing
healthcare operations must provide a means for the collection and analysis of
data in digital format. Given the ambitious goal of the Office of the National
Coordinator for Health Information Technology (ONCHIT) of having an Electronic
Health Record (EHR) for every person in the United States by the year 2014 as a
society we are hopefully now on track to build this infrastructure (Hebda and
Czar, 2013). There are many positive social changes in making current health
processes digital, including improved healthcare quality, catching fraud, and
cost savings from eliminating redundancy and shortening rapid improvement cycles
(Friedman, 2013).
Simple User Interfaces
The
Graphical User Interface (GUI) is one of the most crucial factors in developing
a software driven informatics product. If individuals can not understand how to
utilize the tool, then implementation will be a failure. Trending in GUIs is
leading towards more human-like interfaces, i.e. touch screen implementations
such as pinching and flipping as natural human actions. As technology progresses
to keep pace with the rapid shrinking of the number of transistors fitting on a
computer chip, and hence the increase in processing power per size unit, new
GUIs will become feasible such as speech recognition, heads-up display, and 3-D
imagery or holographic displays to include a few.
Health Informatics for Positive Health Outcomes
There is a great need for health informaticians which possess the unique
combination of training on the human body and its physical well being in context
of its environment joined with the foundations of technology. These areas of
technological social change can not only be incurred by the healthcare industry,
but will be important in the public health field as well in regards to
epidemiology in addition to others (Li Y-p et al., 2013).
References:
Walden University, LLC, (2012). 2012 social change impact report. Retrieved from
website: www.WaldenU.edu/impactreport
Li Y-p, Fang L-q, Gao S-q, Wang Z, Gao H-w, et al. (2013)
Decision support system for the response to infectious disease emergencies based
on WebGIS and mobile services in China. PLoS Med,8 (1).
doi:10.1371/journal.pone.0054842
Hebda, T., & Czar, P. (2013). Handbook of informatics for
nurses & healthcare professionals. (5 ed., p. 381). New Jersey: Pearson
Education, Inc.
Schilling, M., & Klingeberg, T. (2012). Mobile wearable
devices for long term monitoring of vital signs. Computer methods and programs
in biomedicine, 106(2), 89-96.
Free, C., Phillips, G., Watson, L., Galli, L., Felix, L.,
Edwards, P., Patel, V., & Haines, A. (2013). The effectiveness of mobile-health
technologies to improve health care service delivery processes: A systematic
review and meta-analysis. PLoS Med,10(1), doi: 10.1371/journal.pmed.1001363
Friedman, E. (2013). The paper chase: Why are some providers
reluctant to embrace health information technology? [Online forum comment].
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Bilton, N. (2011, May 19). [Web log message]. Retrieved from
//bits.blogs.nytimes.com/2011/05/19/the-sensors-are-coming/