Gino P. Fideles
Module #1
Moving Along the Data Analytics Continuum, Healthcare
Organizations Continue to Make Strides
Levinthal, Rajiv.
Healthcare Informatics,
33(4), 18-21.
Data Analytics: The Future of Healthcare
This article is chosen because it
brings about an interesting point on the use of data and analytics as a tool
for enhancing healthcare. In an era where healthcare data is ever so critical
in transforming the healthcare system into data driven industry, the importance
of data in healthcare can never be overemphasized because healthcare professionals are relying on enormous
amounts of data to perform accurate and efficient clinical care for their
patients.
This article is interesting because
for the past decade or more, healthcare has rapidly evolved itself into a data driven
environment where data becomes the
currency to make the healthcare system work effectively and efficiently. Despite
the advance of data uses in healthcare, the healthcare industry is not tapping
or embracing the full potential of using data and analytics to improve efficiency
and quality of care. The article
describes how data and analytics can change how healthcare systems are
structured and how healthcare processes are conducted. The article is from the Healthcare Informatics.
It is a special report from
healthcare-informatics.com.
The problem identified was 10% of
the 300 surveyed correspondents who work in life sciences companies states
that they have not fully taken
advantage of using data and analytics as a tool to improve efficiency and performance
in healthcare (Leventhal, 2016, p. 19). The use
of predictive analytics in healthcare analytics or data analytics in general can
provide the tools and processes needed to make healthcare delivery more
effective and efficient through using
data analysis to identify patterns that can help predict better patient care
treatment protocols and procedures. Predicative
analysis can use data to create predictive analysis of patient cases and
conduct risk assessment of a patient’s risk to a disease which can then prepare
a patient how effectively manage his or her daily routine to prevent flare ups or
lessen the risk of getting a disease condition.
The implications of data analytics
especially predictive analytics would be a big step towards evolving healthcare
systems. Using analytics as a tool to evaluate healthcare practices and patient
care will enable healthcare system to evolve into a more efficient and
effective form of healthcare delivery to patients through performing data
analysis from data, information and knowledge collected from patients. The
information collected from patients can then serve as a pattern or a knowledge base
which can then serve to help other patients have better treatment options and
care. Data analytics will become important in the future of healthcare delivery
to patients. Data analytics relies on data, information, patterns and trends to
find solutions to patient care problems.
Data analytics or the way data analytics works can be applied to my
practice through allowing trends of data to be used for selecting best possible
way to treat patients.
References
Leventhal, R. (2016).
Moving Along the Data Analytics Continuum, Healthcare Organizations Continue to
Make Strides. Healthcare Informatics, 33(4), 18-21.
.
