1.
The big-data revolution
in healthcare
By Joel Selanikio

2.
Insights

3.
The exponential evolution of data in health care has brought a
lot of challenges in terms of data transfer, storage,
computation and analysis. For healthcare usage and
applications, ample patient information and historical data,
which enclose rich and significant insights that can be exposed
using advanced tools and techniques as well as latest machine
learning algorithms. Though, the size and rapidity of such great
dimensional data requires new big data analytics framework.

4.
Problems
Healthcare Sector is lagging
behind.
Most of the gathering still
takes place manually on
paper.
Sometimes it takes
months to even years in
answering a single
question.

5.
Worst Outcomes

6.
Millions of children die of vaccine-preventable
diseases every year. And the fact is, millions is a
gross estimate, because we don't really know
how many kids die each year of this

7.
The Reason
Data Entry Part
Sometimes it can take six
months to two years to
type that information into a
computer

8.
Only after Collecting
all data once can the
analysis process be
done.
After that one can come up
with a solution.

9.
“Hefty and Error Prone
Process”

10.
He came up with an idea
of palm pilot to collect
data electronically so that
one can skip straight to
the analysis and then to
the use of the data to
actually save lives."
Taking inspiration
from Hotmail, he
created Magpi

11.
Magpi
An online survey creator that allows
users to write their own surveys and
upload data instantly, creating maps
and other analysis tools in real time.

12.
The training video for the
service is just 15 minutes long.
It is cloud-based service that
required no programming
knowledge to use.

13.
CONCLUSION

14.
Critical planning is needed to assemble and integrate the data.
Incorporating data only does not produce value. Progressive
logical models are needed to permit data driven plan. A plan
must recognise where models will create surplus business
value, who will need to use them.

15.
Thanks!