www.panorama.com Panorama Necto uncovers the hidden insights in your data and presents them in beautiful dashboards powered with KPI Alerts, which is managed by a the most secure, centralized & state of the art BI solution.

1. Centralized &
State of The Art BI
Healthcare Industry

2. BI and Data
Analysis in
Healthcare
The use of smart data analytics and
Business Intelligence is becoming the
norm. The healthcare industry is not
behind in this trend. 57% of healthcare
organizations have implemented patient
data analytics to improve patient care
and outcomes. And 46% of organizations
have implemented analytics of their
organizational data to improve their
everyday performance.

3. Actually, medical organizations are key users in business intelligence. They
generate enormous amounts of data. And due to legal regulations, they need state
of the art BI to analyze it while keeping it safe. Just to get an idea of the amount of
data in the healthcare industry and its potential, let’s go over some numbers.
According to the University of Iowa, Carver College of Medicine, medical data is
expected to double every 73 days by 2020. The volume of health data is growing
exponentially; it is expected to be 50 times larger by 2020. This exponential growth
can be due to the fact that more than 16,000 hospitals collect data on patients
worldwide. And 4.9 million patients use remote monitoring devices (including
wearables like Fitbit). Plus, patient monitoring equipment produces an average of
1,000 readings per second.
Now let’s go over some of the benefits of using data analytics. There can be a
20% decrease in patient mortality by analyzing streaming patient data. Of
organizations that analyze their data, 82% reported improved patient care, 63%
reported reduced readmission rates, 62% reported improved overall health
outcomes, 54% reported improved financial reporting capabilities, 50% reported
improved hospital operational performance and 49% reported improved
management decision-making.

4. Healthcare organizations are
implementing data analytics to
improve efficiency and patient care.
Smart data analytics or BI tools can
help organizations analyze the large
volumes of data they generate. This
data has an enormous potential to
reduce operational costs, improve
quality of patient care, identify
patterns and even save lives. Hospitals
can integrate with third-party data
sources to do a benchmark of national
averages. They can compare their
internal metrics and national metrics
to revise their processes and improve
their operations.
Data to reduce costs,
improve efficiency,
and save lives.

5. Medical data can also be used for prevention.
For example, to prevent the spread of
epidemics, population movements can be
tracked with mobile phone location to
predict the spread of viruses like Ebola. This
allows organizations to identify which
regions need urgent allocation of resources
and treatment centers.

6. There are new trends appearing, such as
Personalized Medicine. It means customizing
medicine to a person’s unique genetics. This
is done by analyzing together both a person’s
genetics and information about their
lifestyle. This data can be analyzed together
with thousands of others and be used to
predict illness patterns.

7. There are many things healthcare organizations can do with
their data. The following is a list of 20 things that they can do.
This list is not closed, meaning there are many more uses and
benefits, because the tools can adapt to each organization’s
needs. With a good centralized BI tool, healthcare organizations
can:
1) Connect to multiple data sources and analyze their data in a
secure environment.
2) Find hidden insights to improve overall performance.
3) Identify patterns of cost and profitability.
4) Understand what are the challenges by department and/or
specialty.
5) Provide dashboards with beautiful visualizations to staff.
20 Things Healthcare Can Do With BI

8. 6) Get automatic insights that can be easily turned into action to improve the
quality of patient care.
7) Do accurate allocation of resources.
8) Measure the impact of new programs and initiatives.
9) Monitor KPIs like patient wait times, bed rotation, nurse rotation, patient
volumes by time of the day or day of the week, etc.
10)Compare data to other hospitals per region using geo-analysis.

9. 11)Analyze and compare costs of medical procedures by hospital, by region, etc.
12)Improve doctor and nurse productivity by generating automatic reports and
notifications, allowing doctors to focus on patient care rather than
paperwork.
13)Prioritize care for those patients who need it most.
14)Achieve data-driven operations by providing personalized dashboards and
role-based reports to users, from nurses to executives, giving them the
information they need for making the right decisions, at the right time and
in the right context.
15)Manage cases efficiently by tracking care coordination interventions, care
transition assessments, and readmission risk.
16)Conduct hazard vulnerability analysis.

10. 17)Analyze costs of different medical conditions. It is easy to analyze data of hospitals
by locations and information on average cost to care for a patient. Then using geo-
analysis capabilities, we can identify the locations to prioritize cost reductions.
17)Identify patients with greater readmission rates. By analyzing data such as gender,
age, average cost for care and patient history, we can group the characteristics of
patients most likely to be readmitted.
17)Drill down patient demographic data to discover hidden insights. For example: male
patients between the ages of 25-45 have spikes in cost in a certain period of time in
a certain location. These insights can then be analyzed further to obtain more
insights.
17)Cross analysis of patient readmission and different medical conditions. By analyzing
total patient cost, readmission rates and diagnosis, we can find insights and trends
in the most susceptible patient groups and the most and least costly conditions to
treat over time.
At the top of the list we mentioned that these things can be achieved using a
centralized BI tool. This needs to be explained in more depth, because the right BI
model can ensure a BI project’s success in healthcare.

11. The correct implementation of a BI
project is a big challenge for any company.
Healthcare organizations face an even bigger
challenge when implementing BI because of
the nature of the data they handle. They
generate, collect, and analyze sensitive data,
like patient records, patient financial
information, etc. A lot of this data is regulated
by strict privacy rules. An example of this is
the Health Insurance Portability and
Accountability Act (HIPAA), which calls for
extra security and a special administration of
the data.
Centralized BI in
Healthcare

12. Only certain individuals are allowed to
look at private patient records. Healthcare
organizations have tried different models of
organizing their BI teams. Some have
special BI teams under the supervision of a
Chief Medical Officer, a Chief Financial
Officer and a Chief Operating Officer. This
model ends up creating silos. Each team
works with a different person, each has
their own data and work, edit, comment,
and analyze only on their desktop. The data
is siloed in archives controlled by different
administrative departments, doctors,
clinics, and hospitals. At the end of the day,
for the fear of sharing data that is restricted,
they are also not sharing data that could
benefit the whole organization.

13. The insights they find stay only in one
team. Then it is impossible to try to
merge the data. And in these failed
attempts to merge data, they realize
that there are many versions of the
same files… many versions of the
“truth”. It is a data chaos. And we know
that no business can allow data chaos,
but in a hospital this might mean the
endangering of lives. What if 10 people
save the same patient information
differently? Which one is the real one?
Federated =
Data Chaos

14. It seems like having one version of the
truth and data accuracy plus data privacy is
an impossible task. But it’s not. Information
needs to be updated for everyone in one
same web solution, with IT overseeing who
has permissions to access it and who doesn’t.
The best solution is for BI users to be able to
analyze the data in a centralized
environment.
Meaning they can share insights and
resources between departments, but IT will
govern over the data (making sure to protect
it and stand by HIPAA and other
regulations). The different users can benefit
from the data, but IT will decide who gets to
see what and what is public and what is
confidential. Using a model like this ensures
data privacy and one version of the truth. IT
will give the users the support and resources
they need.
Centralized = One
Version of The Truth

15. Using centralized BI allows organizations to
achieve consistency in data. Everyone in the
organization will be looking at the same
numbers, results, codes, practices, etc.
There will be consistency of data in
physician masters, patient indexes and
records, diagnosis codes, procedure codes,
etc.

16. A good BI solution must provide an easy deployment, beautiful dashboards,
top of the line analytics, automatic insights and KPI alerts; all in a centrally
managed system. Users need to connect multiple data sources, consolidate and
mashup all the data. They need to scale and deploy in a secure manner, in a
centrally administered environment that does not require scripting. Users
need to be able to automatically receive KPI alerts and notifications all the time
to be aware of what is happening in the business.
Necto offers all that, enhanced in a platform that allows you to collaborate,
share, and discuss your findings. It uncovers the hidden insights in your data
and presents them in beautiful dashboards with infographics that users can
understand better. It is an on premise solution with a web deployment, that is
centrally managed and secured.
Why Necto?