Internal Reporting with Tableau

ORBIS Telemedicine – Internal Reporting with Tableau Software 1
ORBIS Telemedicine
Internal Reporting with Tableau Software

Introduction
ORBIS has diligently collected data on the usage of its telemedicine services over the last
decade. As the number of programs and services offered by ORBIS has steadily expanded, the
amount of data collected and stored has also risen. Latent within this data is a wealth of
information about the usage of telemedicine services in various regions of the world and how it
complements other ORBIS programs. This data can be reported internally to advise localized
program development which is evidence based and guide evaluation on a local as well as global
level.
Current Data Storage Landscape
To uncover the intelligence locked within ORBIS’ collected data it is essential to
understand the current spread of data storage. Telemedicine data and relevant ORBIS programs
data is currently siloed in four databases,
1. E-Consultation database: This database is accessed through admin log-in on
E-Consultation website. It holds all the records of e-consultation cases (>9000), partners
involved, partner organizations and pre-screening cases (>2500). These fields can be
sorted by dates, country and also by clinical case category.
2. E-Learning database: This database is accessed through Clarity 5 content management
system. It holds all the records of e-learning courses completed and learner names. It
does not have a consistent and automated way of sorting data by dates or country, thus
requiring considerable hand correlation to extract useful information from data.
3. Google Analytics: This data is accessed through admin log-in on google.com/analytics/.
It provides detailed usage statistics of the www.cybersight.org domain. It presents
information such as, number of visits to website, most popular content, hardware/mobile
devices used to access website and user’s general flow through the website content. This
data can be sorted by dates and geographical area (continent/country/city).
4. ORBIS Intranet: The ORBIS intranet compiles data of hospital based programs (HBP),
flying eye hospital (FEH) visits and volunteer faculty (VF) travel. This data is important
in understanding the role played by telemedicine services in the purview of all ORBIS
programs. This data is static (i.e. on webpages) and hence cannot be automatically
sorted into groups or easily be exported to a database.
E-Learning E-Consultation
Intranet
Documentation
Google Analytics
Hand correlation
required
Figure 1: Current telemedicine and related data storage landscape. No automated communication between databases.
With ORBIS’ growth in the last decade, individual users are now utilizing several
services such as HBP, e-learning and e-consultation to enhance their clinical abilities. This
underlines the need to have a comprehensive database that can track users across these various

services in a consistent manner to provide actionable business intelligence. While the current
siloed model of databases has worked in tracking and adapting individual ORBIS services and
programs, it fails to extract evidence based, actionable intelligence from the data.
Internal Reporting with Tableau Software
Several internal stakeholders stand to benefit if data that has been collected is presented
in a manner that is relevant, easy to understand and easy to manipulate. Internal reports would be
most useful if they can be customized to provide each stakeholder group with information that is
relevant to them. The following are some examples of using Tableau software to combine
information from these databases to create custom reports/dashboards for internal stakeholders.
Click on the images in each section to open the Tableau dashboards in your internet browser.
I. Global visits to Cyber-Sight
The dashboard in Figure 2 presents a snapshot of the number of visits to the Cyber-Sight
website across the globe. It presents this information on a map and also in a bar chart for easy
comparison between geographic regions. It also provides information regarding the average time
users in each country spend on Cyber-Sight. The dashboard allows users to filter and sort the
display by countries and number of website page views.
Figure 2: Global page views on Cyber-Sight
This dashboard uses two sets of data from Google Analytics - first the number of views
by country, and second the time users spend on Cyber-Sight pages (for a given time period). This
information was downloaded in two Excel spreadsheets which were then connected to (or
imported to) Tableau to create the interactive dashboard.
Such a display could be used to visually present an overview of Cyber-Sight usage to the
Board and Senior Management Teams to help them quickly understand trends and identify
anomalies.

II. Regional overview of Cyber-Sight usage
The dashboard in Figure 3 presents information of the usage of Cyber-Sight services in a
map. Viewers of this dashboard can be notified of the number of e-consultation cases submitted,
number of e-learning courses completed and the average time required for completion of
e-learning courses.
Figure 3: Cyber-Sight usage in Africa
This dashboard was built by combining data from two databases, the E-Consultation
database and the E-Learning database. Excel spreadsheets containing the E-Consultation data for
each African country was downloaded and combined into one Excel spreadsheet. Several Excel
spreadsheets were generated by E-Learning database (Clarity 5 content management system)
containing information regarding learners, courses taken and start/finish dates. These were
combined into one Excel spreadsheet through hand correlation. These two Excel spreadsheets
were connected to Tableau and the above dashboard was created. Tableau was used to
automatically count the number of users from each country and to compute the average course
completion times for each country.
E-Learning E-Consultation
Hand correlation
step
Figure 4: Using data from different databases to create dashboard with Tableau

Such a dashboard can be used to quickly present information about Cyber-Sight usage to
Regional Directors. More features such as filters and color shading can be added to this display.
The information presented here could be used to advise further examination of certain regions
through dashboards described in the following sections.
III. Regional E-Consultation Summary
The dashboard in Figure 5 presents information regarding a region’s usage of the
E-Consultation service in varying levels of details. At its most compact form, this dashboard
presents a simple table with country name and the corresponding number of e-consultation cases
for each country in the region. This display can be quickly expanded to show e-consultation
cases from different hospitals within each country and even by various doctors in these hospitals.
This dashboard also makes it possible to view the case categories submitted by each hospital or
doctor (e.g. Strabismus, Cataract etc.). It allows users to filter the data by country name.
Figure 5: E-Consultation Regional Dashboard
This dashboard was built by using data from the E-Consultation database. E-Consultation
details for each country in the region were combined into one Excel spreadsheet and connected
to Tableau. Tableau is able to compute and update the ‘# of E-Consultation cases’ field for each
layer of detail (e.g. by country vs. by hospital in country).

Such a display can be used to quickly present information about E-Consultation usage to
Regional Program Managers. This information could be used identify and tailor program
development tasks towards particular countries, hospitals or doctors.
IV. Regional E-Learning Summary
The dashboard in Figure 6 presents information regarding a region’s usage of E-Learning
service in varying levels of details. At its most compact form, this dashboard presents a simple
table with country name, corresponding number of e-learning courses completed and the average
course completion time for each country in the region. This display can be quickly expanded to
show e-learning course completion details from different doctors within each country. It also
makes it possible to view the course categories engaged by each doctor. The dashboard allows
users to filter the data by country name.
Figure 6: E-Learning Regional Dashboard
This information can also be presented on a time scale as shown in Figure 7. This
provides more insight to the viewer regarding the trends in e-learners in each country over time.

Figure 7: E-Learning Dashboard over Time axis
This dashboard was built by using data from the E-Learning database. Several reports
created by the Clarity content management system were combined into one Excel spreadsheet
which was then connected to Tableau. Hand correlation was required in this process.
Such a dashboard can be used to quickly present information about E-Learning usage to
Regional Program Managers. This information could be used identify and tailor program
development tasks towards particular countries, hospitals or doctors.

V. Dashboards for Cyber-Sight development
The dashboards shown in Figure 8 and Figure 9 present information about which Cyber-
Sight webpages and section are most viewed globally and by country. The dashboard in Figure 8
provides a means to track the general flow of users through the Cyber-Sight website by
highlighting the most visited pages of the website and the average time spent on them. The
dashboard in Figure 9 provides a means to compare characteristics of traffic flow between
countries.
Figure 8: Most viewed web pages globally with average time spent on each page
Figure 9: Number and type of web pages viewed by country
These dashboards were created using two sets of data from Google Analytics. First the
most visited web pages per country and second the average time spent on each web page with
more than 2000 views. These pages were then grouped into four categories (e-consultation, e-
learning, e-resources and miscellaneous) by hand correlation. Certain pages of interest, such as
the e-consultation log-in page, question of the day landing page etc. were manually identified
and annotated.
This information is most useful for Telemedicine Developers as it advises online content
development and management.

VI. Dashboard to advise mobile strategy
The dashboard in Figure 10 shows the mobile hardware devices most frequently used to
access the Cyber-Sight website from various countries. The graph in Figure 11 also shows the
flow of visitors using mobile devices through the website.
Figure 10: Mobile devices used to access Cyber-Sight by country
Figure 11: Flow of visitors using mobile devices through Cyber-Sight (Generated in Google Analytics)
The dashboard in Figure 10 was created using data from Google Analytics, which
required minimal manipulation to generate and connect to Tableau. The visitor’s flow graph in
Figure 11 can be created on Google Analytics (Standard Reports>Audience>Visitors Flow).
Understanding this graph requires some degree of interpretation as the web pages are labeled by
their URLs. For example, web pages grouped under ‘/bins/volume_page.asp’ and
‘/bins/content_page.asp’ both refer to E-Resources section of the website. Similarly web pages

grouped under ‘/bins/econsult_index’ and ‘/telemedicine/bins/...’ both refer to E-Consultation
section of the website.
This information is most useful for Telemedicine Developers as it advises on mobile
platforms that can be targeted for implementation and also identifies which Cyber-Sight services
are most relevant to users when viewed on a mobile hardware device.
Conclusion
Combining data spread across several databases and presenting it in an easy to
understand and easy to manipulate manner can benefit various internal stakeholders. When such
reporting is customized for each internal stakeholder group, they are quickly able to get relevant
information and thus, may be more likely to utilize it in decision making. Such reporting would
be most beneficial to advise program development locally and to provide insights for evaluation.
The E-Consultation database and Google Analytics are fairly easy to manipulate and can
generate Excel spreadsheet reports relatively easily. One possible limitation of the Google
Analytics database might be that it is unable to track E-Learning web pages. This might be the
reson it lists several thousand visits to undefined web pages on the Cybersight.org domain. An
additional functionality that is desired for the E-Consultation database is to quantify the
promptness and the number of exchanges between mentors and mentees. This will provide us
insights regarding satisfaction and highlight best practices for such online exchanges.
E-Learning database (Clarity 5 content management system) offers limited functionality and
nearly always requires hand correlation to develop even basic reports. Using hand correlation to
combine various reports generated by this database, an Excel spreadsheet containing the
following information should be created for each geographic region.
 Country Name
 Courses taken in that country in a given time frame
 Number of learners in each of the aforementioned courses, their names and their
institution name
Such E-Learning Excel spreadsheets will be sufficient to start connecting with Tableau or other
such analytics software.
The Intranet (or various Excel spreadsheets managed by individuals) contains records of
VF visits, number and location of HBP and FEH programs by year. This information could help
internal stakeholders identify and utilize the complementary roles that Telemedicine services
play in ORBIS’ overall work. This information was challenging to include in Tableau as it
requires building and importing Excel spreadsheets, often from scratch. These Excel
spreadsheets typically contain date fields, location fields and other text fields. More time needs
to go into integrating these kinds of information into the Cyber-Sight related Tableau
dashboards. This would provide internal stakeholders a chance to see, for example, the kinds of
e-learning courses undertaken in a particular region or hospital, and to track how this changes if
a HBP is used as an intervention to rapidly build capacity.
Tableau software was found to have a lot of capacity in presenting and manipulating data
visually. The most utilized feature was the ‘Show Me’ pane, which allows dashboard designers
to quickly traverse between different presentation styles (e.g., pie chart vs. a tree map). Another
feature that was found useful was the creation of hierarchies within data dimensions. For
example Excel spreadsheet column headings (and corresponding data) could be nested to enable

an expandable column. This feature was utilized in the Regional E-Consultation and E-Learning
Summary dashboards described in earlier sections. It enabled the following nesting structure
Country>Hospital name>Partner Doctor name>Course/Case category.
An additional feature of future dashboards could also include a filter for range of time.
The dashboards described in this document were created from data which was selected for a
particular time period (e.g. 2003 to 2012). However the dashboard viewer does not currently
have an easy way to examine smaller segments of time during this original defined time period.

Internal Reporting with Tableau

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