1. Taming Diabetes
How can Big Data help?
Raj N Manickam February 2013

2. Driblets of Data
Pre-Diagnosis State
More than 317 million people worldwide have diabetes –
half of them don’t know they have it!
In the US alone, over 6 million cases yet to be detected
Conclusion – we can’t stop at monitoring the known cases
– the entire population is our dataset!
Opportunistic self-screening
High risk people identifiable with simple questionnaire to
assess risk factors such as age, waist
circumference, family history, cardiovascular history and
gestational history.
… all this adds up to substantial data …
Source: International Diabetes Federation, updated 2012

3. Diabetes Cannot be Cured – Has
to be Managed
What do we need to track?
Appropriate medication, high quality care and good medical advice, you should be able
to lead an active and healthy life and reduce the risk of developing complications.
Keeping your blood sugar levels as close to normal as possible. This can be achieved by
a combination of the following:
Physical Activity Levels
Body Weight
Eating Regimen – types of food, quantify, frequency, time interval, etc.
Tobacco Consumption
Monitoring and Early Detection of Complications – eye, foot, blood pressure, blood
glucose, assessing risks for cardiovascular and kidney disease.
… data data everywhere …

4. Between Office Visits:
Monitoring @ Home
Different warning signs:
Frequent urination
Excessive thirst
Increased hunger
Weight loss
Tiredness
Lack of interest and concentration
Vomiting and stomach pain (often mistaken as the flu)
A tingling sensation or numbness in the hands or feet
Blurred vision
Frequent infections
Slow-healing wounds
… Need to provision patients with devices to
collect, analyze, alert, transmit to HCP …
… along with data on time, location, context – MORE data …

5. What do we need to track?
Diabetes is not Alone – Co-morbidities
Cardiovascular disease - the major cause of death in people with
diabetes (and much disability)
Kidney disease (diabetic nephropathy) - increasingly important
cause of renal failure, and indeed has now become the single most
common cause of end stage renal disease
Nerve disease (diabetic neuropathy): can ultimately lead to
ulceration and amputation of the toes, feet and lower limbs
Eye disease (diabetic retinopathy)
… these need to be monitored and tracked as well – even more data …

6. So, I need to manage a *lot* of data –
what is the connection with ‘Big-Data’?
Big-Data – a term referring to the collection of
technologies, platforms, methods to collect, store, process and
publish ‘large’ amounts of data
You need it when:
Your data volume/velocity/variety needs (current or anticipated)
are too much for traditional technologies / processes
You have special needs that can be handled better by non-
traditional technologies / processes (i.e. elastic
scalability, unstructured data, streaming data, …)
Your business needs social, mobile and cloud-based technologies
and deployments that are better matched with big-data tools
You could base your solution on traditional technologies, yet you
are not sure what you need, choose technologies that can flex as
your needs change.

7. Do I need big-data?
Some Rules of Thumb
Volume –storage needs are more a few terabytes and you
are growing
Variety –significant share of non-relational data that
needs to be processed / accessed / presented along with
relational data
Velocity – need to sip from the fire hose
‘Special’ needs:
Assimilate and integrate social data
Gather and present from mobile devices
Tie-in with cloud-based infrastructure

8. Once I have the big-data –
what else can I do with it?
A few examples from Health Technology Forum (San
Francisco, March 2013) on Data-driven mHealth Tools for Managing
Diabetes:
• Feet First, Inc – using a combination of innovative
devices, tests, processes to screen, monitor, alert and intervene
in complications affecting the foot
• ginger.io – using a combination of passive and user-provided
data from mobile devices to amass massive data volumes that
help with analyzing and delivering timely care
• LogicNets – general platform for decision engines used in
transition of care and continuity of care for in-patients at UCSF
Hospital

9. Sounds cool – I’m sold!
How can I get it, how much does it cost?
Not so fast 
In general, platforms, tools, technologies, vendors not as mature
People with the right skills and aptitude hard to find
Pace of innovation is amazing – can seem like you are building on shifting sands
You can ‘buy’ a solution or roll out your own, using open-source tools – costs can vary from $800
per terabyte to $180,000 per terabyte!(1)
No ‘one neck to choke’ – no ‘one solution’ to buy - you need to procure, assemble, build and
deploy your own
Traditional platforms are not standing still – what was ‘big-data’ a few years ago is no longer so
(1) Source: GigaOM, 2012

10. Conclusions
The answer? Depends
on asking and answering the right questions
Thank you for reading. You can send comments and
questions to ‘2025rm at gmail dot com’
Feel free to use / re-use under Creative Commons 3.0
license – attribution requested (Creative Commons 3.0)