Managing Public Health DataTaking SDG as an example8th National Public Health Conference, Hotel Equatorial, Melaka. 2-4th August 2016

Jamalludin Ab Rahman B.Med.Sc., MD, MPH

Department of Community MedicineKulliyyah of Medicine

What are my points1. Public health data is a big data2. We need to change the way we manage data3. Use SDG as example

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Source of public health data 6 Au

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NCD

CDC

Primary Healthcare

Health Enforcement Occupational

Health

EnvironmentalHealth

Nutritional Health

What is big data? Literally means a lot of data Origin – traced down to 1989, Erik Larson; 1990s, John

Mashey…. Doug Laney, 2001 defined as 3V – Volume, Velocity &

Variety In fact there are more Vs…. Volume, Variety, Velocity,

Variability & Veracity

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http://www.evolutionoftheweb.com/#/growth/day

Data increase exponentially

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So what? Change the way we capture

& use data Change the way we

disseminate & share data

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Basically… We generated abundant of data We need abundant of data (do we?) To cater for this changing information architecture Let’s look on how to manage those data/info using SDG

as example

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In August 2014 UN Secretary-General Ban Ki-moon asked an Independent

Expert Advisory Group to make concrete recommendations on

bringing about a data revolution in sustainable development.

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Some examples from SDGSDG Data from UN

No poverty Monitor income level through spending pattern

Zero hunger Track food security through food price monitoring

Good health & well being Track physical activity from phone

Quality education Student’s drop out rate

Gender equality Spending pattern between gender

Clean water & sanitation Data from sensors connected to pump

Affordable & clean energy Smart metering to gauge use of energy

Decent work & economy growth Global postal pattern

Industry innovation & infrastructure GPS data on public transport

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Better data and statistics will helpgovernments track progress and make suretheir decisions are evidence-based; they canalso strengthen accountability. This is notjust about governments. Internationalagencies, CSOs and the private sectorshould be involved. A true data revolutionwould draw on existing and new sources ofdata to fully integrate statistics intodecision making, promote open access to,and use of, data and ensure increasedsupport for statistical systems.” (HLPReport, P23)

“

Evidence-based decisions

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Challenges1. Big data – traditional & new sources2. Information gap – digital divide

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The strategyInformation

PeopleTechnology

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The strategyInformation

PeopleTechnology

• Most important step!!• Determine the information

required• Determine data to collect• Identify must have from

good to have• Determine standard to

follow• Determine network and

storage infrastructure• Always think of backup &

recovery system• Acceptance by users• Simple & attractive

interface• Delicate migration from

old practice• Big data approach

• Form the committed working committee

• Convince stake holders• Identify the ‘champions’• Reward & motivation• Proper & continuous

users training• Feedback to users &

stake holders

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Consider data mining (big data) Secondary analysis of large (available) database Challenging – not standard data, temporal change,

missing value, invalid entries

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Consider data mining (big data) Secondary analysis of large (available) database Challenging – not standard data, temporal change,

missing value, invalid entries

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Survey Analysis: Big Data Adoption in 2013 Shows Substance Behind the Hypehttps://www.gartner.com/doc/2589121

Summary Healthcare data is big data Take note of changing information culture – Web 3.0 Using SDG as the structure or target checklist Use big data technique

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