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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)
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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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