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Managing public health information
- 1. Managing Public Health Data TakingSDG as an example 8th National Public Health Conference, Hotel Equatorial, Melaka. 2-4th August 2016 Jamalludin Ab Rahman B.Med.Sc., MD, MPH Department of Community Medicine Kulliyyah of Medicine
- 2. What are mypoints 1. Public health data is a big data 2. We need to change the way we manage data 3. Use SDG as example 2
- 3. Source of publichealth data 6August2016www.iiumedic.net/commed 3 NCD CDC Primary Healthcare Health Enforcement Occupational Health Environmental Health Nutritional Health
- 4. What is bigdata? 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 6August2016www.iiumedic.net/commed 4
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- 7. So what? Changethe way we capture & use data Change the way we disseminate & share data 7
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- 10. Basically… We generatedabundant 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 10
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- 12. In August 2014UN Secretary-General Ban Ki-moon asked an Independent Expert Advisory Group to make concrete recommendations on bringing about a data revolution in sustainable development. 12
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- 14. Some examples fromSDG SDG 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 14
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- 20. Better data andstatistics will help governments track progress and make sure their decisions are evidence-based; they can also strengthen accountability. This is not just about governments. International agencies, CSOs and the private sector should be involved. A true data revolution would draw on existing and new sources of data to fully integrate statistics into decision making, promote open access to, and use of, data and ensure increased support for statistical systems.” (HLP Report, P23) “ Evidence-based decisions 20
- 21. Challenges 1. Big data– traditional & new sources 2. Information gap – digital divide 21
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- 25. The strategy Information PeopleTechnology • Mostimportant 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 25
- 26. Consider data mining(big data) Secondary analysis of large (available) database Challenging – not standard data, temporal change, missing value, invalid entries 26
- 27. Consider data mining(big data) Secondary analysis of large (available) database Challenging – not standard data, temporal change, missing value, invalid entries 27
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- 29. 6August2016www.iiumedic.net/commed 29 Survey Analysis: BigData Adoption in 2013 Shows Substance Behind the Hype https://www.gartner.com/doc/2589121
- 30. Summary Healthcare datais big data Take note of changing information culture – Web 3.0 Using SDG as the structure or target checklist Use big data technique 30