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Creating evidence from open source data: an in-depth analysis of health and social care in Scotland Prof Bill Buchanan, The Cyber Academy http://asecuritysite.com/bigdata Twitter: billatnapier Objectives: - How to turn data into evidence. - Learn something new.

Open Data and Machine Learning - Prof Bill Buchanan

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Creating evidence from open source data: an in-depth analysis of health and social care in Scotland

Prof Bill Buchanan, The Cyber Academyhttp://asecuritysite.com/bigdata

Twitter: billatnapier

Objectives: - How to turn data into evidence. - Learn something new.

[Link]

Open Source Data

Vision [Link]

Open Source Data

London

London DemographicsAge leave school - 16 or under v Greater than 24 [Link]

London Demographics5 Fruit and veg and health children (Aged 4-5) [Link]

London DemographicsOverweight to underweight … Bexley to Harrow [Link]

London DemographicsObese Children … Hexham to Richmond upon Thames [Link] % Obese Children (Year 6) = 1.509 * % Obese Children (Receiption) + 7.313

London DemographicsObese Children … Southwark to Richmond upon Thames [Link]

London (A Lonely World)

London DemographicsLoneliness and Low-incomes … [Link] % of Children in low-income families = -0.583 * Loneliness Rank in London + 33.02

Scotland

Scottish Health Observatory

[Link]

Scotland - Regional AnalysisBreach of peace, common assault and rowdy behave. [Link][Link]

Mental Health

[Link]

SIDM 2016

Scotland - SIMD 2016Housing and Health [Link][Link]

Scotland - SIMD 2016Attainment and Attendance [Link][Link]

Edinburgh - SIMD 2016No CH and Overcrowding [Link][Link]

Edinburgh

Edinburgh - SIMD 2016Income and Health [Link][Link]

Edinburgh - SIMD 2016Employment and Education [Link][Link]

Edinburgh - SIMD 2016Crime and Housing [Link][Link]

Edinburgh - SIMD 2016Working age and population [Link][Link]

Edinburgh - SIMD 2016Housing and Health [Link][Link]

Edinburgh - SIMD 2016Health and Education [Link][Link]

Edinburgh - SIMD 2016Pupil attendance and No qualifications [Link][Link]

Edinburgh - SIMD 2016Health and Education [Link][Link]

Edinburgh - SIMD 2016Health and Employment [Link][Link]

Glasgow

Glasgow - SIMD 2016Health and Employment [Link][Link]

Glasgow - SIMD 2016Health and Housing [Link][Link]

Glasgow (Rebirth)

Machine Learning

Male Life Expectancy [Link]

• Deaths all ages, Deaths from alcohol conditions, Working age population employment deprived

• Deaths from alcohol conditions, Crime rate, Population within 500 metres of a derelict site

• 96.7% success

People claiming pension credits (aged 60+) 21 Deaths all ages 12 Female life expectancy 11 Working age population employment deprived 8 Crime rate 8

Machine Learning [Link]

• Deaths all ages, New cancer registrations, Patients hospitalised with asthma

• Deaths all ages, New cancer registrations, Patients with emergency hospitalisations

• Deaths all ages, New cancer registrations, Adults incapacity benefit/severe disability allow/employment allow

• Deaths all ages, New cancer registrations, Population within 500 metres of a derelict site

• Deaths all ages, Patients hospitalised with asthma, Average tariff score of all pupils on S4 roll

• Early deaths from cancer (<75), Smoking prevalence (adults 16+), Bowel screening uptake

• Smoking prevalence (adults 16+) Working age adults with low/no educational qual Bowel screening uptake

Deaths all ages 35 Male life expectancy 22 All mortality among 15-44 year olds 20 Patients hospitalised with coronary heart disease 6 Child obesity in primary 4

Deaths All Ages [Link]

Estimated smoking attributable deaths 17 Male life expectancy 16 Female life expectancy 16 Adults rating neighbourhood as a very good place to live 14 Child dental health in primary 1 11

All mortality among 15-44 year olds [Link]

Child obesity in primary 37 Early deaths from CHD (<75) 28 Male life expectancy 7 Working age population claiming Out of Work benefits 7 Adults incapacity benefit/severe disability allow/employment allow 6 Prisoner population 6

Early deaths from CHD (<75) [Link]

All mortality among 15-44 year olds 47 Female life expectancy 12 Estimated smoking attributable deaths 12 Deaths all ages 9 Population income deprived 8

Deaths all ages 44 Early deaths from CHD (<75) 16 New cancer registrations 15 Smoking prevalence (adults 16+) 7 Active travel to work 6

Estimated smoking attributable deaths

Smoking prevalence (adults 16+) [Link]

Estimated smoking attributable deaths 14 Child dental health in primary 1 13 Patients hospitalised with (COPD) 12 Child dental health in primary 7 11 Patients (65+) with multiple emergency hospitalisations 7

Male life expectancy 32 Patients (65+) with multiple emergency hospitalisations 7 19 Patients hospitalised with asthma 7 Drug crimes recorded 7 Low birth weight 5

Alcohol-related hospital stays

Factors for Top 50 [Link]

Factors [Link]• Deaths all ages 134 • Male life expectancy 94 • All mortality among 15-44 year olds 85 • Female life expectancy 62 • Estimated smoking attributable deaths 58 • Early deaths from CHD (<75) 53 • Alcohol-related hospital stays 51 • Child obesity in primary 48 • People claiming pension credits (aged 60+) 38 • New cancer registrations 35 • Child dental health in primary 1 34 • Patients (65+) with multiple emergency hospitalisations 32 • Adults incapacity benefit/severe disability allow/employment allow 31 • Working age population claiming Out of Work benefits 29 • Population income deprived 27 • Working age population employment deprived 27 • Patients hospitalised with asthma 24 • Child dental health in primary 23 • Secondary school attendance 22 • Drug crimes recorded 22

People who do not feel in control over their lives struggle because the system does things to them – it doesn't work with them and help them create 'wellness' for themselves … when things happen that alienate people, they lose that sense of control and a whole range of biological, as well as psychological, things occur.

Conclusions

Creating evidence from open source data: an in-depth analysis of health and social care in Scotland

Prof Bill Buchanan, The Cyber Academyhttp://asecuritysite.com/bigdata

Twitter: billatnapier

Objectives: - How to turn data into evidence. - Learn something new.