the power of surface modelling

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The Power of Surface Modelling Bryan Clarke 2015 HiNZ Conference

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Page 1: The Power of Surface Modelling

The Power of Surface Modelling

Bryan Clarke

2015 HiNZ Conference

Page 2: The Power of Surface Modelling

Thanks to ….

Page 3: The Power of Surface Modelling

Overview

• Mapping 101 using John Snow’s Cholera discovery in 1854• Trend mapping for KPIs to look for opportunities for improvements• Localised mapping of a pharmacy to look at market penetration• Specific medication mapping using trend and penetration mapping

Page 4: The Power of Surface Modelling

Progress since John Snow

Page 5: The Power of Surface Modelling

Thematic Mapping• Boundaries are arbitrary• Boundaries don’t change

as the underlying data changes

• Boundaries are often related to non-healthcare functions (eg voting, rating)

• Uncommunicative and statistically invalid

Page 6: The Power of Surface Modelling

Transactions or trends?

Page 7: The Power of Surface Modelling

Scenario One: Regional Example

Page 8: The Power of Surface Modelling

Where can the KPIs be improved to the greatest effect?

Page 9: The Power of Surface Modelling

Life Threatening Incidents(1 month)

Page 10: The Power of Surface Modelling

● Met target (1)

● Missed target(0)

Page 11: The Power of Surface Modelling

Percentage Surface● 100%● 0 %

Page 12: The Power of Surface Modelling

Incident Density Surface ● Highest density● High density

Page 13: The Power of Surface Modelling

Bang for Buck Surface ● Highest opportunity● High opportunity

Page 14: The Power of Surface Modelling

Scenario Two: Specific PharmacyExample

Page 15: The Power of Surface Modelling

http://www.stats.govt.nz/Census/2013-census.aspx

Population Density● Highest density● Lowest density

Page 16: The Power of Surface Modelling

Patient Density● Highest density● Lowest densityϨ 500m Driving distance contours Scale: Kilometres

Page 17: The Power of Surface Modelling

Market Penetration● 60% penetration● 10% penetration

𝑀𝑎𝑟𝑘𝑒𝑡 𝑃𝑒𝑛𝑒𝑡𝑟𝑎𝑡𝑖𝑜𝑛=𝑃𝑎𝑡𝑖𝑒𝑛𝑡𝐷𝑒𝑛𝑠𝑖𝑡𝑦 /𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝐷𝑒𝑛𝑠𝑖𝑡𝑦Scale: Kilometres

Page 18: The Power of Surface Modelling

Driving distance● Closest to pharmacy● Farthest from any pharmacy (4km)

Driving distance fromBastins● up to 500m● up to 1km● up to 1.5kms

Page 19: The Power of Surface Modelling

Customer growth● Greater opportunity● Reduced opportunity

Page 20: The Power of Surface Modelling

Scenario Three: Specific SmokingMedication Example –Champix vs Habitrol

Page 21: The Power of Surface Modelling

Population Density● Highest population● Lowest population

http://www.stats.govt.nz/Census/2013-census.aspx

Page 22: The Power of Surface Modelling

http://www.stats.govt.nz/Census/2013-census.aspx

UrbanSmokerDensity● Highest density● Lowest density

Page 23: The Power of Surface Modelling

http://www.stats.govt.nz/Census/2013-census.aspx

UrbanSmokerPercentage● 35% ● 5%

Page 24: The Power of Surface Modelling

Market Penetration● 60% penetration● 10% penetration

Scale: Kilometres

Page 25: The Power of Surface Modelling

Ratio● Champix ● Habitrol

Ϩ Pharmacymarket contours (5% intervals)

Scale: Kilometres

Page 26: The Power of Surface Modelling

http://www.stats.govt.nz/Census/2013-census.aspx

Deprivation● Least deprived● Most deprived

Scale: Kilometres

Page 27: The Power of Surface Modelling

http://www.stats.govt.nz/Census/2013-census.aspxScale: Kilometres

Ratio● Champix ● Habitrol

Deprivation● Least deprived● Most deprived

Page 28: The Power of Surface Modelling

Scale: Kilometres

Ratio● Champix ● Habitrol

● High smoker density ● Low smoker density http://www.stats.govt.nz/Census/2013-census.aspx

Page 29: The Power of Surface Modelling

Advantages of Surface Analysis• Computation is not particularly intensive• Easy to understand• Easy to compare different data sets• Anonymise the data (without the need for meshblocks)• Communicative• Can be statistically validated• Automated and served up from the cloud