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USING HEALTHCARE DATA
Considerations, context, and storytelling
August 25, 2015
Anurati Mathur
@anurati
Propeller Health
•  Founded in 2010
•  Located in Madison, WI
and San Francisco, CA
•  FDA 510(k) cleared
•  25+ commercial programs
•  Validated in 12 clinical studies
totaling over 1,200 patients
Propeller Health
Cost of asthma & COPD
Asthma & COPD are the 5th and 6th most expensive diseases in the US
Disease management has not changed in decades
Daily diaries and paper-based action plans add burden &
complexity and are rarely used by patients.
Real-time data can help detect exacerbations
•  Half of patients who go to ED have had symptoms for > 4
days
•  With real-time data, we can intervene early while outpatient
treatment is still an option
What is medication non-adherence?
$290B
Motivations Outcomes
Digital interventions improve adherence
Significant literature supports the use of SMS and audiovisual
reminders to improve adherence to inhaled controller
medications
How the platform works
Sensors measure symptoms & track symptoms
Rescue
Used to address symptoms
when they occur unexpectedly –
among the most important
markers of impairment & risk
Controller / maintenance
Should be used regularly to
minimize or eliminate symptoms
by addressing underlying
pathophysiology
Propeller passively
collects data on
when, where and how
often a person uses
their rescue inhaler
1:38:08
PM PST
Pollen Count 5.2
AQI 102
N47o 34.4452. W110o77.8257
2 inhalations of ProAir (120mcg)
20 seconds apart
Winds from SW, 13mph
And attaches meta
data to each
actuation
Multi-faceted approach to improving adherence
•  Non-adherence is complex and multi-dimensional
•  Improving adherence requires an equally multi-dimensional solution
Rules driven notifications & alerts
Goal is to give users small bits of actionable, personalized
feedback to foster self-management, without increasing the effort
required of users
•  Passive
•  Feed of personalized insights
•  Personalized encouragement
•  Triggered questions & surveys
•  Messaging from Care Team
25+ commercial programs across the country
Retain Users
Enroll Users●  Intercept during
normal clinical care
●  Telephone to schedule visit
●  Email marketing
●  Direct mail
●  Online targeted marketing
●  Incentives
●  Partnership
●  In person (face-to-face)
●  On telephone
●  Online self-enrollment
●  Hardware
●  Software
●  CSS Team
Experiments every step of the way
The healthcare system
Patient
The healthcare system
Patient
MD, NP, RN
Hospital, clinic
Provider
$$
The healthcare system
Patient
MD, NP, RN
Hospital, clinic
Provider
$$
1. Goods
2. Services
Time
Expertise
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
$$
Patient
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
$$
$$$$$$
$$
$$
Patient
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$$$$$
$$
$$ $$$$
Risk-sharing
Patient
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
$$
$$
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
Citizen
$$
$$
$$
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
Citizen
$$
$$
$$
$$
$$ $$
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
Citizen
$$
$$
$$
$$
$$$$
Healthcare goods & services
Pharma, digital health, and more
The healthcare system
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
Citizen
$$
$$
$$
$$
$$$$
Healthcare data – until recently
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
Citizen
$$
$$
$$
$$
$$$$
1
2
Data are the backbone of value-based care
Better data are needed to
understand what happens to
patients in between physician
visits
•  to effectively manage care
•  to improve outcomes
•  to prove effectiveness
Healthcare data - today
Insurance companies
MD, NP, RN
Hospital, clinic
Provider
1. Goods
2. Services
Time
Expertise
Deductible,
copay
$$
$$$$
Patient
Worker
Citizen
$$
$$
$$
$$
$$$$
1
2
4
3
Healthcare data - today
Healthcare data - today
Healthcare data - today
Other, relevant non-healthcare data
•  Enacted August 21, 1996
•  4 key components, including: administrative simplification
•  Administrative simplification, including: privacy & security
standards
Health Insurance Portability and Accountability Act
Privacy standards
•  Protected Health
Information (PHI)
•  Covered entities
•  Routine purposes
Security standards
•  Administrative: Policies, training, etc.
•  Physical: unauthorized intrusion, etc.
•  Technical: encryption, etc.
Once information is de-identified, it is no longer subject to the
privacy regulation restrictions.
De-identification
Statistical de-identification
•  Statistical expert confirms
that data could not
reasonably be re-identified
•  Documentation & results of
all statistical tests &
analyses
Safe Harbor Guidelines
Removal of 18 personal
identifiers that constitute
Personally identifiable
information (PII).
1.  Names
2.  Geo-specificity < than state
3.  All dates (birth, death, doc visits, etc.)
4.  Telephone numbers
5.  Fax numbers
6.  Email addresses
7.  Social security #s
8.  Medical record #s
9.  Health plan #s
10.  Account #s
11.  License #s
12.  Vehicle identifiers
13.  Device identifiers
14.  URLs
15.  IP addresses
16.  Biometric identifiers
17.  Full face photography
18.  Any other uniquely identifying #
Statistical de-identification
Statistical de-identification
Clinical trials
Series of statistically instrumented experiments to prove safety
& efficacy of treatments, devices, and medical strategies
Development process – medical devices
Propeller clinical trials design
500-1,000 enrolled
Intervention
Control
6-12 month study period,
with quarterly assessments of control
Randomization
Sensor +
intervention
Sensor + no
intervention
Primary outcomes
Asthma control
Poorly controlled
Not well controlled
Well controlled
Inhaler use
Rescue inhaler
Controller inhaler
Louisville clinical results
Rescue inhaler use over time Asthma control over time
Anurati Mathur & Propeller Health @ Madison's Big Data Meetup
Case study: Propeller Health in Louisville, Kentucky
“One of the top 20 “most challenging
places to live with asthma in the US.”
- Asthma & Allergy Foundation of America, 2014
Snapshot of Louisville health
•  1 in 3 adults in Louisville are overweight or obese
-  Increased risk for high blood pressure, diabetes, some
cancers, arthritis / joint pain
•  25% of Louisville adults still use tobacco products
-  Increased risk for lung disease, cancer, heart attack and stroke,
and poor wound healing
•  Louisville’s rate of deaths for heart disease, cancer, diabetes,
stroke are higher than the death rates for Kentucky and the
US
Why do this study?
Asthma hospitalizations in Jefferson County, 2011
Data like this has many problems:
•  Based on healthcare utilization
•  Retrospective, time lags
•  Aggregated, low spatial resolution
Louisville study design
Enrollment begins
Baseline data collection for 1 month
instrumentation with sensors, but no access to data
Intervention period & data collection for 12 months
5,430 unique rescue inhaler events recorded
27,197 person-days of data
Temporal data
Temporal data Air quality index
(Levels of health
concern)
Numerical
value
Meaning
Good 0 to 50 Air quality is considered satisfactory & poses
little or no risk
Moderate 51 to 100 Air quality is acceptable, but for some
pollutants there may be risk for unusually
sensitive groups
Unhealthy for
sensitive groups
101 to 150 Members of sensitive groups may experience
health effects
Unhealthy 151 to 200 Everyone may begin to experience health
effects
Very unhealthy 201 to 300 Health warnings of emergency conditions
Hazardous 301 to 500 Health alerts: everyone may experience serious
health effects
Temporal data
EPA monitoring in Jefferson County
QGIS
Understanding the temporal data
Tableau
Inhaler events / person / day
Understanding the temporal data
Inhaler events / person / day
Understanding the temporal data
Understanding the temporal data
Tableau
Understanding the temporal data
Understanding the temporal data
Tableau
Geospatial data
•  Usually latitude, longitude
•  A shapefile is an vector data storage format for storing
the location, shape, and attributes of geographic features
•  Projections matter!
This slide has an
animation.
Projecting a head
North America
This slide has an
animation.
World Geodetic System, 1984 – WGS 84
•  Standard for use in cartography and navigation, including GPS
•  Coordinate origin at the Earth’s center of mass
•  Meridian of zero longitude is ~336 feet east of Greenwich
•  Originally developed by the Department of Defense in 1966
•  Default projection for Tableau & QGIS
Inhaler use events
Tableau
Inhaler use events – wide distribution
Inhaler use events – by device type
Tableau
Inhaler use events – by medication
Tableau
Inhaler use events & census geography
QGIS
Inhaler use events & census geography
QGIS
Inhaler use events & other interesting shapefiles
Total Crime Index, ESRI crime indices data, 2014
QGIS
Inhaler use events & other interesting shapefiles
QGIS
Median household income, American Community Survey (ACS) data, 2012
Inhaler use events & other interesting shapefiles
QGIS
Median year housing structure built, American Community Survey (ACS) data, 2012
Inhaler use events & other interesting shapefiles
Metro parks, Louisville / Jefferson County Information Consortium (LOJIC), 2010
	
  	
  
QGIS
Inhaler use events & other interesting shapefiles
Tree canopy, National Land Cover Database / USGS, 2001
QGIS
	
  	
  
Inhaler use events & other interesting shapefiles
Major roads, Kentucky Transportation Cabinet, 2015
	
  	
  
QGIS
QGIS
Inhaler use events & other interesting shapefiles
Avg. annual traffic count, Kentucky Transportation Cabinet, 2012
	
  	
  
QGIS
Inhaler use events & other interesting shapefiles
Avg. annual traffic count, Kentucky Transportation Cabinet, 2012
	
  	
  
Inhaler use events & other interesting shapefiles
Active mines, Kentucky Mine Mapping Information System, 2008
QGIS
Inhaler use events & other interesting shapefiles
This slide has an
animation.
So what?
This slide has an
animation.
Spatial predictors we explored
•  Exposures
•  Proximity to emission sources, industrial areas, power plants, active mines
•  Transportation infrastructure
•  High density traffic areas
•  Land use
•  Impervious surface (%)
•  “Greenness” and tree canopy
•  Proximity to green spaces & parks
•  Neighborhood
•  Socioeconomic measures: household income, educational attainment,
property values, property age, crime rates
•  Population density
•  Study factors
•  # of users enrolled per zip
Kernels of inhaler use density to find associations
ArcGIS, ERDAS
Ecological niche modeling
1. Geo-reference inhaler use points
2. GIS of environmental variables
3. Extract environmental data at each point
4. Build model against background sample of
pseudo-absences
5. Model calibration & selection (AUC, cross-
validation with test data, etc.)
6. Probability distribution based on environmental
suitability
7. Assessment of environmental
variable contributions
8. Extrapolate into new
environmental or geographic space
9. Test with additional data
Probability of inhaler use – environmental modeling
ArcGIS, ERDAS
Target areas for intervention
ArcGIS, ERDAS
Testing Louisville strategic intervention scenarios
•  What if Louisville…
•  Reduced traffic density?	
  
•  Reduced particulate matter?	
  
•  Greened downtown?	
  
	
  
What if Louisville achieved a 10% reduction in PM2.5
ArcGIS, ERDAS
à 27% reduction in amount of area at risk
ArcGIS, ERDAS
Current AIR Louisville emphases
•  Improved data & sampling
•  More analyses, guided closely by city needs
•  More transparency & public awareness with open data portal
Current AIR Louisville emphases
Obama Climate Data Initiative
Sharing Louisville data publicly
Interesting / informative Surprising / delightful
D3
This slide has an
animation.
D3
D3
D3
D3
D3
D3
D3
Visualizing inhaler events – version 1
D3, TopoJSON
This slide has an
animation.
Mapbox
Mapbox
Mapbox
Visualizing inhaler events – version 2
D3, Mapbox
This slide has an
animation.
Visualizing inhaler events – version 3
D3, Mapbox
This slide has an
animation.
Louisville is one of the top 20
most difficult places to live
with asthma in the US.
AIR Louisville enrolled 300
residents to track their asthma
rescue inhaler use with
Propeller Health sensors.
AIR Louisville collected data on citizens’ inhaler use for 12 months
Here’s what we learned…
We learned a lot about how
Louisville residents experience
asthma symptoms and use
their inhalers.
Only 31% of asthma attacks
occur in homes.
People use inhalers more
when it is hot outside.
Weed, pollen and mold
significantly increase asthma
risk.
Wind clears the air and
reduces asthma attacks.
When pollution levels are high,
people have more asthma
symptoms.
Strong city partnerships are
key to a successful program.
People use rescue inhalers
more on weekdays than on
weekends.
Trees provide a protective
effect for asthma attacks
(especially evergreens).
A 10% reduction in particulate
matter could mean a 27%
reduction in asthma risk.
Blue dot = inhaler signal
This slide has an
animation.
In Mayor Fischer’s own words
This slide has an
animation.
https://youtu.be/iiaTPV09vBE?t=6m27s
Thank you!
Anurati Mathur
anuratim@gmail.com
@anurati
https://www.linkedin.com/in/anurati

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Anurati Mathur & Propeller Health @ Madison's Big Data Meetup

  • 1. USING HEALTHCARE DATA Considerations, context, and storytelling August 25, 2015 Anurati Mathur @anurati
  • 2. Propeller Health •  Founded in 2010 •  Located in Madison, WI and San Francisco, CA •  FDA 510(k) cleared •  25+ commercial programs •  Validated in 12 clinical studies totaling over 1,200 patients
  • 4. Cost of asthma & COPD Asthma & COPD are the 5th and 6th most expensive diseases in the US
  • 5. Disease management has not changed in decades Daily diaries and paper-based action plans add burden & complexity and are rarely used by patients.
  • 6. Real-time data can help detect exacerbations •  Half of patients who go to ED have had symptoms for > 4 days •  With real-time data, we can intervene early while outpatient treatment is still an option
  • 7. What is medication non-adherence? $290B Motivations Outcomes
  • 8. Digital interventions improve adherence Significant literature supports the use of SMS and audiovisual reminders to improve adherence to inhaled controller medications
  • 10. Sensors measure symptoms & track symptoms Rescue Used to address symptoms when they occur unexpectedly – among the most important markers of impairment & risk Controller / maintenance Should be used regularly to minimize or eliminate symptoms by addressing underlying pathophysiology
  • 11. Propeller passively collects data on when, where and how often a person uses their rescue inhaler
  • 12. 1:38:08 PM PST Pollen Count 5.2 AQI 102 N47o 34.4452. W110o77.8257 2 inhalations of ProAir (120mcg) 20 seconds apart Winds from SW, 13mph And attaches meta data to each actuation
  • 13. Multi-faceted approach to improving adherence •  Non-adherence is complex and multi-dimensional •  Improving adherence requires an equally multi-dimensional solution
  • 14. Rules driven notifications & alerts Goal is to give users small bits of actionable, personalized feedback to foster self-management, without increasing the effort required of users •  Passive •  Feed of personalized insights •  Personalized encouragement •  Triggered questions & surveys •  Messaging from Care Team
  • 15. 25+ commercial programs across the country
  • 16. Retain Users Enroll Users●  Intercept during normal clinical care ●  Telephone to schedule visit ●  Email marketing ●  Direct mail ●  Online targeted marketing ●  Incentives ●  Partnership ●  In person (face-to-face) ●  On telephone ●  Online self-enrollment ●  Hardware ●  Software ●  CSS Team Experiments every step of the way
  • 18. The healthcare system Patient MD, NP, RN Hospital, clinic Provider $$
  • 19. The healthcare system Patient MD, NP, RN Hospital, clinic Provider $$ 1. Goods 2. Services Time Expertise
  • 20. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise $$ Patient
  • 21. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise $$ $$$$$$ $$ $$ Patient
  • 22. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$$$$$ $$ $$ $$$$ Risk-sharing Patient
  • 23. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker $$ $$
  • 24. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker Citizen $$ $$ $$
  • 25. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker Citizen $$ $$ $$ $$ $$ $$
  • 26. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker Citizen $$ $$ $$ $$ $$$$
  • 27. Healthcare goods & services Pharma, digital health, and more
  • 28. The healthcare system Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker Citizen $$ $$ $$ $$ $$$$
  • 29. Healthcare data – until recently Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker Citizen $$ $$ $$ $$ $$$$ 1 2
  • 30. Data are the backbone of value-based care Better data are needed to understand what happens to patients in between physician visits •  to effectively manage care •  to improve outcomes •  to prove effectiveness
  • 31. Healthcare data - today Insurance companies MD, NP, RN Hospital, clinic Provider 1. Goods 2. Services Time Expertise Deductible, copay $$ $$$$ Patient Worker Citizen $$ $$ $$ $$ $$$$ 1 2 4 3
  • 36. •  Enacted August 21, 1996 •  4 key components, including: administrative simplification •  Administrative simplification, including: privacy & security standards Health Insurance Portability and Accountability Act Privacy standards •  Protected Health Information (PHI) •  Covered entities •  Routine purposes Security standards •  Administrative: Policies, training, etc. •  Physical: unauthorized intrusion, etc. •  Technical: encryption, etc.
  • 37. Once information is de-identified, it is no longer subject to the privacy regulation restrictions. De-identification Statistical de-identification •  Statistical expert confirms that data could not reasonably be re-identified •  Documentation & results of all statistical tests & analyses Safe Harbor Guidelines Removal of 18 personal identifiers that constitute Personally identifiable information (PII). 1.  Names 2.  Geo-specificity < than state 3.  All dates (birth, death, doc visits, etc.) 4.  Telephone numbers 5.  Fax numbers 6.  Email addresses 7.  Social security #s 8.  Medical record #s 9.  Health plan #s 10.  Account #s 11.  License #s 12.  Vehicle identifiers 13.  Device identifiers 14.  URLs 15.  IP addresses 16.  Biometric identifiers 17.  Full face photography 18.  Any other uniquely identifying #
  • 40. Clinical trials Series of statistically instrumented experiments to prove safety & efficacy of treatments, devices, and medical strategies Development process – medical devices
  • 41. Propeller clinical trials design 500-1,000 enrolled Intervention Control 6-12 month study period, with quarterly assessments of control Randomization Sensor + intervention Sensor + no intervention Primary outcomes Asthma control Poorly controlled Not well controlled Well controlled Inhaler use Rescue inhaler Controller inhaler
  • 42. Louisville clinical results Rescue inhaler use over time Asthma control over time
  • 44. Case study: Propeller Health in Louisville, Kentucky “One of the top 20 “most challenging places to live with asthma in the US.” - Asthma & Allergy Foundation of America, 2014
  • 45. Snapshot of Louisville health •  1 in 3 adults in Louisville are overweight or obese -  Increased risk for high blood pressure, diabetes, some cancers, arthritis / joint pain •  25% of Louisville adults still use tobacco products -  Increased risk for lung disease, cancer, heart attack and stroke, and poor wound healing •  Louisville’s rate of deaths for heart disease, cancer, diabetes, stroke are higher than the death rates for Kentucky and the US
  • 46. Why do this study? Asthma hospitalizations in Jefferson County, 2011 Data like this has many problems: •  Based on healthcare utilization •  Retrospective, time lags •  Aggregated, low spatial resolution
  • 47. Louisville study design Enrollment begins Baseline data collection for 1 month instrumentation with sensors, but no access to data Intervention period & data collection for 12 months 5,430 unique rescue inhaler events recorded 27,197 person-days of data
  • 49. Temporal data Air quality index (Levels of health concern) Numerical value Meaning Good 0 to 50 Air quality is considered satisfactory & poses little or no risk Moderate 51 to 100 Air quality is acceptable, but for some pollutants there may be risk for unusually sensitive groups Unhealthy for sensitive groups 101 to 150 Members of sensitive groups may experience health effects Unhealthy 151 to 200 Everyone may begin to experience health effects Very unhealthy 201 to 300 Health warnings of emergency conditions Hazardous 301 to 500 Health alerts: everyone may experience serious health effects
  • 51. EPA monitoring in Jefferson County QGIS
  • 52. Understanding the temporal data Tableau Inhaler events / person / day
  • 53. Understanding the temporal data Inhaler events / person / day
  • 58. Geospatial data •  Usually latitude, longitude •  A shapefile is an vector data storage format for storing the location, shape, and attributes of geographic features •  Projections matter! This slide has an animation.
  • 60. North America This slide has an animation.
  • 61. World Geodetic System, 1984 – WGS 84 •  Standard for use in cartography and navigation, including GPS •  Coordinate origin at the Earth’s center of mass •  Meridian of zero longitude is ~336 feet east of Greenwich •  Originally developed by the Department of Defense in 1966 •  Default projection for Tableau & QGIS
  • 63. Inhaler use events – wide distribution
  • 64. Inhaler use events – by device type Tableau
  • 65. Inhaler use events – by medication Tableau
  • 66. Inhaler use events & census geography QGIS
  • 67. Inhaler use events & census geography QGIS
  • 68. Inhaler use events & other interesting shapefiles Total Crime Index, ESRI crime indices data, 2014 QGIS
  • 69. Inhaler use events & other interesting shapefiles QGIS Median household income, American Community Survey (ACS) data, 2012
  • 70. Inhaler use events & other interesting shapefiles QGIS Median year housing structure built, American Community Survey (ACS) data, 2012
  • 71. Inhaler use events & other interesting shapefiles Metro parks, Louisville / Jefferson County Information Consortium (LOJIC), 2010     QGIS
  • 72. Inhaler use events & other interesting shapefiles Tree canopy, National Land Cover Database / USGS, 2001 QGIS    
  • 73. Inhaler use events & other interesting shapefiles Major roads, Kentucky Transportation Cabinet, 2015     QGIS
  • 74. QGIS Inhaler use events & other interesting shapefiles Avg. annual traffic count, Kentucky Transportation Cabinet, 2012    
  • 75. QGIS Inhaler use events & other interesting shapefiles Avg. annual traffic count, Kentucky Transportation Cabinet, 2012    
  • 76. Inhaler use events & other interesting shapefiles Active mines, Kentucky Mine Mapping Information System, 2008 QGIS
  • 77. Inhaler use events & other interesting shapefiles This slide has an animation.
  • 78. So what? This slide has an animation.
  • 79. Spatial predictors we explored •  Exposures •  Proximity to emission sources, industrial areas, power plants, active mines •  Transportation infrastructure •  High density traffic areas •  Land use •  Impervious surface (%) •  “Greenness” and tree canopy •  Proximity to green spaces & parks •  Neighborhood •  Socioeconomic measures: household income, educational attainment, property values, property age, crime rates •  Population density •  Study factors •  # of users enrolled per zip
  • 80. Kernels of inhaler use density to find associations ArcGIS, ERDAS
  • 81. Ecological niche modeling 1. Geo-reference inhaler use points 2. GIS of environmental variables 3. Extract environmental data at each point 4. Build model against background sample of pseudo-absences 5. Model calibration & selection (AUC, cross- validation with test data, etc.) 6. Probability distribution based on environmental suitability 7. Assessment of environmental variable contributions 8. Extrapolate into new environmental or geographic space 9. Test with additional data
  • 82. Probability of inhaler use – environmental modeling ArcGIS, ERDAS
  • 83. Target areas for intervention ArcGIS, ERDAS
  • 84. Testing Louisville strategic intervention scenarios •  What if Louisville… •  Reduced traffic density?   •  Reduced particulate matter?   •  Greened downtown?    
  • 85. What if Louisville achieved a 10% reduction in PM2.5 ArcGIS, ERDAS
  • 86. à 27% reduction in amount of area at risk ArcGIS, ERDAS
  • 87. Current AIR Louisville emphases •  Improved data & sampling •  More analyses, guided closely by city needs •  More transparency & public awareness with open data portal
  • 89. Obama Climate Data Initiative
  • 90. Sharing Louisville data publicly Interesting / informative Surprising / delightful
  • 91. D3 This slide has an animation.
  • 92. D3
  • 93. D3
  • 94. D3
  • 95. D3
  • 96. D3
  • 97. D3
  • 98. D3
  • 99. Visualizing inhaler events – version 1 D3, TopoJSON This slide has an animation.
  • 100. Mapbox
  • 101. Mapbox
  • 102. Mapbox
  • 103. Visualizing inhaler events – version 2 D3, Mapbox This slide has an animation.
  • 104. Visualizing inhaler events – version 3 D3, Mapbox This slide has an animation.
  • 105. Louisville is one of the top 20 most difficult places to live with asthma in the US. AIR Louisville enrolled 300 residents to track their asthma rescue inhaler use with Propeller Health sensors. AIR Louisville collected data on citizens’ inhaler use for 12 months Here’s what we learned… We learned a lot about how Louisville residents experience asthma symptoms and use their inhalers. Only 31% of asthma attacks occur in homes. People use inhalers more when it is hot outside. Weed, pollen and mold significantly increase asthma risk. Wind clears the air and reduces asthma attacks. When pollution levels are high, people have more asthma symptoms. Strong city partnerships are key to a successful program. People use rescue inhalers more on weekdays than on weekends. Trees provide a protective effect for asthma attacks (especially evergreens). A 10% reduction in particulate matter could mean a 27% reduction in asthma risk. Blue dot = inhaler signal This slide has an animation.
  • 106. In Mayor Fischer’s own words This slide has an animation. https://youtu.be/iiaTPV09vBE?t=6m27s