Moving Beyond the Map <ul><li>Geospatial Analysis applied to Public Health and the Changing View of Health Equity </li></u...
Computer Mapping and Geographic Information Systems (GIS) <ul><li>Most common use – The creation of land records.* </li></...
Computer Mapping and Geographic Information Systems (GIS) <ul><li>Analytical processes usually rank lower, with regard to ...
Geographic Visualization <ul><li>Support material for reports, charts, and graphs. </li></ul><ul><li>In order to justify t...
Geospatial Analysis Providing an Expanded Use of GIS in Public Health <ul><li>Predictive Modeling  – identifying “hot spot...
Early Pioneer <ul><li>John Snow’s Cholera Map from 1885 </li></ul><ul><li>Map with multiple layers showing a disease outbr...
 
 
Predictive Modeling of Infant Mortality <ul><li>Example:  City of Richmond </li></ul><ul><ul><li>In 2007, City rate of 12....
Richmond VA Infant Deaths, 1990-2005 Predictive Kriging Analysis
Predictive Modeling of Infant Mortality <ul><li>Example:  City of Richmond </li></ul><ul><ul><li>Problem is more focused o...
Infant Mortality – Optimum Clinic Placement <ul><li>Example:  Tidewater area </li></ul><ul><ul><li>In 2007, Planning Distr...
 
Infant Mortality – Optimum Clinic Placement <ul><li>Example:  Tidewater area </li></ul><ul><ul><li>Mean-weighted center es...
Breast Cancer – Predicting Locations of Under-Reporting <ul><li>Example:  Statewide </li></ul><ul><ul><li>Based on multipl...
 
! ( Mammography Units
Breast Cancer – Predicting Locations of Under-Reporting <ul><li>Example:  Statewide </li></ul><ul><ul><li>Southern Virgini...
Psychiatric Facilities – Drive Time Analysis <ul><li>Example:  Statewide </li></ul><ul><ul><li>Areas within one hour of a ...
Psychiatric Facilities – Drive Time Analysis
Thinking and Planning Geospatial with  Regard to Public Health <ul><li>Data distribution </li></ul><ul><li>Confidentiality...
Thank you! Moving Beyond the Map Steve Sedlock, Executive Director The Virginia Network for Geospatial Health Research, In...
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Moving Beyond the Map: Geospatial Analysis applied to Public Health and the Changing View of Health Equity

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Presentation by at the 2009 Virginia Health Equity Conference.

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  • Disaggregation and target areas, based on more specific locational data of incidences, and where to specify intervention. We can always aggregate back up – get as small as possible.
  • The issue of infant mortality cuts across jurisdictional boundaries. Predictive Kriging at the block group level. Police model: With high-probability, the next infant deaths will be in this area. Using this for grants.
  • Mean-weighted centers. Clusters helping for clinic placement.
  • 1200 to 2000 women walking around with undiagnosed breast cancer. Residual analysis compared between Northern VA and the state standard, we determined that there are potentially X amount of undiagnosed breast cancer incidences. This relates back to the fact that we know, through the Cancer Registry, that we have very high levels of late-stage breast cancer in these areas. High percentage of late-stage diagnosis of breast cancer in other data. The next slide shows the mortality data that confirms this slide.
  • Moving Beyond the Map: Geospatial Analysis applied to Public Health and the Changing View of Health Equity

    1. 1. Moving Beyond the Map <ul><li>Geospatial Analysis applied to Public Health and the Changing View of Health Equity </li></ul>Steve Sedlock, Executive Director The Virginia Network for Geospatial Health Research, Inc. Virginia Health Equity Conference – September 10-11, 2009
    2. 2. Computer Mapping and Geographic Information Systems (GIS) <ul><li>Most common use – The creation of land records.* </li></ul><ul><li>Other common uses – cartography, visualization, spatial data management. </li></ul>* 2008 Geospatial Technology Report, Geospatial Information & Technology Association (GITA), Aurora, CO.
    3. 3. Computer Mapping and Geographic Information Systems (GIS) <ul><li>Analytical processes usually rank lower, with regard to usage. </li></ul><ul><ul><li>Spatial analysis </li></ul></ul><ul><ul><li>Geostatistical analysis </li></ul></ul><ul><ul><li>Network analysis </li></ul></ul><ul><li>This type of functionality is typically not available in core GIS (added purchase).* </li></ul>* ESRI extensions include Spatial, Geostatistical, Network, Tracking, and Survey Analysts. These are separate from the core ArcGIS Desktop functionality.
    4. 4. Geographic Visualization <ul><li>Support material for reports, charts, and graphs. </li></ul><ul><li>In order to justify the purchase of GIS software, an organization must get a higher level of usage. </li></ul><ul><li>Simply as a support tool, GIS will have problems sustaining itself. </li></ul>
    5. 5. Geospatial Analysis Providing an Expanded Use of GIS in Public Health <ul><li>Predictive Modeling – identifying “hot spots” where disease or problems are occurring. </li></ul><ul><li>Time-distance analysis – identifying medically-underserved areas (MUAs). </li></ul><ul><li>Service area analysis – determining the appropriate placement for clinics. </li></ul>
    6. 6. Early Pioneer <ul><li>John Snow’s Cholera Map from 1885 </li></ul><ul><li>Map with multiple layers showing a disease outbreak. </li></ul>
    7. 9. Predictive Modeling of Infant Mortality <ul><li>Example: City of Richmond </li></ul><ul><ul><li>In 2007, City rate of 12.4 deaths per 1,000 live births was well above the state rate of 7.7* </li></ul></ul><ul><ul><li>Is infant mortality a geographically widespread problem in the city? </li></ul></ul><ul><ul><li>Predictive modeling, through the use of geospatial process called Kringing, tells us “No.” </li></ul></ul>* Source: Virginia Department of Health – Health Statistics Report, 2007.
    8. 10. Richmond VA Infant Deaths, 1990-2005 Predictive Kriging Analysis
    9. 11. Predictive Modeling of Infant Mortality <ul><li>Example: City of Richmond </li></ul><ul><ul><li>Problem is more focused on an area in eastern Richmond and East-Central Henrico County. </li></ul></ul><ul><ul><li>The problem is cross-jurisdictional. </li></ul></ul><ul><ul><li>Reframing the answer to the problem: </li></ul></ul><ul><ul><ul><li>Potential for the city to geographically identify “hot spots” and focus resources. </li></ul></ul></ul><ul><ul><li>Next level of analysis –the social, behavioral, and environmental variables that could be contributing to this problem. </li></ul></ul><ul><ul><li>Potential Intervention: </li></ul></ul><ul><ul><ul><li>Police know where the next murder is likely to take place. </li></ul></ul></ul><ul><ul><ul><li>Predict where infant mortality is going to occur. </li></ul></ul></ul>
    10. 12. Infant Mortality – Optimum Clinic Placement <ul><li>Example: Tidewater area </li></ul><ul><ul><li>In 2007, Planning District 20 rate of 10.7* </li></ul></ul><ul><ul><ul><li>Norfolk – 16.4 </li></ul></ul></ul><ul><ul><ul><li>Portsmouth – 7.3 </li></ul></ul></ul><ul><ul><ul><li>Chesapeake – 12.3 </li></ul></ul></ul><ul><ul><li>Predictive modeling, using geospatial process called Kernel Density analysis, focuses in on an area that crosses between Norfolk, Tidewater, and Chesapeake. </li></ul></ul>* Source: Virginia Department of Health – Health Statistics Report, 2007.
    11. 14. Infant Mortality – Optimum Clinic Placement <ul><li>Example: Tidewater area </li></ul><ul><ul><li>Mean-weighted center establishes the best locations for maternity clinics in the “hot spot” area. </li></ul></ul><ul><ul><li>Next level of analysis -- the social, behavioral, and environmental variables that could be contributing to this being a “hot spot” area. </li></ul></ul>
    12. 15. Breast Cancer – Predicting Locations of Under-Reporting <ul><li>Example: Statewide </li></ul><ul><ul><li>Based on multiple analyses, determine the potential number of undiagnosed breast cancer cases. </li></ul></ul>
    13. 17. ! ( Mammography Units
    14. 18. Breast Cancer – Predicting Locations of Under-Reporting <ul><li>Example: Statewide </li></ul><ul><ul><li>Southern Virginia potentially has 2,000 undiagnosed cases of breast cancer. </li></ul></ul><ul><ul><li>Mammography locations reflect a lack of facilities in this area. </li></ul></ul><ul><ul><li>Next level of analysis -- the social, behavioral, and environmental variables that could be contributing to Southern Virginia’s potential under-reporting. </li></ul></ul>
    15. 19. Psychiatric Facilities – Drive Time Analysis <ul><li>Example: Statewide </li></ul><ul><ul><li>Areas within one hour of a psychiatric bed facility. </li></ul></ul>
    16. 20. Psychiatric Facilities – Drive Time Analysis
    17. 21. Thinking and Planning Geospatial with Regard to Public Health <ul><li>Data distribution </li></ul><ul><li>Confidentiality </li></ul><ul><li>Cost and Economies of Scale </li></ul><ul><li>Maintaining objectivity through independent research </li></ul><ul><li>Reframing the question. </li></ul>
    18. 22. Thank you! Moving Beyond the Map Steve Sedlock, Executive Director The Virginia Network for Geospatial Health Research, Inc. Phone: 804-264-3325 Email: [email_address]

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