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Diabetes Hotspots Mapping Using GIS tools to Target Quality Gaps CQI “Right Care” Initiative Nicole Lurie, M.D., MSPH & Allen Fremont, MD, PhD September 29, 2008

Diabetes Hotspots Mapping Using GIS tools to Target Quality Gaps CQI “Right Care” Initiative Nicole Lurie, M.D., MSPH & Allen Fremont, MD, PhD September

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Diabetes Hotspots Mapping Using GIS tools to Target Quality Gaps

CQI “Right Care” Initiative

Nicole Lurie, M.D., MSPH & Allen Fremont, MD, PhDSeptember 29, 2008

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National Health Plan Collaborative (NHPC)

• Public-private partnership to improve care quality, reduce disparities

• 11 plans, > 87 million members

• Technical support from RAND and CHCS

• Sponsored by AHRQ and RWJF

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What information about your member population & individual patients could help you serve them better?

(What tools would help you use that information?)

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Can use queries and filters to highlight areas of interest>66% not receiving LDL test & large # of diabetics in census tract

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Users can instantly access salient information by selecting or clicking on areas of interest

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Diagnosing a ‘hot spot’

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Diagnosing a ‘hot spot’

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Missouri Health Literacy Level by Tract

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St. Louis Health Literacy Level by Tract

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GIS Tools can help target potential opportunities for intervention

GIS Tools can help highlight “Hotspots” or areas with clusters of members with worse than expected rates

Diabetic Members with and without LDL Test

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Adding spatial perspective can increase understanding of contributing factors

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Adding spatial perspective can increase understanding of contributing factors

Limited English Proficiency

Inside Cluster: 43 %

Outside Cluster: 29 %

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Mapping tools can help provider groups see their performance patterns more clearly

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Mapping tools can help provider groups see their performance patterns more clearly

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Geospatial tools can help target medical outreach interventions to community

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GIS tools can also help coordinate efforts of local medical and public health providers

CommunityInterventionSites

Hot Spots

(Clinical)

Standardized rates of uncontrolled diabetes

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Conclusion

• Better understand the populations being served

• Identify local “hotspots”

• Assess local factors

• Recognize possibilities for shared action

Emerging mapping and decision tools can help target improvement interventions more efficiently

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