Map Details - Relative Differences in High Blood Pressure (HBP) Medication Adherence Among Medicaid Members, by County

Impact Statement

This map highlights the existence of major geographic disparities in blood pressure medication adherence, even within the Medicaid population.

This map was developed as a part of the GIS Capacity Building Project. Learn more about the project.

This map shows results of statistical significance testing of differences between county-level medication adherence rates for the combined 2015–2016 Michigan Medicaid population 18–64 years old. Berrien, Kalamazoo, Kent, Ingham, Wayne, Bay, Tuscola, Genesee, Saginaw, Shiawassee, and Ogemaw counties had statistically lower rates of medication adherence in comparison to all other counties. Washtenaw and Jackson counties and counties in the Traverse City area and the eastern Upper Peninsula had adherence rates comparable to all other counties. Genesee and Saginaw counties had the largest difference, with adherence rates 10 percent to 15.3 percent lower than all other counties.

Key Points

Major Findings

This map identifies counties that have statistically lower adherence to blood pressure medications in the Medicaid population, as well as the magnitude of the difference.

How the map will be used, or has been used

While also taking into consideration the average number of Medicaid members in each county (shown in the prior map), results will be used to prioritize the Michigan Department of Health and Human Services’ efforts to improve high blood pressure medication adherence.

ArcGIS, Excel, and SAS/SPSS

Michigan Medicaid Claims data; Michigan Open GIS data portal

Proportion of Days Covered calculations for each county; tests of statistical difference of county-level rates for each county relative to all other counties.

Adrian Zeh, Evaluation Specialist, Michigan Department of Health and Human Services

Adrian Zeh, Michigan Department of Health and Human Services; accessed from the Centers for Disease Control and Prevention’s Chronic Disease GIS Exchange.

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