2018 Academy Health Annual Research Meeting Poster
The Design of a Neighborhood Level Community Health Needs Assessment Map Tool
for Non-Profit Hospitals
Evan Copello, MSc1, Jason Smith2, Anna Mease BSc3, Karthikeyan Umapathy, PhD2, Dan Richard, PhD1, Ann-Marie Knight, MHA, FACHE4, Monica Albertie4, MHA, Emma Apatu, DrPH2
1Department of Psychology, 2School of Computing, 3Department of Public Health, University of North Florida, Jacksonville, FL, 32224
4Mayo Clinic, Jacksonville, FL, 32224
To describe the methodology that was used to develop a
neighborhood-level dashboard data tool that can assist non-
profit hospitals identify priority neighborhoods as a way to
focus community health outreach efforts. Data were used to
create a tool with two separate dashboards. The first is a
composite dashboard and the second is a comparison
dashboard. For analysis we standardized each variable by
use of SPSS software. Once standardized, a weighted
composite score was created and input into a Tableau map.
This particular iteration of the map was developed
specifically for Mayo Clinic in Jacksonville Florida to assess
health needs in the area. However, this type of data tool can
be developed for the remaining 499 cities in the 500 Cities
Project and updated as necessary to ensure the most
current data is available. Neighborhood level data is not
available in most cities. This data tool proved to be a useful
tool for visualizing target neighborhoods for community
health outreach within Jacksonville, FL.
• The completed tool has two dashboards, a composite and a comparison.
• Shading is used in both dashboards to distinguish between health outcome
severity with darker shading representing higher composite scores or worse
• Each dashboard contains different additional features including:
• City base maps
• Google Street View™
• A list of available resources
Data were collected from:
• The 500 Cities Project (Center for Disease Control
and Prevention (CDC))
• The University of Florida GeoPlan CenterTableau
• Florida Department of Environmental Protection
• City of Jacksonville Property Appraiser
The map was built using geographical data layered into
Tableau. Google Code™ Application Programming
Health outcome variables were identified by both Mayo
Clinic and CHNA data.
• Coronary Heart Disease
• This tool provides neighborhood level community health
data was previously not available for the Jacksonville,
• This tool serves as a snapshot of a particular point in time
and would need to updated periodically as more current
data is released.
• This dashboard provides a more localized understanding
of Jacksonville neighborhoods and details current health
outcomes and resources.
• Knowing which resources are available within a census
tract helps health workers know what support they may
have within an area and what they need to focus on
• This tool provides a faster approach to identifying target
communities and is based solely on health data,
removing a lot of the subjectivity humans bring to
• This dashboard can be updated with new census data
each year providing consistency in available health data
and the opportunity to track progress within an area.
• This tool proved to be useful for Mayo Clinics Wellness Rx
program and overall fills a void for available
neighborhood level data in the Jacksonville area.
• This tool is publicly available and may be used by other
non-profit hospitals and health organizations in the
Public Health Implications
• The 2010 ACA implemented stricter criteria for nonprofit
hospitals to acquire and maintain a tax exemption status.
• Nonprofit hospitals must provide evidence that they are
addressing these needs within the target community.
• Conducting a needs assessment requires both
quantitative and qualitative data at various population
• State, city, and county data sources are more often
available, but neighborhood level data is not.
• To meet CHNA and ACA requirements and address
neighborhood health needs Mayo Clinic in Jacksonville
partnered with The University of North Florida (UNF)
Data Social Science for Good (DSSG) to create a data tool
for their Wellness RX program which currently works in
the New Town Success Zone.
• Our objective is to display the neighborhood level data
tool that was created for this partnership and describe
the various aspects of this tool, the public health
implications, and methodology so that other
organizations may create a similar tool.
Figure 1. College Gardens Composite and Outcomes Map Figure 2. College Gardens Street View and Resources
Scan the QR code to access the
dashboard tool. More information
can also be found on the DSSG
QR Code to Dashboard
• Poor Mental health
• No Dental Visit in the Past Year
These six health variables where used to create the
To create the composite scores data were:
• Standardized: equal comparison between variables
• Rescaled: z-scores were used to create a 0-10 range
• Weighted: variables were weighted according to
Mayo and CHNA importance
Variables Correlation Equation Weight
Diabetes .970 .970/5.145 18.85%
Stroke .948 .948/5.145 18.43%
Heart Disease .929 .929/5.145 18.06%
Obesity .867 .867/5.145 16.85%
Dental .748 .748/5.145 14.54%
Mental Health .683 .683/5.145 13.28%
Total 5.145 100%