Arizona Department of Health Services
Making data presentation meaningful when dealing with low rates of population density
The Arizona Department of Health Services (ADHS) promotes and protects the health of Arizona’s children and adults. Its mission is to set the standard for personal and community health through direct care, science, public policy, and leadership.
The Department operates programs in behavioral health, disease prevention and control, health promotion, community public health, environmental health, maternal and child health, emergency preparedness and regulation of childcare and assisted living centers, nursing homes, hospitals, other health care providers and emergency services.
When it comes to collecting and disseminating information, population density plays a large part in how the Department is able to highlight significant trends in the program areas and fulfil its role in terms of community profiling. For instance, 60 per cent of the population lives in one county which means that other counties are sparsely populated – presenting a significant challenge for any organization that wants to show detailed analysis at anything below county level.
This issue was of concern when it came to monitoring cancer rates. Until recently, the state-collected cancer data was not complete enough to look at rates on a relatively small geographic scale, limiting analysis to the county level only.
We spoke to Wesley Korteum, GIS Coordinator at Arizona Department of Health Services to find out more about how the Department now presents its data. He says that the graphical depiction of information about communities is an important element of their work and they have managed to overcome the challenge by creating their own Community Health Analysis Area (CHAA). There are 126 CHAAs in Arizona. Each is a geographic unit developed to present data (initially rates of cancer) at a geographic scale smaller than the county level.
A CHAA is built from US 2000 Census Block Groups. These Block Groups are relatively small geographic regions of the state. A typical CHAA contains approximately 21,500 residents. But, because of the scattered pattern of development in Arizona they range widely in population, from 5,000 to 190,000 persons.
“We have a team that has lived here most of their lives and recognised appropriate ways to aggregate Block Groups to create CHAAs that align with political and social boundaries. Each CHAA is made of different Block Groups and we try to keep areas as demographically similar as possible,” says Wesley.
The first project was to present the cancer data. The team felt that by having this data presented in a visually meaningful way it would put an end to the ad hoc requests for custom analysis they were getting. They began the search for a dynamic data presentation tool with outputs that could be shared with non-GIS professionals such as researchers and the public. Having decided to use InstantAtlas cancer data was geo-coded and the dynamic reports created. Wesley believes that presenting the data in this way has made it more meaningful and it has changed the nature of the team’s work.
Meeting the need
The cancer reports have just been made available to the public and Wesley is excited by the potential particularly because it could lead to other developments in community profiling. He and the team have already started making a few changes to ensure that it appeals to as wide an audience as possible. It effectively means that individuals who may have concerns about cancer in their locality can check out comparative rates in other CHAAs using the reports.
Wesley says that other partner organisations have started to take notice. Well Woman is one organization which intends to use the information to help it make grant applications for work with particular cancers. Other Department programmes have also expressed an interest in the way the data is presented with a view to adopting the same approach. For example Health Systems Development is interested in presenting data about health professional shortage in certain areas. The BRFSS team is also keen to use the same approach.
As for developments with respect to cancer rates, the team is hoping to look specifically at urban or rural areas and then to be able to start filtering for certain other factors such as economic deprivation.
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