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Using analytics software to comb data, health officials expected to find seniors most often overheating during the summer months. They were wrong.
Arizona summers mean temperatures of more than 115 degrees, and that puts residents working outside or lacking air conditioning at greater risk for heat-related illness.
This summer, Pinal County is taking software that automates disease surveillance and using it to surveil heat-related illness for the first time.
Previously, the county, located southeast of Phoenix, has farmed its mortality database for deaths using keywords related to heat, extracted those and placed them in Microsoft Excel in a limited attempt to make sense of the information. But adding the analytics software, built by Cary, North Carolina-based SAS, to the equation to match that data with hospital discharge data in real time is a game changer.
“Is heat stress morbidity occurring at a certain temperature or time of year to a particular age group or sex?” Graham Briggs, Pinal County disease investigation program administrator, said in an interview. “We can characterize who’s getting sick related to heat in our county, and we couldn’t do that without SAS.”
A disease like Zika might first crop up with a patient’s rash, and that person’s travel history would be looked at to see if there’s a differential. Medical codes in discharge data reveal heat stress morbidity, but five year’s worth of data constituted millions of lines with multiple columns—best left to software.
While the county is still early in the process, the number of heat-related hospital visits appears to increase as summer progresses, Briggs said, and interestingly it’s not seniors but the young who appear most at risk.
Occupational-related heat illness might be more common than we expected,” he said. "It’s not a 70-year-old going grocery shopping around 1:15 p.m.; it might be a 25-year-old doing construction work around 1:15 p.m.”
The county will need to dig deeper into that population to understand their risk, whether it’s occupational or recreational.
From there, it could be a matter of reminding people to make water available and seek shade or working with construction companies so they’re starting work at 4 or 5 a.m. so they’re off by 2 p.m.
“Ideas can come about how to minimize heat-related illness, if we can characterize that population,” Briggs said.
Severe disease data anomalies are easy to spot because the people who have them are so sick they wind up in a hospital and the health department is called in. Less severe diseases, like those that are food-related, can be more insidious because patients are more likely to stay bedridden.
With heat illness, historical data is compared to real-time data for statistically significant differences.
Pinal County isn’t just innovating in terms of the illnesses it surveils though.
The county has a full-time employee working on tuberculosis case management because the disease is so complex. A single case requires six months of work compared to infections like STDs, which only require the case manager to find the patient's contacts once they’ve tested positive.
TB involves multiple types of lab tests repeatedly, a contact investigation and medication delivery that must be witnessed daily.
“How do you balance your time between a contact investigation of who’s at risk and, at the same time, visiting other people who need medications?” Briggs said. “And you have to watch them take those medications.”
Fortunately, the TB case manager could write code and used the SAS software to better manage his time, Briggs said, creating a time management report generator.
Briggs, an epidemiologist for 15 years, has seen SAS and GIS revolutionize how he looks at information and expects that trend to continue to where coding skills are not as necessary.
“These tools allow us to manage and analyze large datasets,” he said. “I see them becoming more user-friendly and more easy to use so we can get where we want to go easier than we do right now.”
Dave Nyczepir is a News Editor at Government Executive's Route Fifty based in Washington D.C.
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