From EfficientGov. Full article.
by Andrea Fox
To fight the opioid epidemic, the HHS opioid code-a-thon produced opioid apps that present first responders, law enforcement and physicians with new hope.
After 24 straight hours of development, a half-dozen finalist teams — out of more than 50 — presented their opioid apps on December 7th at the finale of the U.S. Health & Human Services (HHS) Opioid Code-a-Thon. Kevin Merritt, founder and chief executive officer of Socrata, spoke as judges made their final decisions on which teams would win the three $10,000 prizes, highlighting the city of Cincinnati’s data set — the sole local government developed data set of the more than 70 data sets HHS prepared for the event.
Dayton, Ohio, is currently the most severe epicenter of opioid morbidity, Merritt noted, but Cincinnati, just 45 minutes away, had also found itself hard hit. “The city turned to data with amazing results,” he said. Cincinnati’s “heroin dashboard” has been a chief tool in the city’s ability to fight back the opioid epidemic. One change, Merritt noted, is the city’s ambulances are re-positioned in order to save lives much faster.
HHS in preparing the massive data trove — including previously unavailable data sets — is setting the national stage to ignite data-driven opioid apps like Cincinnati’s in order to best the opioid threat on three fronts — prevention, usage and treatment.
“This is the first time we have done something of this scale,” said Mona Siddiqui, HHS chief data officer said.
Bruce Greenstein, HHS Chief Technology Officer, said that the University of Louisiana at Lafayette will be hosting the next opioid code-a-thon using the HHS opioid data trove on April 13-14th, 2018. The teams that created the code-a-thon’s winning opioid apps, as well as others, have the opportunity to apply for HHS funding to get their innovations to market and into the hands of local and state governments that need the insights the most.
Opioid Prevention Track Winner Focused on Drug Take Back Mapping
The team from Visionist, Inc., of Columbia, Maryland, including presenter Taylor Corbett, used Centers for Disease Control (CDC) data along with data from Walgreens, CVS and other private drug drop companies, to reduce those at-risk for opioid abuse from getting the drugs in the first place.
More than 70 percent of opioid users start by getting opioid medications and substances from their families, said Corbett.
While the tool can be scaled nationally, in less than 24 hours the team created a five-state regional platform that displays a risk index for potential opioid abuse. The “Takeback America” tool provides visualizations of hard hit counties and the availability of drug take-back programs.
By revealing which hard hit areas have low availability of take back programs, public health decision makers can focus resources where they are needed to increase participation and availability.
Also presenting was the finalist team Protecting the Next Generation of Ryan Haight, who died from purchasing Vicadin online and became the namesake for 2008 legislation that “prohibits the delivery, distribution or dispensing of a controlled substance that is a prescription drug over the Internet without a valid prescription,” according to Govtrack.us.
Tim Mackey of University of California San Diego School of Medicine, speaking for the team, said they applied machine learning to find opioids for sale on social media. Their tool analyzed 120 tweets made between November 15th and December 5th, finding 40 online pharmacies — and their locations — willing to sell opioid drugs without a prescription. The team used U.S. Food and Drug Administration, Drug Enforcement Agency, mortality and census data sets in ArcGIS, automating epidemiological surveillance in real-time. Law enforcement can query date ranges and keywords to detect, analyze and score the online pharmacies, Mackey said.
A third finalist team in opioid apps for prevention was from the University of North Carolina. This team created a patient-facing tool using Carolina Data Warehouse for Health data called the tHOR app. The goal of the tool is to provide patients with a more robust opioid risk assessment.