BIG DATA REVEALS 1 OUT OF 6 ER VISITS IN Q2 2017 OPIOID RELATED
OM1 launches a prototype for tracking the public health crisis in near real time
BOSTON, November 27, 2017 — OM1, a leading AI health outcomes and data company focused on making healthcare more measured, precise and pre-emptive, today announced it has developed a prototype, using big data analytics, for tracking the opioid public health crisis in near real-time.
The OM1 opioid tracker leverages the OM1 Intelligent Data Cloud, which houses the largest, most extensively linked, clinically deep, representative and continually updated sets of healthcare information from the United States healthcare system. Data is assessed on a number of parameters including opioid-related emergency room (ER) visits and a range of important geographic, medical and other factors.
As most patients with symptoms of poisoning are transported to the ER for medical evaluation, this serves as an ideal screening portal to assess the magnitude, trends and potential clusters of this epidemic. Key initial findings, based on data assessments, include:
• A sustained increase in opioid related ER visits since 2013; for example, in Q2 of 2017, 1 out of every 6 ER visits were opioid related
• While the rate of opioid related ER visits increased across all ages during this time, the opioid epidemic is disproportionately impacting younger individuals. The fastest growing age segment is the 0-19 year age group, where rates increased from 10% in 2013 to 16% in Q1 of 2017.
• The opioid epidemic is not an urban disease. While rates increased in all states, Montana is among a few states with the biggest changes in the proportion of opioid-related ER Visits since 2013.%.
“The opioid epidemic has reached alarming levels in the US, affecting the lives of millions of individuals and families. Big data analytics provide an enormous opportunity to be able to track and evaluate the crisis in near real time,” said Vandana Menon, Vice President of Research at OM1. “With this prototype, we are hoping to contribute invaluable data that allows researchers and the healthcare community to gain a deeper, more comprehensive understanding of the magnitude, trends and clusters that are being most affected.”