Tool Predicts Who Is Likely to Abuse Opioids Using Medical and Social
Palo Alto, CA (July 18, 2018) – Recent data from the CDC shows that overdose deaths from opioids have increased by more than five times in the last 20 years.In fact, two-thirds of all drug overdose deaths in 2016 were opioid-related. The CDC estimates the financial cost of opioid abuse at $78 billion annually, with over one-third of that amount going towards increased health care and substance abuse treatment costs.

These statistics and alarming increases in opioid abuse led HBI Solutions to build predictive algorithms on integrated clinical, administrative and social determinant data to help identify patients most at risk for opioid abuse. Powered by data from across the care continuum and HBI’s proven data science capabilities, the new model identifies individuals at risk for abusing opioids, assigns a risk score, and exposes the clinical, social and lifestyle factors driving that risk to help clinicians take action.

It couldn’t come at a better time, as the push for improved opioid prescribing methods and better population health management has led hospitals and health systems to increase their focus on social determinants of health and improve care for patients at risk for abusing opioids.

Traditionally providers have turned to standard prescription, dosage and monitoring practices. However, non-medical conditions and situations like housing status, income and even zip code can influence opioid abuse risk as much as some medical conditions and are leading the drive towards more patient-centered clinical practices.

HBI’s new model helps identify which patients in a certain population should be targeted for intervention and gives providers both clinical and non-clinical factors driving that risk. “We’ve known for some time that the collection and analysis of social determinant of health data is helpful in the identification of those at risk for any type of health event,” said HBI Solutions CEO, Eric Widen.

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