Tackling Opioid Abuse Through Big Data Analytics

Healthcare and big data are advancing towards a stage where they can operate hand-in-hand. Healthcare analytics have the potential to reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life in general. Opioid abuse is a serious problem in the US and big data analytics is helping to tackle it.


If we go by the facts, overdoses from misused opioids caused more accidental deaths in the U.S. than road accidents in 2017, which were previously the most common cause of accidental death. In Canada, the situation has gotten so dire that it has declared opioid abuse to be a national health crisis. Last year, POTUS earmarked $1.1 billion dollars for developing solutions to the issue.

And how is big data analytics helping the cause? Data scientists at Blue Cross Blue Shield have started working with big data experts at Fuzzy Logix to tackle the problem. Fuzzy Logix analysts have been able to identify 742 risk factors using years of insurance and pharmacy data that predict with a high degree of accuracy whether someone is at risk for abusing opioids. This issue is destroying the lives of many people and costing the healthcare system a lot of money. In all honesty, reaching out to people identified as “high risk” and preventing them from developing a drug issue is a delicate undertaking, but this project still offers a lot of hope towards mitigating the issue.

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