How Public Health Informatics Can Be Used to Treat Drug Addiction

Researchers use big data analytics to find opportunities to help alleviate drug addiction amid the U.S. opioid crisis.

Since 2004, deaths due to opioid abuse have more than doubled, according to a U.S. Surgeon General advisory. Says the report, an alarming and rapidly rising percentage of the population is mixing both authentic and counterfeit sedatives with a range of illegal controlled dangerous substances, resulting in unpredictable – and often fatal – outcomes.

According to the Substance Abuse and Mental Health Services Administration (SAMHSA), more than 11 million American citizens over the age of 12 abused opioids in 2018. Across the nation, information gathered from various prescription drug monitoring programs (PDMPs) has revealed that the characteristics of opioids directly contribute to addiction.

Can Data Help to Mitigate the Opioid Crisis?

Data reveals unsettling trends. For instance, over 90% of drug addicts have consumed drugs or alcohol before the age of 18, and more than 20 million Americans over the age of 12 suffer from some form of addiction.

To help these individuals, researchers can use information gathered from public health informatics to create personalized therapeutic strategies, rather than relying on one-size-fits-all treatment plans. The ability to use data to create customized treatments can produce considerably positive outcomes for people struggling with addiction. By encouraging patients to share anonymous data, physicians can contribute to studies that will lead to more efficient treatment for drug addiction.

Data-informed drug interventions can produce consistently positive treatment outcomes. This information can even help addicts who do not reach out for assistance.

By using informatics to inform addiction treatment, physicians can deliver and improve the level of overall care. Furthermore, personalized, data-informed treatment can make addicts feel like they have more control over the recovery process. With the prospect of an improved sense of control, it’s more likely that additional people will reach out for help.

The Search for Answers

Public health informatics systems can provide officials with the information needed to identify groups who face the highest addiction related risks. As an example, data-informed research suggests that prenatal exposure to opioids is an area of heightened concern.

There are effective treatments for opioid addiction. However, only a little under 30% of addicts seek treatment.

This disparity is not unique to opioid abusers. Researchers estimate that only a little over 12% of individuals who suffer from addiction seek treatment.

Furthermore, nearly 50% of people who struggle with addiction also have a mental health disorder. Only about half of individuals whom physicians diagnose with a mental health disorder seek help for either that condition or substance abuse, and only a small fraction seek treatment for both addiction and emotional disorders.

Data-informed intervention can help physicians conform to the highest standards of addiction treatment and prevention. For instance, information gathered from state Prescription Drug Monitoring Programs (PDMPs) can help physicians avoid overprescribing opioids.

Data can also help physicians develop improved evidence-backed interventions and treatments. It’s also a highly useful tool for promoting the awareness of public health issues such as the opioid epidemic. Most importantly, however, data is the foundation on which researchers build solutions for solving society’s worst social ills.

A Data Success Story for Veterans

The REACH VET program is a data success story. The program has helped officials curb violence, overdoses and opioid abuse among American veterans.

So far, the program has helped more than 30,000 United States veterans. By engaging with the program, participating veterans have experienced fewer admissions to mental health facilities, increased visits to the local VA and improved participation in recommended interventions.

This positive outcome is significant, as many veterans who are struggling with either emotional or physical health problems fail to follow through with scheduled medical appointments. By examining the behavior of veterans using data analysis, REACH VET personnel have successfully discovered insights that have led to life-saving interventions.

The REACH VET program obtains its data from the vast store of health information maintained by the Veterans Administration. By using predictive analytics, the program identifies potentially at-risk veterans.

By examining historical data, REACH VET researchers forecast the future behavior of program participants. The scientists deploy techniques such as analytical queries, automated machine learning algorithms and statistical analysis. Using these advanced techniques, REACH VET researchers create highly accurate probability models that identify veterans who are at risk.

For addicts who fail to seek assistance, data analytics can help healthcare professionals develop mediation strategies that reach those who are unwilling or unable to seek treatment. Such personalized intervention helps to improve the quality of life for individuals who are the most at risk.

By leveraging an abundance of health informatics data, treatment providers can return a sense of control to recovery candidates while helping them to heal.

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