Despite their strong pain-relieving properties, opioids have become a scourge on society in recent years. Opioids, the class of drugs either naturally or synthetically derived from the opium poppy, bind to the body’s opioid receptors in order to relieve pain. And they’re one the world’s most highly addictive substances.
As early as 2014, the misuse of opioids reached epidemic proportions in the United States. That year, more than 28,000 people died from an overdose of either heroin or prescription opioids. A further 2 million Americans abuse or are dependent on prescription opioids, according to Recovery Centers of America. These numbers and similar data may hold the key to finding tangible solutions to the opioid epidemic.
Our understanding of opioid abuse, as well as its causes and effects, is partially informed by data analysis. Using relevant public health information, data analysis can pinpoint opioid use trends and patterns. Via the objective analysis of opioid-related data, potential large-scale treatment methods may also begin to emerge. In this way, data analytics is among the myriad modern technological innovations helping to foster change on a global scale, improving our lives and overall public health.
Opioid Data Analysis: What We Know
On the opioid front, data analysis is an integral avenue of research for scientists at the Centers for Disease Control’s Injury Center. Using data, CDC researchers have determined that America’s opioid epidemic occurred in three distinct waves. The most recent of these waves involves an influx of synthetic opioids, most notably fentanyl, and began in about 2013. Fentanyl’s inherent dangers lie in its potency and the fact that it can be easily (although illegally) manufactured.
To better identify and develop an understanding of opioid-related trends, such as the influx of fentanyl use in recent years, accurate data collection is key. The next step in the process involves data analysis by qualified researchers and scientists. Once those professionals have effectively analyzed the available data on opioid use, the next step is to look for workable solutions to the epidemic. These solutions may involve various forms of therapy and/or ensuring hassle-free, community-wide access to overdose-reversing drugs such as Naloxone.
Yet Naloxone and similar drugs should only be used as a last resort, and there are a number of medications on the market that have shown promise in treating opioid dependence. Among the most common of these medications is suboxone, a brand name drug that contains both buprenorphine and naloxone. Suboxone is available in four strengths, encouraging patients to wean off opioids in a gradual, more natural manner.
However, as suboxone is a Schedule III controlled substance, it may not be the appropriate treatment for every patient. Fortunately, research on opioid dependency treatment is a near-constant endeavor as the national crisis persists. Data indicates that a compound known as AT-121 shows promise in treating both opioid dependency and the addicted patient’s underlying chronic pain. While more research is needed, AT-121 seems to target the nociceptin opioid receptor, providing effective pain relief while virtually eliminating the abuse potential of opioids.
The Role of Public Health Informatics in Addiction Treatment
The data from AT-121 efficacy tests may bring us closer to a concrete understanding of the disease of addiction. More than 20 million Americans over the age of 12 are addicted to some type of mind-altering substance, from alcohol to opioids, both illicit and prescription forms, reports the University of Illinois at Chicago. As a significant percentage of people are directly and indirectly affected by substance abuse and addiction, delivering highly targeted care is paramount to treatment.
Enter public health informatics, a concept that merges technology-driven data analysis with existing public health records and research. While promising on the surface, as data analysis can better detect patterns and solutions than its human counterparts, road bumps do exist within the methodology. For instance, the individual viability of health informatics hinges on patient honesty.
If patients are not forthcoming about their past opioid misuse or any aspect of their personal health history, developing a patient-centered treatment plan is virtually impossible. Unfortunately, for many opioid addicts, being dishonest comes with the territory. The behavior may stem from the addict’s personal negative perception of addiction or the idea that they are somehow weak because they cannot stop abusing their drug of choice.
Among addicts, dishonesty may be rooted in another cause altogether. Whatever the case may be, it’s important that data analytics takes dishonesty into account. Verifiable action must become the new form of trust among healthcare professionals who are helping addicts and collecting relevant data.
Can Data Help Curb Opioid Misuse?
So based on what we know about the deadly nature of opioid abuse and its prevalence across America, can data truly provide an operable solution? Signs point to yes, especially considering that we have so much data at our disposal. What’s more, the emerging Internet of Things (IoT) allows us to input and interpret variables that may be affecting data on opioid abuse, such as the propensity of addicts to hide their addictive behavior.
Data analysis can also help us fine-tune the information collected at various facilities, from emergency departments to inpatient treatment centers. This analytical tool can break down opioid overdose deaths into usable data based on location, patient age, and particular substance. From there, we’re better able to see patterns as they emerge, and stop them in their tracks, effectively making the world a better place. In this way, data analytics is integral to our continued understanding of opioid abuse and successful treatment methods.
