The U.S. opioid crisis is evident to anyone who follows the news. Roughly 130 people die every day in this country as a result of abusing opioids, and roughly 80% of those who use heroin began by abusing prescription opioids. So what do we do about it?
It is easy to lay the blame for the current crisis at the feet of medical professionals who prescribe opioids. But such singular blame neither helps us find solutions nor addresses the broader issue of substance abuse. We need to deal with the opioid crisis at a much more fundamental level, beginning with trying to learn as much as we can about trends, patterns, and possible risks.
To that end, some have suggested that big data has a significant role to play in halting the opioid crisis. Rock West Solutions, a California company that provides big data services and solutions to the healthcare sector, would agree. They see big data and its potential as having a huge role in figuring out the roots of opioid addiction – at least from a data standpoint – and mitigating future problems through predictive analytics.
Combining Healthcare and Public Data
A February 2019 article from MedCity News contributor Richard Grape seems to imply that a good place to start is finding ways to combine data from both healthcare sector and public records. According to Grape, analyzing data from both sources is a “critical lens that is often missed” by those people trying to understand the opioid problem.
Grape asserts that data from non-healthcare public records is valuable in that it offers insights into a variety of things that could contribute to opioid misuse. He says public record data can reveal at-risk entities, certain kinds of predictive behavior, and connections between the two.
Combining that sort of data with healthcare records can give researchers a better handle on the history of opioid abuse on an individual basis. Collectively, it can help researchers track trends among groups of people, geographic regions, and so forth.
Utilizing Predictive Analytics
Once combined data has been compiled and analyzed, it is on to predictive analytics. This is one particular area that Rock West Solutions specializes in. They design systems capable of extracting valuable data and using it for analytical purposes.
Imagine being able to recognize patterns and trends among opioid abusers. Imagine being able to compare that data with risk assessment data. You could then predict a variety of precursors to opioid abuse. Successfully identifying those precursors would theoretically make it possible to prevent opioid abuse before it ever starts.
This is exactly what Grape describes in his article. He describes a scenario in which big data and predictive analytics are put to use in such a way as to prevent opioid addiction from occurring. Stop the problem from happening and you don’t have to clean up a mess that is never made.
Prescription Opioid Use
A good place to start would be taking a look at prescription opioids. Given how many heroin users start with prescription opioids, we already know that these powerful painkillers used to treat people following surgeries, serious injuries, etc. are a contributing factor to the opioid crisis in and of themselves.
As a known entity, prescription volumes would give us a good handle of how often the drugs are used in America. Then we could take that information in a variety of directions depending on what big data and predictive analytics tell us. There is no telling where it will take us, but we at least have to make the journey if we intend to find out.