America’s Other Healthcare Crisis Hasn’t Gone Away: How Technology is Combatting the Opioid Epidemic

Technology Changes the Clinical and Value Understanding of Opioids during Pandemic Crisis

Prior to the COVID-19 pandemic, U.S. healthcare participants, throughout both the clinical and value chains, were wrestling with the opioid epidemic. This continuing crisis, rooted in overprescribing legal pain medications, quickly spilled over into illegal and illicit drug use.

The overwhelming majority of overdose deaths are opioid-related. Now, approximately 25% of patients prescribed pain medication for long-term pain relief struggle with addiction and those addicted are 40 times more likely to become heroin users.

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The COVID pandemic has made the already concerning situations exponentially worse, even as attention legitimately shifted to COVID. As of October 6, 2020, the AMA’s Advocacy Resource Center reported: “More than 40 states have reported increases in opioid-related mortality as well as ongoing concerns for those with a mental illness or substance use disorder.” Social isolation, job loss, and disruption of treatment are possible factors. This analysis is only partial as nationwide data is currently unavailable.

In the very near future words like “possible” and “partial” will go away – because of advanced technology that allows for analytics using artificial intelligence (AI) – not just for opioids, but extended to all disease states.

Across the value chain in healthcare as well as from a continuum of care perspective, firms are taking a number of approaches to address the opioid situation – now seen as a subset of the addictive disease state. Many of these firms are emerging, garnering significant interest on the part of strategic and financial investors.

From dispensing control at the patient level to cognitive-behavioral apps that support recovery, technologies are being used and will soon be ubiquitous. These technologies are derived from industries such as financial services and advanced predictive analytics platforms, designed to comprehensively analyze, interpret, and predict potential outcomes across a variety of critical metrics are now being deployed by hospital systems.

Taken together, these approaches give guidance on the scope of the crisis, potential underlying causes, track and monitor behavior throughout the healthcare system, and can help mitigate the effects through broad and deep understanding. They answer two critical questions for participants: what should we do; and, what shouldn’t we do?

These analytics platforms are based on AI and as a result they:

• aid in health detection/ tracking,
• provide insight into health outcomes, and
• ultimately determine critical interventions when it comes to identifying social health determinants.

Where Do We Go from Here with Opioid Crisis?

Until the delivery of technology to underscore precisely what is occurring in the opioid crisis, only partial, and a largely clinical picture, focused primarily on therapeutics alone, has been available to doctors, healthcare systems, even payers.

By using large data sets, a 360-degree view is now available, addressing the crisis both therapeutically and from ma cost/economic perspective. Among other metrics, how opioids are being prescribed, by whom, for what disease states, and when, can inform practice and behavior moving forward both for individual doctors and health systems in the aggregate.

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Other derived data can be used for social, risk, and business purposes.

Simply put: clinicians and healthcare providers will not have to wait to address the opioid situation after someone becomes addicted because they will have a better handle at the outset as to whether opioids are indicated and what outcome, given very specific situations, can be expected.

Present at the Creation

Applying advanced analytics is likely to increasingly become the norm across disease states. What works for opioids is extensible to other pharmaceuticals, and applicable to disease states themselves – COVID is an example.

The fact is that these methods are just that – the underlying algorithms in use can be applied with equal effect throughout virtually every point in the healthcare system. The result will be a greater understanding of each particular situation, and measurement of effectiveness, which ultimately can be aggregated to understand clinical practice, economics, and risk as a whole.

This will take time, as conversion to new methods, especially across an entire enterprise or industry means the adoption not only of a new technology but a new mindset and culture in the industry itself. However, the benefits that accrue at will outweigh any difficulties in migrating to these platforms.

It wasn’t so long ago, for instance, that stock trading was done in fractions, not decimals, via paper trading and phone. That simply no longer exists anywhere in the world as the entire financial services industry has moved to electronics (and, routinely uses predictive analytics as “no big deal”). The therapeutic and value benefits of predictive as opposed to reactive medicine will circumvent some disease states, allow for earlier interventions, increase value productivity, and reduce costs – all on a continuous, rolling basis from a platform technology as opposed to “point in time” or even worse, “rearview mirror” measure. Eventually, these technologies will aid in precision medicine as well.

Every single participant in healthcare, most importantly patients, will win.