We face a paradoxical difficulty in the field of behavioral health when it comes to substance use disorder (SUD) and addiction. There is a huge gap in our understanding and agreement regarding how treatment and recovery from SUD / addiction works most effectively.
To compound the issue, there is little transparency in long term addiction recovery, with many patients unwilling to participate in data collection. Many times, this unwillingness is a product of anonymity which plays a key role in patients becoming willing to begin the process of treatment and recovery for SUD / addiction. The emphasis on anonymity as part of the recovery process is understandable from the patient’s perspective given the stigma surrounding addiction and SUD. However, lack of patient data makes finding common ground about effective addiction recovery, or developing a standardized set of protocols and procedures, exceedingly difficult.
We do know what happens to the brain when the chronic disease of addiction is active. The physical impact on the brain is visible and measurable. Here’s what we don’t know: how do people stay in long-term recovery and why? This question remains relevant because we don't have enough longitudinal outcomes data about how successful recovery occurs. However, it’s possible that by using outcomes data, data that covers the end result of a health care systems effect on a population of people, we can begin to identify the factors that contribute to long-term recovery. Through this strategy we can begin to scratch the surface on the mysteries of successful addiction recovery, and hopefully move towards a standardized approach to treatment.
An argument for the use of outcomes data can be found in childhood cancer patients. At the beginning of the 1980s the rate of mortality for childhood cancer was at an all-time high.
Image Source: https://www.health.ny.gov/diseases/cancer/childhoo...
In the chart above, it’s clear that there was an incredible spike and then sudden decrease in childhood cancer mortality in New York between 1982 and 1985 -- this is especially apparent in Leukemia patients as indicated by the orange line. When looking at the causes for the spike in cancer diagnosis, there’s evidence to suggest the rate of cancer didn’t actually increase. Instead, the peak of cancer diagnoses can be attributed to the advancement of technologies such as magnetic resonance imaging (MRI). Better technologies lead to more and more accurate diagnosis.
While the detection and spike can only be speculated, the rapid decline in mortality rate does have a direct correlation and can be contributed to concerted efforts on behalf of the medical community. A consortium, which was originally founded in the 1950s but expanded rapidly through the 1980s and into the 1990s, now known as the Children’s Oncology Group was dedicated to the research of childhood cancer treatments. In the late 1970s and early 1980s a number of treatment methodologies were being utilized including multiple forms of chemotherapy, radiotherapy, bone marrow transplants, antibiotics, and blood transfusions. Medical practitioners would study the outcomes of these treatments, adopt the most effective methods, then compare those methods against new and emerging treatments and continue that cycle so only the most effective methods survived.
It’s no coincidence that interest began to peak in the long-term health of the survivors. This cancer treatment methodology was so effective in reducing the mortality of childhood cancer patients that it lead to the development of research initiatives like the Childhood Cancer Research Study, which continues to study the survivors of these treatments to this day.
This method implemented in childhood cancer can be applied to other fields of medical study including SUD / addiction recovery. It is important to note that addiction recovery doesn’t have outcomes that are as measurable as the treatment of childhood cancers, and it is altogether a different kind of disease. However, it’s clear in the example above, given the correlation of improved outcomes data and cancer mortality rates declining, that as a community we would greatly benefit in making a coordinated effort in discovering standardized and effective ways to treat addiction and SUD patients.
One way we can begin to work towards more standardized approaches to diagnose and treat those who suffer is to look at demographic differences leading to addiction and relapse: gender, age, socioeconomic background, drug of choice, presence of trauma, veteran status, and family dynamics to name a few. Such demographic variables could prove useful in determining the kind of recovery pathway a patient should take.
If the addiction recovery community and all parties involved in the treatment spectrum were to come together and collect meaningful outcomes data, that had an adherence to certain treatment protocols as well as long-term recovery support like other chronic diseases, it’s possible we could see an increase in those maintaining long term recovery and a decrease in mortality from addiction relapse.
The data collected on childhood cancer mortality spanned several decades and took the coordination of multiple institutions. Needless to say, it wasn’t an easy task. Collecting data on addiction recovery may be even harder. Where the signs of cancer relapse and remission are easy to detect, the same is not true in addiction recovery.
Addiction itself carries a lot of stigma in our society. Many who suffer from the disease of addiction do not want to directly participate in clinical research for the fear of judgement, being ostracized, or being belittled for their disease. Addiction recovery is typically an anonymous pursuit and those who suffer from addiction are often not as forthcoming as those who suffer from other chronic illnesses.
It’s also important to understand that not everybody who suffers from addiction has the same severity of disease. Back to the cancer analogy: an individual with stage one breast cancer is going to be treated differently than an individual with stage four breast cancer. To take it one step further: a child with leukemia isn’t going to be treated the same way as an adult with pancreatic cancer. If that same distinction is applied to addiction as a chronic brain disease, then not all people that suffer from the disease would be classified with the same disease severity as they are now.
The Twelve-step program is probably the most widely known form of addiction recovery, and the easiest way to illustrate the disparity in individuals in recovery who have seemingly similar addictions. Consider these two scenarios:
Individual A begins attending twelve step meetings. They go through the twelve steps with a sponsor, they begin to sponsor other people in recovery, and they maintain an active role in the recovery community -- because of their continued effort in recovery and their new connections they maintain a healthy lifestyle and do not relapse.
Individual B wholeheartedly goes into treatment. They begin attending meetings while in treatment and continue on afterward. They work through the twelve steps with a sponsor, and they have service positions at the meetings they attend. However, within the first 2-3 years of recovery they relapse, overdose, and die.
What is the difference between these two people? What information are we missing? Why did recovery work for Individual A but not Individual B? They both had a similar experience in recovery, yet the severity of Individual B’s disease was such that they died from their addiction. Presently, the conclusion of most people would be that the severity of their addiction was too progressed for typical recovery treatment methods to be effective. But, if this were almost any other disease this huge gap in important information would never be acceptable.
Unfortunately, there isn’t a standard of measurement for the severity of addiction that could be applied to these two individuals in a measurable way. The closest applicable standard is in the American Society of Addiction Medicine’s (ASAM) levels of care. However, the flaw in using the ASAM criteria is that it is simply a placement criteria for determining the degree of medical management the patient needs. The ASAM criteria doesn’t address the severity or the underlying causes of their addiction. This is a huge problem.
That begs the question: What kind of standardized treatment plans can be employed in addiction recovery when there is also an emphasis on providing “individualized” treatment?
As we said before, there are a lot of unknown factors in the field of addiction recovery, and the efficacy of different treatments models is one of them. Since there are no clear indicators of what can guarantee a full recovery from addiction, there are also no clear indicators of effective recovery methods.
With a lack of data to support the efficacy of one treatment plan over another, most treatment providers employ therapy modalities based on clinical judgement and preference. There are numerous modalities that are specialized and have potential benefits: yoga therapy, meditation and mindfulness, music therapy, equine-assisted therapy, outdoor adventure therapy, art therapy, spa therapy, etc. However, very few have the research data to support the long-term efficacy of their particular modality. And, while they may be a preferred method for the provider, there are simply patients who do not react positively to certain types of therapies.
For instance, we know that people that adhere to a twelve step model have a statistical advantage in long-term abstinence, and that going to recovery meetings is incredibly important to a long-term recovery journey. But, the simple fact is, not everyone wants to go to twelve step meetings.
This complexity of addiction treatment is reflected in the national dialogue, and even finds itself in the National Institute on Drug Abuse (NIDA) in their principles of drug addiction treatment. Even their own principles are broad, and are a reflection of the addiction treatment landscape as a whole. From the top down, it makes sense that we are still far away from a standardized approach to addiction treatment.
MAP's goal is to develop positive outcomes for patients so that recovery pathways can be truly individualized and adapted based on relevant outcome data in an effort to provide a more effective approach to addiction treatment for all people who suffer from this terrible chronic disease.
Unfortunately, what the addiction and treatment industry does right now, in terms of addiction treatment, is declare they provide “individualized” treatment plans; however, in their current state, “individualized” treatment plans, with only a small degree of exceptions and variations, look pretty much the same for everyone. Utilizing comprehensive outcomes data on addiction treatment allows us to stop this “fake it ‘til you make it” mentality, and begin providing more effective and measurable results across the care continuum.