2018 in Review: Impactful Literature on Pain & OpioidsExpertise | December 19, 2018
At axialHealthcare, our pain and opioid care solutions are based in and continually updated with the latest peer-reviewed evidence. In order to maintain the highest standards for our products, and the patient care they support, our experts sort through thousands of publications each year.
Adding more than 100 publications to our compendium this year, we’ve compiled a list of the most relevant and impactful pieces we read in 2018 below.
Medication for Opioid Use Disorder After Nonfatal Opioid Overdose and Association With Mortality: A cohort study
Recommended by Mathilde Granke, PhD, Senior Research Data Scientist
This study examines the association between medication-assisted treatment (MAT) and mortality after a nonfatal opioid overdose. Two major takeaways to support the importance of connecting patients with MAT through axialHealthcare’s Centers of Recovery Excellence:
- Buprenorphine medication was associated with reductions in all-cause and opioid-related mortality. The suboxone group had a 40% lower death rate after one year compared with those who did not receive any medication.
- Following opioid overdose, only 30% receive medication to treat addiction.
On the Moral Value of Pain and Opioids
Recommended by Katie Miller, PharmD, Principal, Clinical Product Development
This perspective piece highlights the importance of understanding appropriateness of treatment per patient. The author cautions against labeling treatments as good or bad; treating pain is much more complex. While axialHealthcare is already making an impact, there are so many exciting opportunities to improve this space.
Communicating about Opioids in Appalachia
Recommended by Lindsey Morris, PhD, Director of Data Science
When discussing the opioid epidemic in Appalachian communities, the public health impact is the most commonly reported concern of subject matter experts and community members. Participants in this focus group also cited increasing criminal activity, the collapse in the workforce, and lost opportunities for economic development as contributors to the corrosive effect of the opioid epidemic.
Opioid Prescribing Decreases After Learning of a Patient’s Fatal Overdose
Recommended by Amber Watson, PharmD, Clinical Pharmacist, Scientific Writer
Researchers found that clinicians who were notified of their patients’ fatal overdoses decreased opioid prescribing by ~10%, acknowledging that communicating important patient-level data can influence a clinician’s prescribing habits. axialHealthcare has the opportunity to refine and improve this approach by:
- Intervening prior to an overdose event or prior to an overdose event that results in death.
- Promoting appropriate, safe opioid prescribing rather than encouraging widespread opioid de-escalation.
Risks of Fatal Opioid Overdose during the First Year Following Nonfatal Overdose
Recommended by Brooke Defosse, PharmD, Director, Intellectual Property Enablement
This study found that adults treated for opioid overdose frequently have repeated opioid overdoses in the following year. These patients are also at high risk of fatal opioid overdose throughout this period, underscoring the importance of efforts to engage and maintain these high risk patients in evidence-based care.
Distributed Representations of Sentences and Documents
Recommended by Kevin Wilson, VP of Engineering
A semantic embedding is a natural language processing technique that maps words and phrases to a continuous vector space for numerical comparison. At axialHealthcare, we can represent a patient’s medical claims history as “phrases” of ICD (International Classification of Diseases) and NDC (National Drug Code) “words.”
Then, using semantic embedding we have the potential to form a foundational representation of the patients to begin to understand how they relate to one another, identify healthy/unhealthy patterns, and predict directional trends.
Developing an Opioid Use Disorder Treatment Cascade: A Review of Quality Measures
Recommended by Chad You, MD, Senior Research Data Scientist
Developing a cascade of care model for opioid use disorder (OUD) could quantify the current gaps in care processes for individuals with OUD and provide tools for goal setting, accountability, measurement of progress, identification of needed treatment resources, and increases in the use of guideline-consistent, evidence-based care processes.
Outpatient Opioid Prescriptions for Children and Opioid-Related Adverse Events
Recommended by Meridith Peratikos, MS, Director of Statistics & Scientific Collaboration
The authors identified opioid-related adverse events out of the 1.3 million opioid prescriptions prescribed to Tennessee children over 5 years. A strength of this study is that the events were adjudicated using medical and/or death records.
In 2016, axialHealthcare performed two studies on children in episodes of pain with client data. We calculated the median Morphine Equivalent Daily Dose (MEDD) to be 15 mg on the low end and higher depending on population and age group. We found dentists, primary care providers, and emergency medicine practitioners prescribed the majority of opioids.
Buprenorphine for Medication-Assisted Treatment of Opioid Use Disorder in Pregnancy: Relationship to Neonatal Opioid Withdrawal Syndrome
Recommended by Ray Pasek, PhD, Senior Research Data Scientist
This study found that incidence of neonatal abstinence syndrome (referred to as neonatal opioid withdrawal syndrome) was not related to the dosage of buprenorphine, suggesting that buprenorphine dose is not predictive of patients who are likely to give birth to an infant with neonatal abstinence syndrome. This is important for clinicians treating women for OUD during pregnancy.
Reduction in Opioid Prescribing through Evidence-based Prescribing Guidelines
Recommended by Chris Muller, PhD, Senior Research Data Scientist
This particular study combines analysis of prescription claims data with patient outreach to formalize pain management best practices and curb excess opioid prescribing to mitigate the risk of opioid diversion. Authors hope the results of this study will serve as a platform for other states and organizations to develop more streamlined postoperative opioid prescribing guidelines.
By David Simon, Ph.D., Research Data Scientist Predicting a patient’s risk for adverse outcomes is an important part of delivering precision medicine and improving the lives of patients. In order to achieve these goals, axialHealthcare has developed a number of machine learning models that quantify patient risk. An exciting example is our machine learning model…Read More ›