Mental health and opioid addiction comorbidities among chronic pain patients

Kevin Cevasco, Bill Saunders

Abstract


Objective

Assessing mental health and opioid addiction comorbidities among chronic pain patients using a large longitudinal clinical, operational, and laboratory data set.

Introduction

The National Institute for Drug Abuse Report, Common Comorbidities with Substance Use Disorders, states there are “many individuals who develop substance use disorders (SUD) are also diagnosed with mental disorders, and vice versa.”(1) Prescription opioids are amongst the most commonly used drugs that lead to illicit drug use.(2)Much of the data about the starting point of the prescription opioid addiction is in the patient health history and is recorded within the provider electronic health record and administrative systems.

Description

There are a variety of addiction and misuse risk screening tools available and selecting appropriate tools screening can be confusing for providers. Examples of common screening tools: Opioid Abuse Risk Screener (OARS), Opioid Risk Tool (ORT), Screener and Opioid Assessment for Patients with Pain (SOAPP), Current Opioid Misuse Measure (COMM), Diagnosis, Intractability, Risk, and Efficacy (DIRE). These opioid risk screening tools are interview based and vary in how they survey for psychosocial factors. The screening tools are useful, but are meant only to alert the provider to conduct further investigation.(3)
Understanding how the comorbidities recorded in the patient’s clinical interactions may help improve risk assessment investigations and ongoing monitoring programs. Studying the chronic pain patients’ longitudinal clinical, operational, and laboratory records provides the basis for better study controls than those using population based on emergency department admission and mortality events.
Methods
The analysis leverages IBM's Explorys electronic health record (EHR) data, a large integrated source of real world clinical, operational and lab data across 39 large integrated delivery networks that span the continuum of care. In addition to demographic characteristics of drug abusers, we will describe common comorbidities of selected mental health diagnoses, examine coding-related issues, distinguish chronic and episodic addiction and look for regional differences due to state/local level prescribing training and provider addiction awareness.

How the Moderator Intends to Engage the Audience in Discussions on the Topic

Promote the event through interatction with the @ISDS twitter account and #ISDS19 hashtag.
Solicit question for presenters-panelists through social media before the briefing, and meet with presenters before the event to tune the presenations to areas of interest.
Conduct a demographic poll of the audience to get them engaged. Ask audience to stand to show their organization-role. e.g. state-local public health, provider, vendor. This helps the presenters adapt to the audience profile.
After each panelist speaks, have the panelist ask a question to the audience about a lingering question that arose during the research. Limit the audience to ~1 minute to answer. Allow panelists to ask a few more questions if the process is working, but limit to overall event time schedule.
Finish with Q&A from the audience.

References

1. Abuse NI on D. Part 1: The Connection Between Substance Use Disorders and Mental Illness [Internet]. [cited 2018 Sep 29]. Available from: https://www.drugabuse.gov/publications/research-reports/common-comorbidities-substance-use-disorders/part-1-connection-between-substance-use-disorders-mental-illness
2. Lankenau SE, Teti M, Silva K, Bloom JJ, Harocopos A, Treese M. Initiation into prescription opioid misuse amongst young injection drug users. Int J Drug Policy. 2012 Jan 1;23(1):37–44.
3. Hudspeth RS. Safe Opioid Prescribing for Adults by Nurse Practitioners: Part 1. Patient History and Assessment Standards and Techniques. J Nurse Pract. 2016 Mar;12(3):141–8.

 


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DOI: https://doi.org/10.5210/ojphi.v11i1.9798



Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org