Identifying High-Risk Comorbidities Associated with Opioid Use Patterns Using Electronic Health Record Prescription Data

Abstract

Introduction. Opioid use disorders (OUD) constitute a major public health issue, and we urgently need alternative methods for characterizing risk for OUD. Electronic health records (EHR) are useful tools for understanding complex medical phenotypes, but have been underutilized for OUD because of challenges related to underdiagnosis, binary diagnostic frameworks, and minimally-characterized reference groups. As a first step in addressing these challenges, a new paradigm is warranted that characterizes risk for opioid prescription misuse on a continuous scale of severity, i.e., as a continuum. Methods. Across sites within the PsycheMERGE network, we extracted prescription opioid data and diagnoses that co-occur with OUD (including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C) for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: no prescriptions, minimal exposure, and chronic exposure and then compared the comorbidity profiles of these groups to the full registries and to those with OUD diagnostic codes. Results. Our results confirm that EHR data reflects known higher prevalence of substance use disorders, psychiatric disorders, medical, and pain diagnoses in patients with OUD diagnoses and chronic opioid use. Comorbidity profiles that distinguish opioid exposure are strikingly consistent across large health systems, indicating the phenotypes described in this new quantitative framework are robust to health systems differences. Conclusion. This work indicates that EHR prescription opioid data can serve as a platform to characterize complex risk markers for OUD using existing data.

Mental health and substance use disorder comorbidities among Medicaid beneficiaries: Associations with opioid use disorder and prescription opioid misuse

“…Criteria for determining no, possible, and probable misuse are based on number of prescriptions for opioids received, and the number of different pharmacies where prescriptions were filled as well as morphine millgram equivalents per day [33] . Persons with an OUD were identified through analysis of claims data indicating receipt of treatment services for an OUD during the year, as specified in the SUD Technical Specifications document [34] . Significance levels for all categorical variables are based on the Pearson Chi-square statistic while effect size is based on Cramer's V. Signficance for the comparison of mean numbers of substance use and mental health disorders by potential misuse status are based on bivariate regressions estimated with robust standard errors.…”

“…Criteria for determining no, possible, and probable misuse are based on number of prescriptions for opioids received, and the number of different pharmacies where prescriptions were filled as well as morphine millgram equivalents per day [33] . Persons with an OUD were identified through analysis of claims data indicating receipt of treatment services for an OUD during the year, as specified in the SUD Technical Specifications document [34] . The reference category for all multinomial logistic models was Medicaid beneficiaries with no detected opioid use in the past year.…”

“…A study of Iraq and Afghanistan veterans with a mental health diagnoses showed a higher prevalence of adverse clinical outcomes including opioid accidents and overdoses [33] . More recently and most germane to the present study, research performed by Jennings et al [34] used electronic health record data to examine the co-occurrence of psychiatric, substance use, and medical disorders among three groups with varying levels of opioid exposure that ranged from no opioid prescriptions to chronic exposure, defined as having received 10 or more prescriptions in a 12-month period. The study included an additional comparison group consisting of those who had been diagnosed with an OUD.…”

Developing a Framework to Infer Opioid Use Disorder Severity From Clinical Notes to Inform Natural Language Processing Methods: Characterization Study

“…At least one diagnosis code for OUD. International Classification of Disease codes used to define OUD were based on Jennings et al [ 29 ].…”

Acute Pain and Development of Opioid Use Disorder: Patient Risk Factors

“…Another patient-related risk factor for OUD development in the treatment of acute pain is a history of mental illness such as anxiety disorders, or depression [ 10 ••], including the morphine’s mood-elevating effects of opioids [ 28 •]. Moreover, patients with preexisting use of antidepressants, benzodiazepines, or other recreational drugs such as tobacco, alcohol, or cocaine are at an increased risk of developing OUD [ 9 , 10 ••, 22 , 32 , 33 ].…”