Trends in comorbid opioid and stimulant use disorders among Veterans receiving care from the Veterans Health Administration, 2005-2019

Correlates of Staff Acceptability of a Novel Telemedicine-Delivered Medications for Opioid Use Disorder Program in a Rural Detention Center

Opioid overdose death is significantly increased immediately following incarceration. Evidence-based medications are underutilized in rural jails and detention centers. We have reported our efforts to address this gap through telemedicine-based medications for opioid use disorder treatment (tele-MOUD) for incarcerated patients. Staff acceptance and perceptions are critically important factors in the assurance of program validation. We assessed tele-MOUD acceptability and perceptions of effectiveness and stigma in one detention center. Overall, we found that jail staff's general acceptability of the program was rather low, as was perceived effectiveness of MOUD, while stigmatizing beliefs were present. Furthermore, tele-MOUD acceptability was positively correlated with perceptions of MOUD effectiveness and negatively correlated with stigmatizing notions of MOUD (p's < 0.001). Findings suggest the need for educational interventions. Future research investigating the potential moderating effects of training on staff acceptability of jail-based tele-MOUD will support the implementation and sustainability of these life-saving programs.

A Comparison of Veterans with Problematic Opioid Use Identified through Natural Language Processing of Clinical Notes versus Using Diagnostic Codes

Opioid use disorder is known to be under-coded as a diagnosis, yet problematic opioid use can be documented in clinical notes, which are included in electronic health records. We sought to identify problematic opioid use from a full range of clinical notes and compare the demographic and clinical characteristics of patients identified as having problematic opioid use exclusively in clinical notes to patients documented through ICD opioid use disorder diagnostic codes. We developed and applied a natural language processing (NLP) tool that combines rule-based pattern analysis and a trained support vector machine to the clinical notes of a patient cohort (n = 222,371) from two Veteran Affairs service regions to identify patients with problematic opioid use. We also used a set of ICD diagnostic codes to identify patients with opioid use disorder from the same cohort. The NLP tool achieved 96.6% specificity, 90.4% precision/PPV, 88.4% sensitivity/recall, and 94.4% accuracy on unseen test data. NLP exclusively identified 57,331 patients; 6997 patients had positive ICD code identifications. Patients exclusively identified through NLP were more likely to be women. Those identified through ICD codes were more likely to be male, younger, have concurrent benzodiazepine prescriptions, more comorbidities, and more care encounters, and were less likely to be married. Patients in both these groups had substantially elevated comorbidity levels compared with patients not documented through either method as experiencing problematic opioid use. Clinicians may be reluctant to code for opioid use disorder. It is therefore incumbent on the healthcare team to search for documentation of opioid concerns within clinical notes.

Characteristics and co-morbidities associated with hospital discharges for opioid and methamphetamine co-use, United States 2016-2019

Introduction

The US overdose crisis is increasingly characterized by opioid and methamphetamine co-use. Hospitalization is an important opportunity to engage patients in substance use treatment. Understanding characteristics of co-use-related hospital stays can inform the development of services to better support this growing patient population.

Methods

We used 2016-2019 National Inpatient Sample data to conduct a cross sectional analysis of hospitalizations involving use of opioids, methamphetamine, or both. We used bivariate analysis to compare patient demographics. We then used multinomial logistic regressions to compare the proportion of hospital stays which indicated co-morbid diagnosis. To account for correlated data, we used generalized linear models to compare outcomes in hospital mortality, patient-directed discharge, and length of stay.

Results

Co-use-related stays had a higher proportion of co-morbid mental health (60.7%; 95% CI: 59.9-61.4%) and infectious diseases (41.5%; 95% CI: 40.8-42.2%), than opioid- or methamphetamine-related stays. Co-use-related stays increased between 2016 and 2019 and were associated with a higher proportion of patient directed discharge (10.7%; 95% CI: 10.4-11.0%) and longer length of stay (6.3 days; 95% CI: 6.2-6.4 days) compared to opioid (8.1%; 95% CI: 7.9-8.3% and 5.8 days; 95% CI: 5.8-5.9 days) and methamphetamine-related stays (6.5%; 95% CI: 6.3-6.6% and 5.5 days; 95% CI: 5.4-5.5 days).

Conclusion

Patients discharged with co-use differ from patients with opioid or methamphetamine use alone, representing a range of challenges and opportunities. In addition to offering treatment for both substance use disorders, hospital-based services that address co-occurring conditions may better support patients with co-use through targeted and tailored approaches.

Are you thinking what I'm thinking? Defining what we mean by "polysubstance use."

The rise in drug overdoses and harms associated with the use of more than one substance has led to increased use of the term "polysubstance use" among researchers, clinicians, and public health officials. However, the term retains no consistent definition across contexts. The current authors convened from disciplines including sociology, epidemiology, neuroscience, and addiction psychiatry to propose a recommended definition of polysubstance use. An iterative process considered authors' formal and informal conversations, insights from relevant symposia, talks, and conferences, as well as their own research and clinical experiences to propose the current definition. Three key concepts were identified as necessary to define polysubstance use: (1) substances involved, (2) timing, and (3) intent. Substances involved include clarifying either (1) the number and type of substances used, (2) presence of more than one substance use disorder, or (3) primary and secondary substance use. The concept of timing is recommended to use clear terms such as simultaneous, sequential, and same-day polysubstance use to describe short-term behaviors (e.g., 30-day windows). Finally, the concept of intent refers to clarifying unintentional use or exposure when possible, and greater attention to motivations of polysubstance use. These three components should be clearly defined in research on polysubstance use to improve consistency across disciplines. Consistent definitions of polysubstance use can aid in the synthesis of evidence to better address an overdose crisis that increasingly involves multiple substances.

Charting the fourth wave: Geographic, temporal, race/ethnicity and demographic trends in polysubstance fentanyl overdose deaths in the United States, 2010-2021

AIMS

To characterize polysubstance death in the United States during the transition to the fourth wave of the drug overdose crisis. To characterize co-involved substances in fatal overdose involving synthetic opioids (mainly illicitly manufactured fentanyl analogues) by year, state, and intersectional sociodemographic groups.

DESIGN

Population-based study of national death records.

SETTING

United States.

PARTICIPANTS/CASES

All people who died from drug overdose in the United States between 2010 and 2021.

MEASUREMENTS

Percentage of all fatal overdose involving fentanyls, stimulants, and other drugs. Most commonly co-involved substances in fentanyl overdose by state and year. Percentage of fatal fentanyl overdose co-involving stimulants by state and year. Percentage of fatal fentanyl overdose co-involving stimulants by intersectional region, race/ethnicity, age, and sex.

FINDINGS

The percent of US overdose deaths involving both fentanyl and stimulants increased from 0.6% (n = 235) in 2010 to 32.3% (34 429) in 2021, with the sharpest rise starting in 2015. In 2010, fentanyl was most commonly found alongside prescription opioids, benzodiazepines, and alcohol. In the Northeast this shifted to heroin-fentanyl co-involvement in the mid-2010s, and nearly universally to cocaine-fentanyl co-involvement by 2021. Universally in the West, and in the majority of states in the South and Midwest, methamphetamine-fentanyl co-involvement predominated by 2021. The proportion of stimulant involvement in fentanyl-involved overdose deaths rose in virtually every state 2015-2021. Intersectional group analysis reveals particularly high rates for older Black and African American individuals living in the West.

CONCLUSIONS

By 2021 stimulants were the most common drug class found in fentanyl-involved overdoses in every state in the US. The rise of deaths involving cocaine and methamphetamine must be understood in the context of a drug market dominated by illicit fentanyls, which have made polysubstance use more sought-after and commonplace. The widespread concurrent use of fentanyl and stimulants, as well as other polysubstance formulations, presents novel health risks and public health challenges.

Impact of COVID-19 on stimulant use disorder treatment: A national cohort study in the Veterans Health Administration

OBJECTIVE

Rates of stimulant overdose have increased dramatically, which may have been exacerbated by treatment disruptions during the pandemic, but no recent studies have examined use of stimulant use disorder (StUD) treatment.

METHODS

In this retrospective cohort study (March 2018 to February 2022) of national Veterans Health Administration patients, we use an interrupted time-series analysis to examine the impact of COVID-19 (starting in March 2020) on treatment use for StUD.

RESULTS

The number of patients receiving StUD care was increasing pre-COVID (22,640-23,020, February 2018-February 2020) but dropped post-pandemic to 18,578 in February 2022. The monthly number of patients receiving StUD care increased by 34.6 patients per month (95% CI, 1.1-68.0; P=0.04) before March 2020, decreased by 2803.3 patients (95% CI, -3912.3 to -1694.3; P <0.001) in March 2020, and, accounting for pre-COVID trends, further decreased by 85.85 patients per month (95% CI,-148.9.2 to -23.0; P =0.01) after March 2020.

CONCLUSIONS

Care for StUD drastically declined during the COVID-19 pandemic and has yet to show signs of a return to pre-pandemic levels despite surging rates of stimulant-involved overdose deaths and a critical need to engage people with StUD in care.

Drive Time to Addiction Treatment Facilities Providing Contingency Management across Rural and Urban Census Tracts in 6 US States

OBJECTIVE

We examined drive times to outpatient substance use disorder treatment providers that provide contingency management (CM) and those that integrate CM with medication for opioid use disorder (MOUD) services in 6 US states.

METHODS

We completed cross-sectional geospatial analysis among census tracts in Delaware, Louisiana, Massachusetts, North Carolina, New York, and West Virginia. We excluded census tracts with a population of zero. Using data from the 2020 Shatterproof substance use treatment facility survey, our outcome was the minimum drive time in minutes from the census tract mean center of population to the nearest outpatient CM provider, outpatient CM provider with MOUD services, and federally qualified health centers (FQHC). We stratified census tracts by 2010 Rural-Urban Commuting Area codes and by state.

RESULTS

The population was greater than zero in 11,719 of 11,899 census tracts. The median drive time to the nearest CM provider was 12.2 [interquartile range (IQR), 7.0-23.5) minutes and the median drive time to the nearest CM provider increased from 9.7 (IQR, 6.0-15.0) minutes in urban census tracts to 38.8 (IQR, 25.4-53.0) minutes in rural ( H = 3683, P < 0.001). The median drive time increased to the nearest CM provider with MOUD services [14.2 (IQR, 7.9-29.5) minutes, W = 18,877, P < 0.001] and decreased to the nearest FQHC [7.9 (IQR, 4.3-13.6) minutes, W = 11,555,894, P < 0.001].

CONCLUSIONS

These results suggest limited availability of CM, particularly within rural communities and for patients needing concurrent CM and MOUD treatment. Our results suggest greater adoption of CM within FQHCs could reduce urban-rural disparities in CM availability.

Co-occurring Medical Multimorbidity, Mental Illness, and Substance Use Disorders Among Older Criminal Legal System-Involved Veterans

BACKGROUND

Older veterans involved in the criminal legal system (CLS) may have patterns of multimorbidity that place them at risk for poor health outcomes.

OBJECTIVES

To estimate the prevalence of medical multimorbidity (≥2 chronic medical diseases), substance use disorders (SUDs), and mental illness among CLS-involved veterans aged 50 and older.

RESEARCH DESIGN

Using Veterans Health Administration health records, we estimated the prevalence of mental illness, SUD, medical multimorbidity, and the co-occurrence of these conditions among veterans by CLS involvement as indicated by Veterans Justice Programs encounters. Multivariable logistic regression models assessed the association between CLS involvement, the odds for each condition, and the co-occurrence of conditions.

SUBJECTS

Veterans aged 50 and older who received services at Veterans Health Administration facilities in 2019 (n=4,669,447).

METHODS

Mental illness, SUD, medical multimorbidity.

RESULTS

An estimated 0.5% (n=24,973) of veterans aged 50 and older had CLS involvement. For individual conditions, veterans with CLS involvement had a lower prevalence of medical multimorbidity compared with veterans without but had a higher prevalence of all mental illnesses and SUDs. After adjusting for demographic factors, CLS involvement remained associated with concurrent mental illness and SUD (adjusted odds ratio [aOR] 5.52, 95% CI=5.35-5.69), SUD and medical multimorbidity (aOR=2.09, 95% CI=2.04-2.15), mental illness and medical multimorbidity (aOR=1.04, 95% CI=1.01-1.06), and having all 3 simultaneously (aOR=2.42, 95% CI=2.35-2.49).

CONCLUSIONS

Older veterans involved in the CLS are at high risk for co-occurring mental illness, SUDs, and medical multimorbidity, all of which require appropriate care and treatment. Integrated care rather than disease-specific care is imperative for this population.

Research and policy recommendations from the SOTA XVI: State of the Art Conference on VA Emergency Medicine

To better understand and prioritize research on emergency care for Veterans, the Department of Veteran Affairs (VA) Health Services Research and Development convened the 16th State of the Art Conference on VA Emergency Medicine (SAVE) in Winter 2022 with emergency clinicians, researchers, operational leaders, and additional stakeholders in attendance. Three specific areas of focus were identified including older Veterans, Veterans with mental health needs, and emergency care in the community (non-VA) settings. Among older Veterans, identified priorities included examination of variation in care and its impact on patient outcomes, utilization, and costs; quality of emergency department (ED) care transitions and strategies to improve them; impact of geriatric ED care improvement initiatives; and use of geriatric assessment tools in the ED. For Veterans with mental health needs, priorities included enhancing the reach of effective, multicomponent suicide prevention interventions; development and evaluation of interventions to manage substance use disorders; and identifying and examining safety and effective acute psychosis practices. Community (non-VA) emergency care priorities included examining changes in patterns of use and costs in VA and the community care settings as a result of recent policy and coverage changes (with an emphasis on modifiable factors); understanding quality, safety, and Veteran experience differences between VA and community settings; and better understanding follow-up needs among Veterans who received emergency care (or urgent care) and how well those needs are being coordinated, communicated, and met. Beyond these three groups, cross-cutting themes included the use of telehealth and implementation science to refine multicomponent interventions, care coordination, and data needs from both VA and non-VA sources. Findings from this conference will be disseminated through multiple mechanisms and contribute to future funding applications focused on improving Veteran health.

Substance use disorders and social determinants of health from electronic medical records obtained during Kentucky's "triple wave"

Social determinants of health (SDOH) play a critical role in the risk of harmful drug use. Examining SDOH as a means of differentiating populations with multiple co-occurring substance use disorders (SUDs) is particularly salient in the era of prevalent opioid and stimulant use known as the "Third Wave". This study uses electronic medical records (EMRs) from a safety net hospital system from 14,032 patients in Kentucky from 2017 to 2019 in order to 1) define three types of SUD cohorts with shared/unique risk factors, 2) identify patients with unstable housing using novel methods for EMRs and 3) link patients to their residential neighborhood to obtain quantitative perspective on social vulnerability. We identified patients in three cohorts with statistically significant unique risk factors that included race, biological sex, insurance type, smoking status, and urban/rural residential location. Adjusting for these variables, we found a statistically significant, increasing risk gradient for patients experiencing unstable housing by cohort type: opioid-only (n = 7385, reference), stimulant-only (n = 4794, odds ratio (aOR) 1.86 95 % confidence interval (CI): 1.66-2.09), and co-diagnosed (n = 1853, aOR = 2.75, 95 % CI: 2.39 to 3.16). At the neighborhood-level, we used 8 different measures of social vulnerability and found that, for the most part, increasing proportions of patients with stimulant use living in a census tract was associated with more social vulnerability. Our study identifies potentially modifiable factors that can be tailored by substance type and demonstrates robust use of EMRs to meet national goals of enhancing research on social determinants of health.