Prevalence Of Opioid Use Disorder Research Articles

Racial inequities in opioid use disorder management: can the anesthesiologist improve outcomes?

Racial inequities in opioid use disorder management: can the anesthesiologist improve outcomes?

Current and emerging pharmacotherapies for opioid dependence treatments in adults: a comprehensive update

Introduction Opioid use disorder (OUD) is characterized by compulsive opioid seeking and taking, intense drug craving, and intake of opioids despite negative consequences. The prevalence of OUDs has now reached an all-time high, in parallel with peak rates of fatal opioid-related overdoses, where 15 million individuals worldwide meet the criteria for OUD. Further, in 2020, 120,000 opioid-related deaths were reported worldwide with over 75,000 of those deaths occurring within the United States. Areas covered In this review, we highlight pharmacotherapies utilized in patients with OUDs, including opioid replacement therapies, and opioid antagonists utilized for opioid overdoses and deterrent of opioid use. We also highlight newer treatments, such as those targeting the neuroimmune system, which are potential new directions for research given the recently established role of opioids in activating neuroinflammatory pathways, as well as over the counter remedies, including kratom, that may mitigate withdrawal. Expert opinion To effectively treat OUDs, a deeper understanding of the current therapeutics being utilized, their additive effects, and the added involvement of the neuroimmune system are essential. Additionally, a complete understanding of opioid-induced neuronal alterations and therapeutics that target these abnormalities – including the neuroimmune system – is required to develop effective treatments for OUDs.

Hospitalist perspectives on buprenorphine treatment for inpatients with opioid use disorder

BackgroundPatients with opioid use disorder (OUD) have high hospital admission rates. Hospitalists, clinicians that work in inpatient medical settings, may have a unique opportunity to intervene on behalf of these patients, yet their experience with and attitudes towards treating patients with OUD need further exploration. MethodsWe conducted qualitative analysis of 22 semi-structured interviews with hospitalists between January and April 2021 in Philadelphia, PA. Participants were hospitalists in one major metropolitan university hospital and one urban community hospital in a city with a high prevalence of OUD and overdose deaths. Participants were asked about their experiences, successes, and difficulties in treating hospitalized patients with OUD. ResultsTwenty-two hospitalists were interviewed. Participants were majority female (14, 64%) and White (16, 73%). We identified the following common themes: lack of training/experience with OUD, a lack of community OUD treatment infrastructure, a lack of inpatient OUD/withdrawal treatment resources, the “X-waiver” as a barrier to prescribing buprenorphine, the “ideal” patient to start on buprenorphine, and the hospital as an ideal intervention setting. ConclusionsHospitalization due to acute illness or complication of drug use represents a potential intervention point to initiate treatment for patients with OUD. While hospitalists exhibit willingness to prescribe medications, provide harm reduction education, and link patients to outpatient addiction treatment, they identify training and infrastructure barriers that must first be addressed.

Improving hepatitis C screening and access to treatment.

The rising prevalence of opioid use disorder and injection drug use has resulted in an increasing incidence of chronic hepatitis C virus (HCV) infection. Although older adults historically have represented the bulk of HCV infections in the United States, demographics have shifted and most new infections are presenting in younger patients. As a result, screening guidelines for HCV have evolved, moving toward a near-universal screening paradigm. Rates of screening and linkage to care remain low, attributed to the fact that underserved populations are disproportionately affected and often have limited access to specialty care. Collaborative models to treat HCV using primary care providers have been proposed to facilitate linkage to care and reduce transmission.

Opioid Use Disorder Among Ohio's Medicaid Population: Prevalence Estimates From 19 Counties Using a Multiplier Method.

The decades-long overdose epidemic in the United States is driven by opioid misuse. Overdoses commonly, although not exclusively, occur in individuals with opioid use disorder (OUD). To allocate adequate resources and develop appropriately scaled public health responses, accurate estimation of the prevalence of OUD is needed. Indirect methods (e.g., a multiplier method) of estimating prevalence of problematic substance-use behavior circumvent some limitations of household surveys and use of administrative data. We used a multiplier method to estimate OUD prevalence among the adult Medicaid population (ages 18-64 years) in 19 Ohio counties that are highly affected by overdose. We used Medicaid claims data and the US National Vital Statistics System overdose death data, which were linked at the person level. A statistical model leveraged opioid-related death rate information from a group with known OUD to estimate prevalence among a group with unknown OUD status given recorded opioid-related deaths in that group. We estimated that 13.6% of the total study population had OUD in 2019. Men (16.7%) had a higher prevalence of OUD than women (11.4%), and persons aged 35-54 had the highest prevalence (16.7%). Our approach to prevalence estimation has important implications for OUD surveillance and treatment in the United States.

Delivery timing for the opioid–exposed infant

The prevalence of opioid use disorder and medication-assisted treatment in pregnancy is increasing. Compared with term infants, preterm infants have a lower incidence of neonatal opioid withdrawal syndrome. It is unknown whether early term delivery compared with full or late-term delivery decreases the risk of neonatal opioid withdrawal syndrome. This study aimed to compare the neonatal outcomes among opioid-exposed infants born in the early, full, and late-term periods. This was a retrospective cohort study of opioid-exposed pregnancies delivering at a single center from 2010 to 2017 at ≥37 weeks gestation. Participants with multiple gestations or fetal anomalies were excluded. Maternal opioid exposurewas defined as prescription (including medication-assisted treatment) or nonprescription opioid use or a positive urine drug screen in pregnancy for opiates. The primary outcome was a neonatal composite of respiratory distress syndrome, neonatal sepsis, neonatal seizures, hypoxic ischemic encephalopathy, jaundice requiring treatment, 5-minute Apgar <5, neonatal intensive care unit admission, neonatal opioid withdrawal syndrome, or neonatal death. The secondary outcomes included individual components of the primary outcome, birthweight, need for and length of neonatal opioid withdrawal syndrome treatment, length of hospital admission, and maximum Finnegan scores. Early (37-<39), full (39-<41), and late (41-<42 weeks) term groups were defined by the American College of Obstetricians and Gynecologists. Of 399 infants, 136 (34.1%), 229 (57.4%), and 34 (8.5%) were born in the early, full, and late-term periods, respectively. Two hundred and seventy patients (67.7%) received medication-assisted treatment for opioid use disorder, and the baseline characteristics were similar in all the groups except for history of intranasal heroin use, positive urine toxicology screen for heroin or any opiates, and delivery indication (P<.05). The primary composite outcome occurred in 313 (78.4%) neonates, and 296 (74.2%) neonates had neonatal opioid withdrawal syndrome. More than half (219 [54.9%]) of opioid-exposed neonates were admitted to the neonatal intensive care unit, and 160 (40.1%) required pharmacologic neonatal opioid withdrawal syndrome treatment for a mean duration of almost 3 weeks (19.0±16.1 days). There were no significant differences in the primary composite outcome, incidence of neonatal opioid withdrawal syndrome, or other secondary outcomes (except birthweight) between neonates born in the early, full, or late-term periods. Although neonatal morbidity was frequent among opioid-exposed neonates, the incidence and severity of neonatal opioid withdrawal syndrome or other neonatal outcomes were not different between neonates delivered in the early, full, and late-term periods, suggesting that opioid-exposed infants may not benefit from early term delivery.

Defining Opioid-related Problems Using a Health Care Safety Net Institution's Inpatient Electronic Health Records: Limitations of Diagnosis-based Definitions.

Measuring clinically relevant opioid-related problems in health care systems is challenging due to the lack of standard definitions and coding practices. Well-defined, opioid-related health problems (ORHPs) would improve prevalence estimates and evaluation of clinical interventions, crisis response, and prevention activities. We sought to estimate prevalence of opioid use disorder (OUD), opioid misuse, and opioid poisoning among inpatients at a large, safety net, health care institution. Our study included events documented in the electronic health records (EHRs) among hospitalized patients at Denver Health Medical Center during January 1, 2017 to December 31, 2018. Multiple EHR markers (ie, opioid-related diagnostic codes, clinical assessment, laboratory results, and free-text documentation) were used to develop diagnosis-based and extended definitions for OUD, opioid misuse, and opioid poisoning. We used these definitions to estimate number of hospitalized patients with these conditions. During a 2-year study period, 715 unique patients were identified solely using opioid-related diagnostic codes; OUD codes accounted for the largest proportion (499/715, 69.8%). Extended definitions identified an additional 973 unique patients (~136% increase), which includes 155/973 (15.9%) who were identified by a clinical assessment marker, 1/973 (0.1%) by a laboratory test marker, and 817/973 (84.0%) by a clinical documentation marker. Solely using diagnostic codes to estimate prevalence of clinically relevant ORHPs missed most patients with ORHPs. More inclusive estimates were generated using additional EHR markers. Improved methods to estimate ORHPs among a health care system's patients would more fully estimate organizational and economic burden to more efficiently allocate resources and ensure capacity to provide clinical services.

Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis.

Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers’ capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.

Sex Differences in Comorbid Mental and Substance Use Disorders Among Primary Care Patients With Opioid Use Disorder.

The authors sought to characterize the 3-year prevalence of mental disorders and nonnicotine substance use disorders among male and female primary care patients with documented opioid use disorder across large U.S. health systems. This retrospective study used 2014-2016 data from patients ages ≥16 years in six health systems. Diagnoses were obtained from electronic health records or claims data; opioid use disorder treatment with buprenorphine or injectable extended-release naltrexone was determined through prescription and procedure data. Adjusted prevalence of comorbid conditions among patients with opioid use disorder (with or without treatment), stratified by sex, was estimated by fitting logistic regression models for each condition and applying marginal standardization. Females (53.2%, N=7,431) and males (46.8%, N=6,548) had a similar prevalence of opioid use disorder. Comorbid mental disorders among those with opioid use disorder were more prevalent among females (86.4% vs. 74.3%, respectively), whereas comorbid other substance use disorders (excluding nicotine) were more common among males (51.9% vs. 60.9%, respectively). These differences held for those receiving medication treatment for opioid use disorder, with mental disorders being more common among treated females (83% vs. 71%) and other substance use disorders more common among treated males (68% vs. 63%). Among patients with a single mental health condition comorbid with opioid use disorder, females were less likely than males to receive medication treatment for opioid use disorder (15% vs. 20%, respectively). The high rate of comorbid conditions among patients with opioid use disorder indicates a strong need to supply primary care providers with adequate resources for integrated opioid use disorder treatment.

Treatment Experiences Among People Who Use Opioids: A Social Ecological Approach.

The prevalence of opioid use disorder (OUD) and surge in overdose deaths remain key public health concerns. Despite evidence supporting the efficaciousness of medications for opioid use disorder, most people with OUD do not receive treatment. In this qualitative study, semi-structured interviews were conducted with 35 adults in a northeastern city to learn about their experiences with substance use treatment. Qualitative data were analyzed using an inductive thematic content analysis approach, and a social ecological model was applied to examine contextual factors affecting participants' experiences accessing and engaging in treatment. While we organized our findings following the individual, interpersonal, community, and society levels of the socio-ecological model, we also observed overlap and interconnectedness between and across these levels. Our findings suggest that retention in treatment often depends upon personal motivation, treatment availability, the match of the treatment modality to an individual's needs, and social support. A person-centered approach is needed to promote individualized care and tailor treatment components to the patient's needs.

Societal Cost of Opioid Use in Symptomatic Knee Osteoarthritis Patients in the United States.

Symptomatic knee osteoarthritis (SKOA) is a chronic, disabling condition, requiring long-term pain management; over 800,000 SKOA patients in the US use opioids on a prolonged basis. We aimed to characterize the societal economic burden of opioid use in this population. We used the Osteoarthritis Policy Model, a validated computer simulation of SKOA, to estimate the opioid-related lifetime and annual cost generated by the US SKOA population. We included direct medical, lost productivity, criminal justice, and diversion costs. We modeled the SKOA cohort with a mean ± SD age of 54 ± 14 years and Western Ontario and McMaster Universities Osteoarthritis Index pain score of 29 ± 17 (0-100, 100 = worst). We estimated annual costs of strong ($1,381) and weak ($671) opioid regimens using Medicare fee schedules, Red Book, the Federal Supply Schedule, and published literature. The annual lost productivity and criminal justice costs of opioid use disorder (OUD), obtained from published literature, were $11,387 and $4,264, per-person, respectively. The 2015-2016 Medicare Current Beneficiary Survey provided OUD prevalence. We conducted sensitivity analyses to examine the robustness of our estimates to uncertainty in input parameters. Assuming 5.1% prevalence of prolonged strong opioid use, the total lifetime opioid-related cost generated by the US SKOA population was estimated at $14.0 billion, of which only $7.45 billion (53%) were direct medical costs. Lost productivity, diversion, and criminal justice costs comprise approximately half of opioid-related costs generated by the US SKOA population. Reducing prolonged opioid use may lead to a meaningful reduction in societal costs that can be used for other public health causes.

The Feasibility and Utility of Harnessing Digital Health to Understand Clinical Trajectories in Medication Treatment for Opioid Use Disorder: D-TECT Study Design and Methodological Considerations.

IntroductionAcross the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substance use during substance use disorder treatment. However, much of this literature has examined a small set of potential moderators or mediators of outcomes in MOUD treatment and may lead to over-simplified accounts of treatment non-adherence. Digital health methodologies offer great promise for capturing intensive, longitudinal ecologically-valid data from individuals in MOUD treatment to extend our understanding of factors that impact treatment engagement and outcomes.MethodsThis paper describes the protocol (including the study design and methodological considerations) from a novel study supported by the National Drug Abuse Treatment Clinical Trials Network at the National Institute on Drug Abuse (NIDA). This study (D-TECT) primarily seeks to evaluate the feasibility of collecting ecological momentary assessment (EMA), smartphone and smartwatch sensor data, and social media data among patients in outpatient MOUD treatment. It secondarily seeks to examine the utility of EMA, digital sensing, and social media data (separately and compared to one another) in predicting MOUD treatment retention, opioid use events, and medication adherence [as captured in electronic health records (EHR) and EMA data]. To our knowledge, this is the first project to include all three sources of digitally derived data (EMA, digital sensing, and social media) in understanding the clinical trajectories of patients in MOUD treatment. These multiple data streams will allow us to understand the relative and combined utility of collecting digital data from these diverse data sources. The inclusion of EHR data allows us to focus on the utility of digital health data in predicting objectively measured clinical outcomes.DiscussionResults may be useful in elucidating novel relations between digital data sources and OUD treatment outcomes. It may also inform approaches to enhancing outcomes measurement in clinical trials by allowing for the assessment of dynamic interactions between individuals' daily lives and their MOUD treatment response.Clinical Trial RegistrationIdentifier: NCT04535583.

Prevalence and Outcomes of Opioid Use Disorder in Pediatric Surgical Patients: A Retrospective Cohort Study.

Chronic opioid use among adolescents is a leading preventable public health problem in the United States. Consequently, a sizable proportion of surgical patients in this age group may have a comorbid opioid use disorder (OUD). No previously published study has examined the prevalence of OUD and its impact on postoperative morbidity or mortality in the adolescent surgical population. Our objective was to investigate the prevalence of comorbid OUD and its association with surgical outcomes in a US adolescent surgical population. We hypothesized that OUD among adolescent surgical patients is on an upward trajectory and that the presence of OUD is associated with higher risk of postoperative morbidity or mortality. Using the pediatric health information system, we performed a 1:1 propensity score-matched, retrospective cohort study of adolescents (10-18 years of age) undergoing inpatient surgery between 2004 and 2019. The primary outcome was inpatient mortality. The secondary outcomes were surgical complications and postoperative infection. We also evaluated indicators of resource utilization, including mechanical ventilation, intensive care unit (ICU) admission, and postoperative length of stay (LOS). Of 589,098 adolescents, 563 (0.1%) were diagnosed with comorbid OUD (563 were matched on OUD). The prevalence of OUD in adolescents undergoing surgery increased from 0.4 per 1000 cases in 2004 to 1.6 per 1000 cases in 2019, representing an average annual percent change (AAPC) of 9.7% (95% confidence interval [CI], 5.7-13.9; P value < .001). The overall postoperative mortality rate was 0.50% (n = 2941). On univariable analysis, mortality rate was significantly higher in adolescents with comorbid OUD than those without comorbid OUD (3.37% vs 0.50%; P < .001). Among propensity-matched pairs, comorbid OUD diagnosis was associated with an estimated 57% relative increase in the risk of surgical complications (adjusted relative risk [aRR], 1.57; 95% CI, 1.24-2.00; P < .001). The relative risk of postoperative infection was 2-fold higher in adolescents with comorbid OUD than in those without OUD (aRR, 2.02; 95% CI, 1.62-2.51; P < .001). Adolescents with comorbid OUD had an increased risk of ICU admission, mechanical ventilation, and extended postoperative LOS. OUD is becoming increasingly prevalent in adolescents presenting for surgery. Comorbid OUD is an important determinant of surgical complications, postoperative infection, and resource utilization, underscoring the need to consider OUD as a critical, independent risk factor for postsurgical morbidity.

What is the prevalence of and trend in opioid use disorder in the United States from 2010 to 2019? Using multiplier approaches to estimate prevalence for an unknown population size

Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7–7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6–7 million US adolescents and adults.

Prevalence of Opioid Use Disorder among Patients with Cancer-Related Pain: A Systematic Review.

Background: The opioid use disorder is an international public health problem. Over the past 20 years it has been the subject of numerous publications concerning patients treated for chronic pain other than cancer-related. Patients with cancer-related pain are also at risk of opioid use disorder. The primary objective of this literature review was to determine the prevalence of opioid use disorder in patients with cancer-related chronic pain. Its secondary objective was to identify the characteristics of these opioid users. Methods: This is a literature review of studies published over the last twenty years, from 1 January 2000 to 31 December 2020 identified by searching the three main medical databases: Pubmed, Cochrane, and Embase. A meta-analysis took account of between and within-study variability with the use of random-effects models estimated by the DerSimonian and Laird method. Results: The prevalence of opioid use disorder was 8% (1–20%) and of the risk of use disorder was 23.5% (19.5–27.8%) with I2 values of 97.8% and 88.7%, respectively. Conclusions: Further studies are now needed on the prevalence of opioid use disorder in patients treated for cancer-related chronic pain. A screening scale adapted to this patient population is urgently needed.

Barriers and Facilitators to Peer Support Services for Patients With Opioid Use Disorder in the Emergency Department.

There is a high prevalence of opioid use disorder in the United States, and emergency departments (EDs) play multiple vital roles in providing care to help these patients with achieving sobriety, one of which is the application of peer recovery services. This technical report discusses the utilization of peer recovery supporters in the ED and associated barriers. They include but are not limited to the difficult hiring process, referral process challenges for certain populations, difficulty with follow-up data collection, retention of peer recovery supporters, and a lack of ED provider awareness. This article also discussed strategies to address these barriers. Examples include simplifying hospital onboarding processes for peer recovery supporters, obtaining grants to utilize peer recovery services, and using managed care organizations to facilitate follow-up data collection, ED provider education, and discharge planning.

Opioid agonist treatment (OAT) experiences and release plans among federally incarcerated individuals with opioid use disorder (OUD) in Ontario, Canada: a mixed-methods study

BackgroundIncarcerated populations experience an elevated prevalence of opioid use disorder (OUD). Federal correctional institutions in Canada have increasingly treated OUD among correctional populations via opioid agonist treatment (OAT) – an evidence based pharmacotherapy that works to reduce drug use and related health harms. However, there is limited evidence regarding incarcerated individuals’ experiences with institutional-based OAT, as well potential OAT-related community release prospects. This information is important for optimal treatment retention and improved health. To address this knowledge gap, we conducted a longitudinal follow-up study examining OAT-related experiences among federally incarcerated individuals before and after community release. This article focuses on the baseline (pre-release) data.MethodsThis mixed-methods study examined OAT-related experiences and release prospects among n = 46 individuals scheduled for community release, recruited from seven federal prisons located in Ontario, Canada. Participants underwent a comprehensive interviewer-administered on-site assessment, including quantitative and qualitative items. Assessment data was furthermore linked to administrative correctional data. Data were analyzed using thematic qualitative and descriptive quantitative approaches.ResultsParticipants had complex histories with opioid use including related negative health outcomes. Experiences with institutional OAT were divergent and provision was not standardized; those with OAT engagement pre-admission did not experience many challenges, whereas those initiating OAT during incarceration experienced barriers such as treatment waitlists and adverse process experiences. Most participants expressed a preference for buprenorphine-naloxone over methadone, but described difficulties accessing it. Participants were keen to transition into community-based treatment, yet envisaged prospective barriers and facilitators concerning successful reintegration and treatment continuity.ConclusionsMajor barriers towards the current administration of OAT in federal correctional systems in Canada exist, including extensive waitlists, non-standardized practices, and challenges accessing preferred OAT formulations; this contributes to sub-optimal treatment. Eliminating waitlists, standardizing OAT provision, providing additional OAT options, and more comprehensive release planning may be essential for treatment retention and positive outcomes.

Impacts of a Medicaid “lock-in” program on opioid use disorder treatment and services and naloxone dispensing

Background“Lock-in” programs are used by health insurers to reduce the risk of adverse outcomes that can result from overutilization of opioids and other controlled substances. We estimated the association between North Carolina’s Medicaid lock-in program and use of opioid use disorder treatment-related services and naloxone dispensing. MethodsA cohort study of individuals who became eligible for a Medicaid lock-in program between December 2016 and December 2019 (n = 21,220). We compared those enrolled in the program to those eligible but not enrolled. Outcomes included rate of medication for opioid use disorder (MOUD); rate of other substance use disorder treatment (e.g., detoxification); and naloxone dispensing. ResultsThe majority of beneficiaries enrolled in the program had recently received MOUD or other treatment prior to enrollment (59%). After controlling for several potential confounders, the program was associated with slight increases in MOUD use, compared to those eligible but not enrolled (adjusted rate ratio: 1.09, 95% CI: 1.04,1.14). Those enrolled in the program received, on average, 5.4 more days of MOUD per person per year than those eligible but not enrolled (adjusted risk difference: 5.43, 95% CI: 2.49,8.36). Naloxone dispensing was similar and low among those enrolled and not enrolled in the program (7–8%). ConclusionsEnrollment in a Medicaid lock-in program was associated with a small increase in the number of days with substance use disorder treatment. However, given the high prevalence of opioid use disorder among beneficiaries in the program, findings highlighted considerable opportunity for improvement in treatment utilization and retention and a need for increased naloxone dispensing.

Abstract P106: Estimating The Difference In CVD Prevalence Among Patients With OUD Identified By NLP &amp; ICD-10-CM Codes Using EHR Data

Background: Diagnostic codes may underestimate the prevalence of opioid use disorder, especially among complex patients. We estimated the prevalence of cardiovascular disease (CVD) among patients with OUD identified from electronic health records (EHR) from ICD-10-CM diagnostic codes and by natural language processing (NLP) of clinical notes. Methods: We conducted a cross-sectional study using anonymized EHR from one academic medical center, representing inpatient and emergency department visits for 2019. Patients with OUD were identified by ICD-10-CM (ICD) codes and by a rule-based NLP algorithm applied to unstructured EHR clinical notes. CVD was identified using ICD codes for acute myocardial infarction, cardiac arrhythmia, stroke, heart failure, ischemic heart disease (IHD), and infective endocarditis (IE). We estimated crude prevalence of CVD diagnoses (overall and by type) for patients with OUD identified by ICD codes and NLP. Results: Among 22,701 patients, 1,878 were identified as having OUD, of which 1,483 (79%) were identifiable by ICD codes and 395 were only identifiable from clinical notes using NLP (Table 1). Patients identified only by NLP tended to be older, more likely African American and more likely Hispanic relative to patients identified by ICD. The prevalence of any CVD among all patients with OUD was 44.7% (841/1878). Prevalence of IE was very low in both groups. For the other CVD types, between 17-29% of diagnoses were among OUD patients found only by NLP. Conclusion: NLP can recover OUD cases from unstructured notes that cannot be identified by ICD codes alone. If relying on ICD codes alone to identify OUD from EHR, researchers may underestimate prevalence of both OUD and CVD among patients with OUD (e.g. heart failure, IHD), or overestimate the prevalence of conditions, such as IE. * CVD was ascertained via ICD codes. Results are n, row %, for ‘ICD-10-CM’ and ‘NLP only’ columns. For the Total column, results are n, column %.

Developing a cascade of care for opioid use disorder among individuals in jail

IntroductionThe overdose epidemic persists as a public health crisis in the United States. Jails are a critical overdose prevention touchpoint. The risk of overdose postincarceration may be increased if an individual is released without medication for opioid use disorder (MOUD) treatment or transferred to long-term residential treatment. A growing number of studies have examined the difficulties in implementing evidence-based care for opioid use disorder (OUD) in jail settings. MethodsWe use administrative data (July 1, 2020, through September 30, 2020) from four jail facilities that implemented OUD treatment programs. These data included screening data from the Rapid Opioid Dependence Screener (RODS) (n = 2562), along with booking and medication information from jail records, which we used to develop a cascade-of-care. ResultsScreening rates varied dramatically by facility, with integration into the jail records management system showing the best outcomes. The prevalence of OUD identified from the RODS was 8.1% and did not vary significantly by facility. Nearly one third (31.3%) of those identified as having an OUD were dispensed medications, with two-thirds receiving methadone and the remaining third buprenorphine. The average length of stay for all screened individuals was two weeks, compared to two months for those who received an MOUD. ConclusionsScreening for OUD diagnosis is critical to reduce gaps in a cascade-of-care, and our results provide guidance on how to achieve this in jail. Failing to identify OUD and provide MOUD places an individual at an increased risk for fatal overdose. Future studies should consider examining MOUD discharge planning and factors that improve treatment retention following release from incarceration. Our study also illustrates the churn of jail populations and the need for rapid induction of treatment and overdose prevention strategies upon release.