Evaluation of a Medicaid performance improvement project to reduce high-dose opioid prescriptions.

BACKGROUND: In 2015, Oregon's Medicaid program implemented a performance improvement project to reduce high-dose opioid prescribing across its 16 coordinated care organizations (CCOs). The objective of this study was to evaluate the effect of that program on prescription opioid use and outcomes. METHODS: Using Medicaid claims data from 2014 to 2017, we conducted interrupted time-series analyses to examine changes in the prescription opioid use and overdose rates before (July 2014 to June 2015) and after (January 2016 to December 2017) implementation of Oregon's high-dose policy initiative (July 2015 to December 2015). Prescribing outcomes were: 1) total opioid prescriptions 2) high-dose [> 90 morphine milligram equivalents per day] opioid prescriptions, and 3) proportion of opioid prescriptions that were high-dose. Opioid overdose outcomes included emergency department visits or hospitalizations that involved an opioid-related poisoning (total, heroin-involved, non-heroin involved). Analyses were performed at the state and CCO level. RESULTS: There was an immediate reduction in high dose opioid prescriptions after the program was implemented (- 1.55 prescription per 1000 enrollee; 95% CI - 2.26 to - 0.84; p < 0.01). Program implementation was also associated with an immediate drop (- 1.29 percentage points; 95% CI - 1.94 to - 0.64 percentage points; p < 0.01) and trend reduction (- 0.23 percentage point per month; 95% CI - 0.33 to - 0.14 percentage points; p < 0.01) in the monthly proportion of high-dose opioid prescriptions. The trend in total, heroin-involved, and non-heroin overdose rates increased significantly following implementation of the program. CONCLUSIONS: Although Oregon's high-dose opioid performance improvement project was associated with declines in high-dose opioid prescriptions, rates of opioid overdose did not decrease. Policy efforts to reduce opioid prescribing risks may not be sufficient to address the growing opioid crisis.

Linkage of public health and all payer claims data for population-level opioid research.

OBJECTIVE: Our objective is to describe how we combine, at an individual level, multiple administrative datasets to create a Comprehensive Opioid Risk Registry (CORR). The CORR will characterize the role that individual characteristics, household characteristics, and community characteristics have on an individual's risk of opioid use disorder or opioid overdose. DATA SOURCES: Study data sources include the voluntary Oregon All Payer Claims Database (APCD), American Community Survey Census Data, Oregon Death Certificate data, Oregon Hospital Discharge Data (HDD), and Oregon Prescription Drug Monitoring (PDMP) Data in 2013-2018. STUDY DESIGN: To create the CORR we first prepared the APCD data set by cleaning and geocoding addresses, creating a community grouper and adding census indices, creating household grouper, and imputing patient race. Then we deployed a probabilistic linkage methodology to incorporate other data sources maintaining compliance with strict data governance regulations. DATA COLLECTION/EXTRACTION METHODS: Administrative datasets were obtained through an executed data use agreement with each data owner. The APCD served as the population universe to which all other data sources were linked. PRINCIPAL FINDINGS: There were 3 628 992 unique people in the APCD over the entire study period. We identified 968 767 unique households in 2013 and 1 209 236 in 2018, and geocoded patient addresses representing all census tracts in Oregon. Census, death certificate, HDD, and PDMP datasets were successfully linked to this population universe. CONCLUSIONS: This methodology can be replicated in other states and may also apply to a broad array of health services research topics.

Prescription Opioid Dispensing Patterns Prior to Heroin Overdose in a State Medicaid Program: a Case-Control Study.

BACKGROUND: A large proportion of individuals who use heroin report initiating opioid use with prescription opioids. However, patterns of prescription opioid use preceding heroin-related overdose have not been described. OBJECTIVE: To describe prescription opioid use in the year preceding heroin overdose. DESIGN: Case-control study comparing prescription opioid use with a heroin-involved overdose, non-heroin-involved opioid overdose, and non-overdose controls from 2015 to 2017. PARTICIPANTS: Oregon Medicaid beneficiaries with linked administrative claims, vital statistics, and prescription drug monitoring program data. MAIN MEASURES: Opioid, benzodiazepine, and other central nervous system depressant prescriptions preceding overdose; among individuals with one or more opioid prescription, we assessed morphine milligram equivalents per day, overlapping prescriptions, prescriptions from multiple prescribers, long-term use, and discontinuation of long-term use. KEY RESULTS: We identified 1458 heroin-involved overdoses (191 fatal) and 2050 non-heroin-involved opioid overdoses (266 fatal). In the 365 days prior to their overdose, 45% of individuals with a heroin-involved overdose received at least one prescribed opioid compared with 78% of individuals who experienced a non-heroin-involved opioid overdose (p < 0.001). For both heroin- and non-heroin-involved overdose cases, the likelihood of receiving an opioid increased with age. Among heroin overdose cases with an opioid dispensed, the rate of multiple pharmacy use was the only high-risk opioid pattern that was greater than non-overdose controls (adjusted odds ratio 3.2; 95% confidence interval 1.48 to 6.95). Discontinuation of long-term opioid use was not common prior to heroin overdose and not higher than discontinuation rates among non-overdose controls. CONCLUSIONS: Although individuals with a heroin-involved overdose were less likely to receive prescribed opioids in the year preceding their overdose relative to non-heroin opioid overdose cases, prescription opioid use was relatively common and increased with age. Discontinuation of long-term prescription opioid use was not associated with heroin-involved overdose.

Physician Responses to Enhanced Prescription Drug Monitoring Program Profiles.

OBJECTIVE: Many states have begun implementing enhancements to PDMP patient profiles such as summaries or graphics to highlight issues of concern and enhance comprehension. The purpose of this study was to examine how physicians respond to sample enhanced PDMP profiles based on patient vignettes. DESIGN: Brief semistructured interviews with physicians. SETTING: Three national medical conferences for targeted specialties. SUBJECTS: Ninety-three physicians practicing in primary care, emergency medicine, or pain management. METHODS: We presented participants with one of three patient vignettes with corresponding standard and enhanced PDMP profiles and conducted brief interviews. RESULTS: Findings indicated that enhanced profiles could increase ease of comprehension, reduce time burden, and aid in communicating with patients about opioid risks. Physicians also expressed concern about liability for prescribing when the enhanced profile indicates risk and cautioned against any implication that risk warnings should override clinical judgment based on the patient's complete medical history or presenting condition. Physicians emphasized the need for transparency of measures and evidence of validation of risk scores. We found little indication that enhanced profiles would change opioid prescribing decisions, though decisions varied by physician. CONCLUSIONS: Our study underscores the importance of involving prescribers in developing and testing PDMP profile enhancements, as well as providing guidance in the interpretation and clinical use of enhanced profiles. Reduced time burden is an important benefit to consider as the number of states mandating PDMP use increases.

Impact of the RESPOND Toolkit on community pharmacists' opioid safety attitudes, self-efficacy, and knowledge.

OBJECTIVE: Pharmacists are well positioned to reduce risks from opioid-prescribing but often lack resources and training to effectively support these activities. The Resources Encouraging Safe Prescription Opioid and Naloxone Dispensing (RESPOND) Toolkit is an educational package developed to provide community pharmacists with a comprehensive education program and practice resources on prescription drug misuse, prescription drug monitoring programs (PDMPs), and naloxone dispensing. Our objective was to evaluate the effectiveness of the RESPOND Toolkit to improve pharmacists' knowledge and assess changes in pharmacists' attitudes and beliefs toward opioid use disorder (OUD) and PDMPs across a diverse pool of Oregon community pharmacists. METHODS: Pharmacists were recruited using an electronic mailing list of Oregon-licensed pharmacists. Pharmacists were asked to complete a preintervention survey, 3 online educational modules with pre- and post-module quizzes (optional), and a postintervention survey. Data were analyzed using paired t tests, chi-square analyses, and effect size calculations (Cohen's d). RESULTS: A total of 131 pharmacists completed the 3 educational modules and postintervention survey. Respondents were aged 37.6 ± 11.0 (mean ± SD) years and mostly frontline pharmacy staff (n = 86; 65.6%) with 10.5 ± 11.6 years of pharmacy experience. Pharmacists' knowledge and attitudes toward OUD, perceived behavioral control to address OUD, resources to address OUD, and perceptions regarding PDMP-associated difficulties improved significantly as a result of the intervention (all P < 0.001). In addition, 120 pharmacists completed the optional module quizzes, and aggregate knowledge assessment scores improved significantly (P < 0.001). CONCLUSION: The RESPOND Toolkit is an effective and scalable training resource for community pharmacists, with the potential to promote behavioral shifts that support opioid safety among patients. The results demonstrated improved attitudes, knowledge, and perceived behavioral control. Future work on the RESPOND Toolkit should evaluate the effect of implementation on pharmacist clinical activities and dispensing outcomes.

Opioid-Prescribing Continuity and Risky Opioid Prescriptions.

We aimed to better understand the association between opioid-prescribing continuity, risky prescribing patterns, and overdose risk. For this retrospective cohort study, we included patients with long-term opioid use, pulling data from Oregon's Prescription Drug Monitoring Program (PDMP), vital records, and hospital discharge registry. A continuity of care index (COCI) score was calculated for each patient, and we defined metrics to describe risky prescribing and overdose. As prescribing continuity increased, likelihood of filling risky opioid prescriptions and overdose hospitalization decreased. Prescribing continuity is an important factor associated with opioid harms and can be calculated using administrative pharmacy data.

Opioid Prescribing Patterns and Patient Outcomes by Prescriber Type in the Oregon Prescription Drug Monitoring Program.

Objective: Prescription drug monitoring programs (PDMPs) were created to facilitate responsible use of controlled substances. In Oregon, physicians, physician's assistants (MDs/DOs/PAs), dentists, nurse practitioners (NPs), and naturopathic physicians (NDs) may prescribe opioids, but differences in prescribing practices, patient mix, and patient outcomes among prescriber types have not been characterized. Methods: De-identified Oregon PDMP data from October 2011 through October 2014 were linked with vital records and a statewide hospital discharge registry. The disciplines of registered prescribers were identified by board affiliations. Prescription profiles associated with opioid overdose risk were tabulated for patients with at least one registered prescriber. Opioid-related hospitalizations and deaths were identified using ICD-9 and ICD-10 codes. Results: There were 5,935 prescribers registered during the study period. Patients of NPs or NDs received more high-risk opioid prescriptions than patients of MDs/DOs/PAs. For example, they received greater proportions of high-dose prescriptions (NP 12.9%, ND 15%, MD/DO/PA 11.1%), and had greater opioid-related hospitalization (NP 1.7%, ND 3.1%, MD/DO/PA 1.2%; P < 0.005 for all). However, patients of NPs or NDs were also more likely to have four or more prescribers (NP 45.3%, ND 58.5%, MD/DO/PA 27.1%), and most of their patients' high-risk opioid prescriptions came from prescribers in other disciplines. Conclusion: Our analysis suggests significant differences in opioid prescription profiles and opioid-related hospitalization and mortality among patients receiving opioid prescriptions from nurse practitioners, naturopathic physicians, or medical clinicians in Oregon. However, these differences appear largely due to differences in patient mix between provider types rather than discipline-specific prescribing practices.

Pharmacists' Role in Opioid Safety: A Focus Group Investigation.

Objective: The pharmacist's role and responsibilities in addressing the opioid epidemic have yet to be clearly defined, particularly from the patient's point of view. This qualitative study explores the pharmacist's role in promoting opioid safety from the perspective of pharmacists and patients. Design: Focus groups. Setting: Patient groups were held in person, and pharmacist groups were held online. Subjects: Oregon pharmacists (N = 19, Mage = 39.0 years, range = 26-57 years, 58% female) and patients (N = 18, Mage = 60.1 years, range = 30-77 years, 71% female) with current experience dispensing or receiving opioid medications. Methods: Pharmacists were asked about the challenges and opportunities for opioid safety monitoring and prescription dispensing. Patients were asked about their experiences accessing care, medications, and safety information. Focus group data were analyzed by a multidisciplinary team using an immersion-crystallization approach. Results: Pharmacists and patients agreed that pharmacists are responsible for medication safety. Pharmacists expressed discomfort filling potentially high-risk opioid prescriptions and noted barriers such as lack of clinical information and discomfort policing high-risk prescribing. Patients were concerned about pharmacists potentially overstepping their professional responsibilities by interfering with prescribers' clinical decisions. Conclusions: Feedback from both pharmacists and patient participants suggests that there is uncertainty in the degree to which pharmacists can and should confront the prescription opioid epidemic directly. Ambiguities in the pharmacist's role may be best clarified through structured training promoting enhanced between-party communication.

Association Between Initial Opioid Prescribing Patterns and Subsequent Long-Term Use Among Opioid-Naïve Patients: A Statewide Retrospective Cohort Study.

BACKGROUND: Long-term efficacy of opioids for non-cancer pain is unproven, but risks argue for cautious prescribing. Few data suggest how long or how much opioid can be prescribed for opioid-naïve patients without inadvertently promoting long-term use. OBJECTIVE: To examine the association between initial opioid prescribing patterns and likelihood of long-term use among opioid-naïve patients. DESIGN: Retrospective cohort study; data from Oregon resident prescriptions linked to death certificates and hospital discharges. PARTICIPANTS: Patients filling opioid prescriptions between October 1, 2012, and September 30, 2013, with no opioid fills for the previous 365 days. Subgroup analyses examined patients under age 45 who did not die in the follow-up year, excluding most cancer or palliative care patients. MAIN MEASURES: Exposure: Numbers of prescription fills and cumulative morphine milligram equivalents (MMEs) dispensed during 30 days following opioid initiation ("initiation month"). OUTCOME: Proportion of patients with six or more opioid fills during the subsequent year ("long-term users"). KEY RESULTS: There were 536,767 opioid-naïve patients who filled an opioid prescription. Of these, 26,785 (5.0 %) became long-term users. Numbers of fills and cumulative MMEs during the initiation month were associated with long-term use. Among patients under age 45 using short-acting opioids who did not die in the follow-up year, the adjusted odds ratio (OR) for long-term use among those receiving two fills versus one was 2.25 (95 % CI: 2.17, 2.33). Compared to those who received < 120 total MMEs, those who received between 400 and 799 had an OR of 2.96 (95 % CI: 2.81, 3.11). Patients initiating with long-acting opioids had a higher risk of long-term use than those initiating with short-acting drugs. CONCLUSIONS: Early opioid prescribing patterns are associated with long-term use. While patient characteristics are important, clinicians have greater control over initial prescribing. Our findings may help minimize the risk of inadvertently initiating long-term opioid use.

Research to support optimization of prescription drug monitoring programs.

PURPOSE: Research is needed to evaluate the impact of prescription drug monitoring programs (PDMPs). This paper describes research priorities for PDMPs that were initially discussed at a 2015 meeting of PDMP administrators, researchers, public health officials, and other stakeholders. METHODS: Meeting participants defined the current landscape of PDMP research and identified research gaps. Research priorities were grouped by theme. RESULTS: Prescription drug monitoring program research priorities were identified for 3 key areas: individual patient health outcomes, prescriber use and decision making, and population-level outcomes. Research areas for individual patient outcomes include examining drug-use thresholds that best predict risk for overdose or substance use disorder and unintended consequences of PDMP use. Proposed research on prescriber PDMP use include evaluating how enhancements to the content and format of PDMP reports informs clinical decision making and optimal clinician actions in response to a concerning PDMP report. Finally, research topics related to population-level outcomes include measuring the impact of PDMP policies on the incidence of substance misuse and harms and assessing the return on investment for these databases. CONCLUSIONS: The clinical, public health, and economic impacts of PDMPs must be evaluated, using both quantitative and qualitative methods. In addition to assessing patient outcomes, qualitative research should examine how clinicians use and interpret PDMP information. Research should also examine the impact of PDMP features and policies on prescriber utilization. Comparative analyses across states with differing PDMP policies should be conducted to inform best practices.

Clinicians' Use of Prescription Drug Monitoring Programs in Clinical Practice and Decision-Making.

Objectives: Little is known about clinicians' use of prescription drug monitoring program (PDMP) profiles in decision-making. The objective of this qualitative study was to understand how clinicians use, interpret, and integrate PDMP profiles with other information in making clinical decisions. Design: Qualitative interviews of clinician PDMP users. Setting: Oregon registrants in the state's PDMP. Subjects: Thirty-three clinicians practicing in primary care, emergency medicine, pain management, psychiatry, dentistry, and surgery. Methods: We conducted semistructured telephone interviews with PDMP users. A multidisciplinary team used a grounded theory approach to identify patterns of PDMP use and how PDMP profiles influence clinical decisions. Results: PDMP use varied from consistent monitoring to checking the PDMP only on suspicion of misuse, with inconsistent use reported particularly among short-term prescribers. Primary care clinicians reported less routine use with existing pain patients than with new patients. In response to worrisome PDMP profiles with new patients, participants reported declining to prescribe, except in the case of acute, verifiable conditions. Long-term prescribers reported sometimes continuing prescriptions for existing patients depending on perceived patient intent, honesty, and opioid misuse risk. Some long-term prescribers reported discharging patients from their practices due to worrisome PDMP profiles; others expressed strong ethical grounds for retaining patients but discontinuing controlled substances. Conclusion: Greater consistency is needed in use of PDMP in monitoring existing patients and in conformity to guidelines against discharging patients from practice. Research is needed to determine optimal approaches to interpreting PDMP profiles in relation to clinical judgment, patient screeners, and other information.

Preparing a prescription drug monitoring program data set for research purposes.

PURPOSE: To develop a complete and consistent prescription drug monitoring program (PDMP) data set for use by drug safety researchers in evaluating patterns of high-risk use and potential abuse of scheduled drugs. METHODS: Using publically available data references from the US Food and Drug Administration and the Centers for Disease Control and Prevention, we developed a strategic methodology to assign drug categories based on pharmaceutical class for the majority of prescriptions in the PDMP data set. We augmented data elements required to calculate morphine milligram equivalents and assigned duration of action (short-acting or long acting) properties for a majority of opioids in the data set. RESULTS: About 10% of prescriptions in the PDMP data set did not have a vendor-assigned drug category, and 20% of opioid prescriptions were missing data needed to calculate risk metrics. Using inclusive methods, 19 133 167 (>99.9%) of prescriptions in the PDMP data set were assigned a drug category. For the opioid category, augmenting data elements resulted in 10 760 669 (99.8%) having required values to calculate morphine milligram equivalents and evaluate duration of action properties. CONCLUSIONS: Drug safety researchers who require a complete and consistent PDMP data set can use the methods described here to ensure that prescriptions of interest are assigned consistent drug categories and complete opioid risk variable values. Copyright © 2016 John Wiley & Sons, Ltd.

Clinical Styles and Practice Policies: Influence on Communication with Patients Regarding Worrisome Prescription Drug Monitoring Program Data.

OBJECTIVES: Clinician communication with patients regarding worrisome findings in Prescription Drug Monitoring Programs (PDMPs) may influence patient responses and subsequent care. The authors studied the range of approaches clinicians report when communicating with patients in this situation and how practice policies and procedures may influence this communication. DESIGN: Qualitative interviews of clinician PDMP users. SETTING: Oregon registrants in the state's PDMP. SUBJECTS: Thirty-three clinicians practicing in pain management, emergency medicine, primary care, psychiatry, dentistry, and surgery. METHODS: The authors conducted semi-structured interviews via telephone with clinicians who routinely used the PDMP. A multidisciplinary team used a grounded theory approach to identify ways clinicians reported using information from the PDMP when communicating with patients, and policies that influenced that communication. RESULTS: Clinicians reported using a range of approaches for communicating about PDMP results, from openly sharing, to questioning patients without disclosing access to the PDMP, to avoiding the conversation. Clinicians also reported practice policies and procedures that influenced communication with their patients about prescribing and ongoing care, including policies that normalized use of the PDMP with all patients and those that facilitated difficult conversations by providing a rationale not to prescribe in certain circumstances. CONCLUSION: Clinicians' self-reported approaches to sharing PDMP findings and communicating prescribing decisions with patients vary and may be facilitated by appropriate practice policies. Such communication may have implications for patient engagement and alliance building. More research is needed to identify best practices and potential guidelines for effectively communicating about PDMP findings, as this may enhance health outcomes.

How clinicians use prescription drug monitoring programs: a qualitative inquiry.

OBJECTIVES: Prescription drug monitoring programs (PDMPs) are now active in most states to assist clinicians in identifying potential controlled drug misuse, diversion, or excessive prescribing. Little is still known about the ways in which they are incorporated into workflow and clinical decision making, what barriers continue to exist, and how clinicians are sharing PDMP results with their patients. DESIGN: Qualitative data were collected through online focus groups and telephone interviews. SETTING: Clinicians from pain management, emergency and family medicine, psychiatry/behavioral health, rehabilitation medicine, internal medicine and dentistry participated. PATIENTS: Thirty-five clinicians from nine states participated. METHODS: We conducted two online focus groups and seven telephone interviews. A multidisciplinary team then used a grounded theory approach coupled with an immersion-crystallization strategy for identifying key themes in the resulting transcripts. RESULTS: Some participants, mainly from pain clinics, reported checking the PDMP with every patient, every time. Others checked only for new patients, for new opioid prescriptions, or for patients for whom they suspected abuse. Participants described varied approaches to sharing PDMP information with patients, including openly discussing potential addiction or safety concerns, avoiding discussion altogether, and approaching discussion confrontationally. Participants described patient anger or denial as a common response and noted the role of patient satisfaction surveys as an influence on prescribing. CONCLUSION: Routines for accessing PDMP data and how clinicians respond to it vary widely. As PDMP use becomes more widespread, it will be important to understand what approaches are most effective for identifying and addressing unsafe medication use.

Opioid Overdose After Medication for Opioid Use Disorder Initiation Following Hospitalization or ED Visit.

Importance: Hospitalizations related to opioid use disorder (OUD) represent an opportunity to initiate medication for OUD (MOUD). Objective: To assess whether starting MOUD after a hospitalization or emergency department (ED) visit is associated with the odds of fatal and nonfatal opioid overdose at 6 and 12 months. Design, Setting, and Participants: This population-based cohort study used data from the Oregon Comprehensive Opioid Risk Registry, which links all payer claims data to other administrative health datasets, for individuals aged 18 years or older who had diagnosis codes related to OUD recorded at an index ED visit or hospitalization from January 2017 to December 2019. Data were analyzed between May 2023 and January 2024. Exposures: Receipt of MOUD within the 7 days after an OUD-related hospital visit. Main Outcomes and Measures: The primary outcome was fatal or nonfatal overdose at 6 and 12 months after discharge. Sample characteristics, including age, sex, insurance plan, number of comorbidities, and opioid-related overdose events, were stratified by receipt or nonreceipt of MOUD within 7 days after an OUD-related hospital visit. A logistic regression model was used to investigate the association between receipt of MOUD and having an opioid overdose event. Results: The study included 22 235 patients (53.1% female; 25.0% aged 25-39 years) who had an OUD-related hospital visit during the study period. Overall, 1184 patients (5.3%) received MOUD within 7 days of their ED visit or hospitalization. Of these patients, 683 (57.7%) received buprenorphine, 463 (39.1%) received methadone, and 46 (3.9%) received long-acting injectable naltrexone. Patients who received MOUD within 7 days after discharge had lower adjusted odds of fatal or nonfatal overdose at 6 months compared with those who did not (adjusted odds ratio [AOR], 0.63; 95% CI, 0.41-0.97). At 12 months, there was no difference in adjusted odds of fatal or nonfatal overdose between these groups (AOR, 0.79; 95% CI, 0.58-1.08). Patients had a lower risk of fatal or nonfatal overdose at 6 months associated with buprenorphine use (AOR, 0.50; 95% CI, 0.27-0.95) but not with methadone use (AOR, 0.57; 95% CI, 0.28-1.17). Conclusions and Relevance: In this cohort study of individuals with an OUD-related hospital visit, initiation of MOUD was associated with reduced odds of opioid-related overdose at 6 months. Hospitals should consider implementing programs and protocols to offer initiation of MOUD to patients with OUD who present for care.

Beyond the 5-year recovery mark: Perspectives of researchers with lived and living experience on public engagement and discourse.

There has been growing attention toward including people with lived and living experience (PWLLE) with substance use, substance use disorders, and recovery in public-facing activities. The goals of including PWLLE in sharing their perspectives often include demonstrating that recovery is possible, destigmatizing and humanizing people who have substance use experiences, and leveraging their lived experience to illuminate a particular topic or issue. Recently, the National Council for Mental Wellbeing issued a set of guidelines entitled, "Protecting Individuals with Lived Experience in Public Disclosure," which included a "Lived Experience Safeguard Scale." We offer the present commentary to bolster some of the ideas presented by the Council and to articulate suggested changes to this guidance, with the goal of reducing unintentional gatekeeping and stigma. Specifically, we offer that there are numerous problems with the recommendation to only invite people who have "five or more years of sustained recovery" to contribute to public discourse. The idea of perceived stability after five years of abstinence is not new to us or the field. We suggest that this idea excludes people who have experienced the present rapidly changing substance use landscape, people who have briefly returned to use, some young people, and people with living experience who also can valuably contribute to public discourse. We offer alternative guidelines to the National Council for Mental Wellbeing and others seeking to promote practices that are inclusive to the diversity of PWLLE.

Peer Recovery Support Services Across the Continuum: In Community, Hospital, Corrections, and Treatment and Recovery Agency Settings - A Narrative Review.

In this narrative review, we outline the literature describing the history, training, certification, and role of peer recovery support specialists working with people with substance use disorders at different stages of active use and recovery. We explore the impact of peer recovery support specialists serving people in various settings, including the community, hospitals and emergency departments, jails and prisons, and treatment and recovery agencies; and describes considerations for future expansion of peer recovery support services, including supervision needs, compassion fatigue and burnout, and scope of practice. Finally, we make recommendations to support the broad implementation of peer recovery support services as a sustainable, cohesive, and replicable component of harm reduction and addiction services. We also make recommendations for research to continue to evaluate peer recovery support specialist interventions across settings and outcomes.

Factors Associated With Opioid Overdose After an Initial Opioid Prescription.

Importance: The opioid epidemic continues to be a public health crisis in the US. Objective: To assess the patient factors and early time-varying prescription-related factors associated with opioid-related fatal or nonfatal overdose. Design, Setting, and Participants: This cohort study evaluated opioid-naive adult patients in Oregon using data from the Oregon Comprehensive Opioid Risk Registry, which links all payer claims data to other health data sets in the state of Oregon. The observational, population-based sample filled a first (index) opioid prescription in 2015 and was followed up until December 31, 2018. Data analyses were performed from March 1, 2020, to June 15, 2021. Exposures: Overdose after the index opioid prescription. Main Outcomes and Measures: The outcome was an overdose event. The sample was followed up to identify fatal or nonfatal opioid overdoses. Patient and prescription characteristics were identified. Prescription characteristics in the first 6 months after the index prescription were modeled as cumulative, time-dependent measures that were updated monthly through the sixth month of follow-up. A time-dependent Cox proportional hazards regression model was used to assess patient and prescription characteristics that were associated with an increased risk for overdose events. Results: The cohort comprised 236 921 patients (133 839 women [56.5%]), of whom 667 (0.3%) experienced opioid overdose. Risk of overdose was highest among individuals 75 years or older (adjusted hazard ratio [aHR], 3.22; 95% CI, 1.94-5.36) compared with those aged 35 to 44 years; men (aHR, 1.29; 95% CI, 1.10-1.51); those who were dually eligible for Medicaid and Medicare Advantage (aHR, 4.37; 95% CI, 3.09-6.18), had Medicaid (aHR, 3.77; 95% CI, 2.97-4.80), or had Medicare Advantage (aHR, 2.18; 95% CI, 1.44-3.31) compared with those with commercial insurance; those with comorbid substance use disorder (aHR, 2.74; 95% CI, 2.15-3.50), with depression (aHR, 1.26; 95% CI, 1.03-1.55), or with 1 to 2 comorbidities (aHR, 1.32; 95% CI, 1.08-1.62) or 3 or more comorbidities (aHR, 1.90; 95% CI, 1.42-2.53) compared with none. Patients were at an increased overdose risk if they filled oxycodone (aHR, 1.70; 95% CI, 1.04-2.77) or tramadol (aHR, 2.80; 95% CI, 1.34-5.84) compared with codeine; used benzodiazepines (aHR, 1.06; 95% CI, 1.01-1.11); used concurrent opioids and benzodiazepines (aHR, 2.11; 95% CI, 1.70-2.62); or filled opioids from 3 or more pharmacies over 6 months (aHR, 1.38; 95% CI, 1.09-1.75). Conclusions and Relevance: This cohort study used a comprehensive data set to identify patient and prescription-related risk factors that were associated with opioid overdose. These findings may guide opioid counseling and monitoring, the development of clinical decision-making tools, and opioid prevention and treatment resources for individuals who are at greatest risk for opioid overdose.

Association between treatment setting and outcomes among oregon medicaid patients with opioid use disorder: a retrospective cohort study.

BACKGROUND: Residential treatment is a common approach for treating opioid use disorder (OUD), however, few studies have directly compared it to outpatient treatment. The objective of this study was to compare OUD outcomes among individuals receiving residential and outpatient treatment. METHODS: A retrospective cohort study used linked data from a state Medicaid program, vital statistics, and the Substance Abuse and Mental Health Services Administration (SAMHSA) Treatment Episodes Dataset (TEDS) to compare OUD-related health outcomes among individuals treated in a residential or outpatient setting between 2014 and 2017. Multivariable Cox proportional hazards and logistic regression models examined the association between treatment setting and outcomes (i.e., opioid overdose, non-overdose opioid-related and all-cause emergency department (ED) visits, hospital admissions, and treatment retention) controlling for patient characteristics, co-morbidities, and use of medications for opioid use disorders (MOUD). Interaction models evaluated how MOUD use modified associations between treatment setting and outcomes. RESULTS: Of 3293 individuals treated for OUD, 957 (29%) received treatment in a residential facility. MOUD use was higher among those treated as an outpatient (43%) compared to residential (19%). The risk of opioid overdose (aHR 1.39; 95% CI 0.73-2.64) or an opioid-related emergency department encounter or admission (aHR 1.02; 95% CI 0.80-1.29) did not differ between treatment settings. Independent of setting, MOUD use was associated with a significant reduction in overdose risk (aHR 0.45; 95% CI 0.23-0.89). Residential care was associated with greater odds of retention at 6-months (aOR 1.71; 95% CI 1.32-2.21) but not 1-year. Residential treatment was only associated with improved retention for individuals not receiving MOUD (6-month aOR 2.05; 95% CI 1.56-2.71) with no benefit observed in those who received MOUD (aOR 0.75; 95% CI 0.46-1.29; interaction p = 0.001). CONCLUSIONS: Relative to outpatient treatment, residential treatment was not associated with reductions in opioid overdose or opioid-related ED encounters/hospitalizations. Regardless of setting, MOUD use was associated with a significant reduction in opioid overdose risk.