Association of initial opioid prescription duration and an opioid refill by pain diagnosis: Evidence from outpatient settings in ten US health systems.

OBJECTIVE: The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription. METHODS: We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription. RESULTS: Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3-4 days' supply). CONCLUSIONS: Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined.

An individual segmented trajectory approach for identifying opioid use patterns using longitudinal dispensing data.

PURPOSE: The aim of this study is to use electronic opioid dispensing data to develop an individual segmented trajectory approach for identifying opioid use patterns. The resulting opioid use patterns can be used for examining the association between opioid use and drug overdose. METHODS: We retrospectively assembled a cohort of members on long-term opioid therapy (LTOT) between January 1, 2006 and June 30, 2019 who were 18 years and older and enrolled in one of three health care systems in the US. We have developed an individual segmented trajectory analysis for identifying various opioid use patterns by scanning over the follow-up and finding distinct opioid use patterns based on variability measured with coefficient of variation and trends of milligram morphine equivalents levels. RESULTS: Among 31, 865 members who were on LTOT between January 1, 2006 and June 30, 2019, 58.3% were female, and the average age was 55.4 years (STD = 15.4). The study population had 152 557 person-years of follow-up, with an average follow-up of 4.4 years per enrollment per person (STD = 3.4). This novel approach identified up to 13 distinct patterns including 88 756 episodes of "stable" pattern (42.1%) with an average follow-up of 11.2 months, 29 140 episodes of "increasing" pattern (13.8%) with an average follow-up of 6.0 months, 13 201 episodes of ≤10% dose reduction (6.3%) with an average follow-up of 10.4 months, 7286 episodes of 11%-20% dose reduction (3.5%) with an average follow-up of 5.3 months, 4457 episodes of 21%-30% dose reduction (2.1%) with an average follow-up of 4.0 months, and 9903 episodes of >30% dose reduction (4.7%) with an average follow-up of 2.6 months. CONCLUSIONS: A novel approach was developed to identify 13 distinct opioid use patterns using each individual's longitudinal dispensing data and these patterns can be used in examining overdose risk during the time that these patterns are ongoing.

Opioid Overdose Risk Following Hospital Discharge Among Individuals Prescribed Long-Term Opioid Therapy: a Risk Interval Analysis.

BACKGROUND: Individuals prescribed long-term opioid therapy (LTOT) have increased risk of readmission and death after hospital discharge. The risk of opioid overdose during the immediate post-discharge time period is unknown. OBJECTIVE: To examine the association between time since hospital discharge and opioid overdose among individuals prescribed LTOT. DESIGN: Self-controlled risk interval analysis. PARTICIPANTS: Adults prescribed LTOT with at least one hospital discharge at a safety-net health system and a non-profit healthcare organization in Colorado. MAIN MEASURES: We identified individuals prescribed LTOT who were discharged from January 2006 through June 2019. The outcome was a composite of fatal and non-fatal opioid overdoses during a 90-day post-discharge observation period, identified using electronic health record (EHR) and vital statistics data. Risk intervals included days 0-6 after index and subsequent hospital discharges. Control intervals ranged from days 7 to 89 after index discharge and included all other time during the observation period that did not fall within a risk interval or time readmitted during a subsequent hospitalization, which was excluded. Poisson regression was used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for overdose events during risk in comparison to control intervals. KEY RESULTS: We identified 7695 adults (63.3% over 55 years, 59.4% female, 20.3% Hispanic) who experienced 9499 total discharges during the study period. Twenty-one overdoses occurred during their observation periods (1174 per 100,000 person-years [9 in risk, 12 in control]). Overdose risk was significantly higher during the risk interval in comparison to the control interval (IRR 6.92; 95% CI 2.92-16.43). CONCLUSION: During the first 7 days after hospital discharge, individuals prescribed LTOT appear to be at elevated risk for opioid overdose. Clarifying mechanisms of overdose risk may help inform in-hospital and post-discharge prevention strategies.

Update of a Multivariable Opioid Overdose Risk Prediction Model to Enhance Clinical Care for Long-term Opioid Therapy Patients.

BACKGROUND: Clinical opioid overdose risk prediction models can be useful tools to reduce the risk of overdose in patients prescribed long-term opioid therapy (LTOT). However, evolving overdose risk environments and clinical practices in addition to potential harmful model misapplications require careful assessment prior to widespread implementation into clinical care. Models may need to be tailored to meet local clinical operational needs and intended applications in practice. OBJECTIVE: To update and validate an existing opioid overdose risk model, the Kaiser Permanente Colorado Opioid Overdose (KPCOOR) Model, in patients prescribed LTOT for implementation in clinical care. DESIGN, SETTING, AND PARTICIPANTS: The retrospective cohort study consisted of 33, 625 patients prescribed LTOT between January 2015 and June 2019 at Kaiser Permanente Colorado, with follow-up through June 2021. MAIN MEASURES: The outcome consisted of fatal opioid overdoses identified from vital records and non-fatal opioid overdoses from emergency department and inpatient settings. Predictors included demographics, medication dispensings, substance use disorder history, mental health history, and medical diagnoses. Cox proportional hazards regressions were used to model 2-year overdose risk. KEY RESULTS: During follow-up, 65 incident opioid overdoses were observed (111.4 overdoses per 100,000 person-years) in the study cohort, of which 11 were fatal. The optimal risk model needed to risk-stratify patients and to be easily interpreted by clinicians. The original 5-variable model re-validated on the new study cohort had a bootstrap-corrected C-statistic of 0.73 (95% CI, 0.64-0.85) compared to a C-statistic of 0.80 (95% CI, 0.70-0.88) in the updated model and 0.77 (95% CI, 0.66-0.87) in the final adapted 7-variable model, which was also well-calibrated. CONCLUSIONS: Updating and adapting predictors for opioid overdose in the KPCOOR Model with input from clinical partners resulted in a parsimonious and clinically relevant model that was poised for integration in clinical care.

Spinal cord injury and prescribed opioids for pain: a scoping review.

OBJECTIVE: Spinal cord injury (SCI) is a life-altering neurological condition affecting physical and psycho-social functioning and associated high rates of pain. Thus, individuals with SCI may be more likely to be exposed to prescription opioids. A scoping review was conducted to synthesize published research findings on post-acute SCI and prescription opioid use for pain, identify literature gaps, and propose recommendations for future research. METHODS: We searched 6 electronic bibliographic databases (PubMed [MEDLINE], Ovid [MEDLINE], EMBASE, Cochrane Library, CINAHL, PsychNET) for articles published from 2014 through 2021. Terms for "spinal cord injury" and "prescription opioid use" were used. Included articles were in English and peer reviewed. Data were extracted using an electronic database by 2 independent reviewers. Opioid use risk factors for chronic SCI were identified and a gap analysis was performed. RESULTS: Of the 16 articles included in the scoping review, a majority were conducted in the United States (n = 9). Most articles lacked information on income (87.5%), ethnicity (87.5%), and race (75%). Prescription opioid use ranged from 35% to 64% in articles reporting this information (n = 7 articles, n = 3675 participants). Identified risk factors for opioid use included middle age, lower income, osteoarthritis diagnosis, prior opioid use, and lower-level spinal injury. Limited reporting of diversity in study populations, absence of risk of polypharmacy, and limited high quality methodology were identified gaps. CONCLUSIONS: Future research should report data on prescription opioid use in SCI populations, with additional demographics such as race, ethnicity, and income, given their importance to risk outcomes.

Association Between Opioid Dose Reduction Rates and Overdose Among Patients Prescribed Long-Term Opioid Therapy.

BACKGROUND: Tapering long-term opioid therapy is an increasingly common practice, yet rapid opioid dose reductions may increase the risk of overdose. The objective of this study was to compare overdose risk following opioid dose reduction rates of ≤10%, 11% to 20%, 21% to 30%, and >30% per month to stable dosing. METHODS: We conducted a retrospective cohort study in three health systems in Colorado and Wisconsin. Participants were patients ≥18 years of age prescribed long-term opioid therapy between January 1, 2006, and June 30, 2019. Five opioid dosing patterns and drug overdoses (fatal and nonfatal) were identified using electronic health records, pharmacy records, and the National Death Index. Cox proportional hazard regression was conducted on a propensity score-weighted cohort to estimate adjusted hazard ratios (aHRs) for follow-up periods of 1, 3, 6, 9, and 12 months after a dose reduction. RESULTS: In a cohort of 17 540 patients receiving long-term opioid therapy, 42.7% of patients experienced a dose reduction. Relative to stable dosing, a dose reduction rate of >30% was associated with an increased risk of overdose and the aHR estimates decreased as the follow-up increased; the aHRs for the 1-, 6- and 12-month follow-ups were 5.33 (95% CI, 1.98-14.34), 1.81 (95% CI,1.08-3.03), and 1.49 (95% CI, 0.97-2.27), respectively. The slower tapering rates were not associated with overdose risk. CONCLUSIONS: Patients receiving long-term opioid therapy exposed to dose reduction rates of >30% per month had increased overdose risk relative to patients exposed to stable dosing. Results support the use of slow dose reductions to minimize the risk of overdose.

Opioid Use Disorder Treatment Initiation and Continuation: a Qualitative Study of Patients Who Received Addiction Consultation and Hospital-Based Providers.

BACKGROUND: Hospitalizations related to opioid use disorder (OUD) are rising. Addiction consultation services (ACS) increasingly provide OUD treatment to hospitalized patients, but barriers to initiating and continuing medications for OUD remain. We examined facilitators and barriers to hospital-based OUD treatment initiation and continuation from the perspective of patients and healthcare workers in the context of an ACS. METHODS: In this qualitative study, we sought input using key informant interviews and focus groups from patients who received care from an ACS during their hospitalization and from hospitalists, pharmacists, social workers, and nurses who work in the hospital setting. A multidisciplinary team coded and analyzed transcripts using a directed content analysis. FINDINGS: We conducted 20 key informant interviews with patients, nine of whom were interviewed following hospital discharge and 12 of whom were interviewed during a rehospitalization. We completed six focus groups and eight key informant interviews with hospitalists and hospital-based medical staff (n = 62). Emergent themes related to hospital-based OUD treatment included the following: the benefit of an ACS to facilitate OUD treatment engagement; expanded use of methadone or buprenorphine to treat opioid withdrawal; the triad of hospitalization, self-efficacy, and easily accessible, patient-centered treatment motivates change in opioid use; adequate pain control and stabilization of mental health conditions among patients with OUD contributed to opioid agonist therapy (OAT) continuation; and stable housing and social support are prerequisites for OAT uptake and continuation. CONCLUSION: Modifiable factors which facilitate hospital-based OUD treatment initiation and continuation include availability of in-hospital addiction expertise to offer easily accessible, patient-centered treatment and the use of methadone or buprenorphine to manage opioid withdrawal. Further research and public policy efforts are urgently needed to address reported barriers to hospital-based OUD treatment initiation and continuation which include unstable housing, poorly controlled chronic medical and mental illness, and lack of social support.

Naloxone Co-Dispensing with Opioids: a Cluster Randomized Pragmatic Trial.

BACKGROUND: Although naloxone prevents opioid overdose deaths, few patients prescribed opioids receive naloxone, limiting its effectiveness in real-world settings. Barriers to naloxone prescribing include concerns that naloxone could increase risk behavior and limited time to provide necessary patient education. OBJECTIVE: To determine whether pharmacy-based naloxone co-dispensing affected opioid risk behavior. Secondary objectives were to assess if co-dispensing increased naloxone acquisition, increased patient knowledge about naloxone administration, and affected opioid dose and other substance use. DESIGN: Cluster randomized pragmatic trial of naloxone co-dispensing. SETTING: Safety-net health system in Denver, Colorado, between 2017 and 2020. PARTICIPANTS: Seven pharmacies were randomized. Pharmacy patients (N=768) receiving opioids were followed using automated data for 10 months. Pharmacy patients were also invited to complete surveys at baseline, 4 months, and 8 months; 325 survey participants were enrolled from November 15, 2017, to January 8, 2019. INTERVENTION: Intervention pharmacies implemented workflows to co-dispense naloxone while usual care pharmacies provided usual services. MAIN MEASURES: Survey instruments assessed opioid risk behavior; hazardous drinking; tobacco, cannabis, and other drug use; and knowledge. Naloxone dispensings and opioid dose were evaluated using pharmacy data among pharmacy patients and survey participants. Intention-to-treat analyses were conducted using generalized linear mixed models accounting for clustering at the pharmacy level. KEY RESULTS: Opioid risk behavior did not differ by trial group (P=0.52; 8-month vs. baseline adjusted risk ratio [ARR] 1.07; 95% CI 0.78, 1.47). Compared with usual care pharmacies, naloxone dispensings were higher in intervention pharmacies (ARR 3.38; 95% CI 2.21, 5.15) and participant knowledge increased (P=0.02; 8-month vs. baseline adjusted mean difference 1.05; 95% CI 0.06, 2.04). There was no difference in other substance use by the trial group. CONCLUSION: Co-dispensing naloxone with opioids effectively increased naloxone receipt and knowledge but did not increase self-reported risk behavior. TRIAL REGISTRATION: Registered at ClinicalTrials.gov ; Identifier: NCT03337100.

The impact of access to addiction specialist on attitudes, beliefs and hospital-based opioid use disorder related care: A survey of hospitalist physicians.

BACKGROUND: Hospitalizations for complications related to opioid use disorder (OUD) are increasing. Hospitalists care for most hospitalized patients in the United States, yet little is known about their attitudes, beliefs, and clinical practices regarding OUD-related care.Methods: We distributed an online survey to hospitalists in the United States to measure how access to addiction specialists affected attitudes and beliefs regarding hospital-based OUD care, OUD screening practices, naloxone prescribing, and buprenorphine initiation.Results: Among 262 respondents, 67.9% (n = 178) reported having access to addiction specialists. While 84.5% (n = 221) reported often or always caring for patients with OUD, 48.2% (n = 126) rarely or never screened for OUD, 57.1% (n = 149) rarely or never prescribed or recommended naloxone as harm reduction, and 88.9% (n = 233) rarely or never initiated buprenorphine. In multivariable analyses, compared to hospitalists without access to addiction specialists, hospitalist with access to addiction specialists were more likely to feel supported to screen and refer patients to treatment (aOR = 4.4, 95% CI 2.1 - 9.1; ρ < 0.001), to be aware of local treatment resources (aOR = 3.4, 95% CI 1.8 - 6.3; ρ < 0.001), and refer patients to treatment (aOR = 3.0, 95% CI 1.7 - 5.6; ρ < 0.001).Conclusions: Many hospitalists do not provide life-saving treatment to patients with OUD. Access to addiction specialists may increase provision of OUD-related care by hospitalists.

A national survey of barriers and facilitators to medications for opioid use disorder among legal-involved veterans in the Veterans Health Administration.

Background: Medications for opioid use disorder (MOUD) are clinically effective at treating OUD among legal-involved populations. However, research shows that legal-involved veterans who receive care through the VHA have lower rates of MOUD use compared to non-legal-involved veterans. Education may be a key factor in intervention strategies to improve MOUD access. This study was a national survey of VHA staff to identify barriers to and facilitators of MOUD, as well as MOUD-related education needs for VHA staff, community partners, criminal justice partners, and legal-involved veterans. Method: A 98-item online survey was conducted to examine VHA staff perspectives (N = 218) around needed education, barriers to, and facilitators of MOUD for legal-involved veterans. Descriptive statistics were conducted and linear regression analyses were used to evaluate differences in perceptions by respondents' current position at the VHA and their VHA facility's rate of provision of MOUD among legal-involved veterans. Results: Respondents endorsed a need for education in all areas of MOUD (e.g., existing medications for the treatment of OUD) for VHA staff and providers, community partners, criminal justice partners, and legal-involved veterans. VHA staff perceived barriers to MOUD for legal-involved veterans to include stigma and complicated guidelines around MOUD and OUD treatment. Facilities with low rates of MOUD use highlighted barriers including MOUD conflicting with the philosophy of the local VHA facility and provider stigma toward patients with OUD. Perceptions of efficacy of MOUD differed by respondents' current position at the VHA such that substance use disorder treatment providers perceived buprenorphine and methadone as more effective compared to Veterans Justice Specialists. Conclusion: The results of this study suggest a need for an educational intervention emphasizing the evidence supporting use of MOUD as a lack of knowledge about these medications was considered a barrier to access, whereas gaining education about MOUD was a facilitator to access. Education strategies specifically tailored to address VHA facility-level differences may help address barriers to MOUD experienced by legal-involved veterans.

Clinical documentation of patient-reported medical cannabis use in primary care: Toward scalable extraction using natural language processing methods.

Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.

Prevalence and Medication Treatment of Opioid Use Disorder Among Primary Care Patients with Hepatitis C and HIV.

BACKGROUND: Hepatitis C and HIV are associated with opioid use disorders (OUD) and injection drug use. Medications for OUD can prevent the spread of HCV and HIV. OBJECTIVE: To describe the prevalence of documented OUD, as well as receipt of office-based medication treatment, among primary care patients with HCV or HIV. DESIGN: Retrospective observational cohort study using electronic health record and insurance data. PARTICIPANTS: Adults ≥ 18 years with ≥ 2 visits to primary care during the study (2014-2016) at 6 healthcare systems across five states (CO, CA, OR, WA, and MN). MAIN MEASURES: The primary outcome was the diagnosis of OUD; the secondary outcome was OUD treatment with buprenorphine or oral/injectable naltrexone. Prevalence of OUD and OUD treatment was calculated across four groups: HCV only; HIV only; HCV and HIV; and neither HCV nor HIV. In addition, adjusted odds ratios (AOR) of OUD treatment associated with HCV and HIV (separately) were estimated, adjusting for age, gender, race/ethnicity, and site. KEY RESULTS: The sample included 1,368,604 persons, of whom 10,042 had HCV, 5821 HIV, and 422 both. The prevalence of diagnosed OUD varied across groups: 11.9% (95% CI: 11.3%, 12.5%) for those with HCV; 1.6% (1.3%, 2.0%) for those with HIV; 8.8% (6.2%, 11.9%) for those with both; and 0.92% (0.91%, 0.94%) among those with neither. Among those with diagnosed OUD, the prevalence of OUD medication treatment was 20.9%, 16.0%, 10.8%, and 22.3%, for those with HCV, HIV, both, and neither, respectively. HCV was not associated with OUD treatment (AOR = 1.03; 0.88, 1.21), whereas patients with HIV had a lower probability of OUD treatment (AOR = 0.43; 0.26, 0.72). CONCLUSIONS: Among patients receiving primary care, those diagnosed with HCV and HIV were more likely to have documented OUD than those without. Patients with HIV were less likely to have documented medication treatment for OUD.

Identifying naloxone administrations in electronic health record data using a text-mining tool.

Background: Effective and efficient methods are needed to identify naloxone administrations within electronic health record (EHR) data to conduct overdose surveillance and research. The objective of this study was to develop and validate a text-mining tool to identify naloxone administrations in EHR data. Methods: Clinical notes stored in databases between January 2017 and March 2018 were used to iteratively develop a text-mining tool to identify naloxone administrations. The first iteration of the tool used broad search terms. Then, after reviewing clinical notes of overdose encounters, we developed a list of phrases that described naloxone administrations to inform iteration two. While validating iteration two, additional phrases were found, which were then added to inform the final iteration. The comparator was an administrative code query extracted from the EHR. Medical record review was used to identify true positives. The primary outcome was the positive predictive values (PPV) of the second iteration, final iteration, and administrative code query. Results: Iteration two, the final iteration, and the administrative code had PPVs of 84.3% (95% confidence interval [CI] 78.6-89.0%), 83.8% (95% CI 78.6-88.2%), and 57.1% (95% CI 47.1-66.8%), respectively. Both iterations of the tool had a significantly higher PPV than the administrative code (p < 0.001). Conclusions: A text-mining tool improved the identification of naloxone administrations in EHR data from less than 60% with the administrative code to greater than 80% with both versions of the tool. Text-mining tools can inform the use of more sophisticated informatics methods, which often require significant time, resource, and expertise investment.

Opioid Use and Chronic Infections: The Value of Addressing the Syndemic in Correctional Settings Via Telemedicine Guidance and Broader Use of Long-Acting Medications.

In the United States, we are experiencing linked epidemics (a syndemic) of substance use disorders (SUDs) and infections associated with drug use, including unsafe injecting and unsafe sex in exchange for drugs or money. Current drug laws, together with risk-taking behavior among persons with SUDs, contribute to disproportionately high prevalences of these conditions in correctional settings. Detection and treatment of diseases with a high impact on public health are best addressed in the settings where such conditions are most prevalent (ie, jails and prisons for SUDs and chronic infections). The effectiveness, safety, cost of care. and public health impact of these conditions can be improved by means of broader screening and expanded access to specialty consultations through telemedicine/telehealth, along with broader use of long-acting medications for the treatment of human immunodeficiency virus and SUDs. Expanding telemedicine/telehealth, first for specialties which do not require advanced technology (eg, infectious diseases, addictions), can eventually lead to further advancements in correctional healthcare.

Barriers to Medications for Opioid Use Disorder Among Veterans Involved in the Legal System: a Qualitative Study.

BACKGROUND: Veterans involved in the legal system are at high risk for overdose but have lower receipt of medications for opioid use disorder than other veterans. OBJECTIVE: The study aimed to understand barriers to medication access from the perspective of legally involved veterans with opioid use disorder and people who work with these veterans in the Veterans Health Administration (VHA) and the legal system. DESIGN: This national qualitative study interviewed veterans and stakeholders from 14 geographically diverse VHA facilities to explore perceptions of barriers to medications for opioid use disorder. PARTICIPANTS: Participants included veterans with a history of opioid use disorder and legal involvement (n = 18), VHA Veterans Justice Programs Specialists (n = 15), VHA and community substance use disorder treatment providers (n = 5), and criminal justice staff (n = 12). APPROACH: We conducted interviews based on the Consolidated Framework for Implementation Research. Interview transcripts were analyzed using a team-based approach. KEY RESULTS: Four key barriers, noted by group, were identified: (1) a preference for counseling along with or instead of medications (veterans, Specialists, treatment providers, criminal justice staff); (2) concerns about veterans using medications without a prescription, selling them, or providing them to others (veterans, Specialists, treatment providers, criminal justice staff); (3) concerns about perceived stigma towards medication use (veterans, Specialists, treatment providers, criminal justice staff); and (4) concerns about medication discontinuation after recurrent opioid use (veterans, criminal justice staff). A fifth theme, education, was noted by all stakeholders except providers as important to facilitating use of medications for opioid use disorder. All five themes mapped to the framework construct of knowledge and beliefs about the intervention. CONCLUSIONS: Based on identified barriers, interventions focused on enhancing medication knowledge, reducing stigma towards use of medications, and increasing knowledge that opioid use may recur during treatment may help increase access to medication for veterans with legal involvement.

Modifying and Evaluating the Opioid Overdose Knowledge Scale for Prescription Opioids: A Pilot Study of the Rx-OOKS.

OBJECTIVE: To develop a validated instrument that measures knowledge about prescription opioid overdose. METHODS: Within an integrated health care system, we adapted, piloted, and tested the reliability and predictive validity of a modified Opioid Overdose Knowledge Scale (OOKS) instrument specific to prescription opioids (Rx-OOKS) with a patient population prescribed long-term opioid therapy and potentially at risk of opioid overdose. We used an interdisciplinary team approach and patient interviews to adapt the instrument. We then piloted the survey on a patient sample and assessed it using Cronbach's alpha and logistic regression. RESULTS: Rx-OOKS (N = 56) resulted in a three-construct, 25-item instrument. Internal consistency was acceptable for the following constructs: "signs of an overdose" (10 items) at α = 0.851, "action to take with opioid overdose" (seven items) at α = 0.692, and "naloxone use knowledge" (eight items) at α = 0.729. One construct, "risks of an overdose" (three items), had an α of 0.365 and was subsequently eliminated from analysis due to poor performance. We conducted logistic regression to determine if any of the constructs was strongly associated with future naloxone receipt. Higher scores on "actions to take in an overdose" had nine times the odds of receiving naloxone (odds ratio [OR] = 9.00, 95% confidence interval [CI] = 1.42-57.12); higher "naloxone use knowledge" scores were 15.8 times more likely to receive naloxone than those with lower scores (OR = 15.83, 95% CI = 1.68-149.17). CONCLUSIONS: The Rx-OOKS survey instrument can reliably measure knowledge about prescription opioid overdose recognition and naloxone use. Further, knowledge about actions to take during an opioid overdose and naloxone use were associated with future receipt of naloxone.

Mixed method evaluation of Relational Team Development (RELATED) to improve team-based care for complex patients with mental illness in primary care.

BACKGROUND: Patients with mental illness are frequently treated in primary care, where Primary Care Providers (PCPs) report feeling ill-equipped to manage their care. Team-based models of care improve outcomes for patients with mental illness, but multiple barriers limit adoption. Barriers include practical issues and psychosocial factors associated with the reorganization of care. Practice facilitation can improve implementation, but does not directly address the psychosocial factors or gaps in PCP skills in managing mental illness. To address these gaps, we developed Relational Team Development (RELATED). METHODS: RELATED is an implementation strategy combining practice facilitation and psychology clinical supervision methodologies to improve implementation of team-based care. It includes PCP-level clinical coaching and a team-level practice change activity. We performed a preliminary assessment of RELATED with a convergent parallel mixed method study in 2 primary care clinics in an urban Federally Qualified Health Center in Southwest, USA, 2017-2018. Study participants included PCPs, clinic staff, and patient representatives. Clinic staff and patients were recruited for the practice change activity only. Primary outcomes were feasibility and acceptability. Feasibility was assessed as ease of recruitment and implementation. Acceptability was measured in surveys of PCPs and staff and focus groups. We conducted semi-structured focus groups with 3 participant groups in each clinic: PCPs; staff and patients; and leadership. Secondary outcomes were change in pre- post- intervention PCP self-efficacy in mental illness management and team-based care. We conducted qualitative observations to better understand clinic climate. RESULTS: We recruited 18 PCPs, 17 staff members, and 3 patient representatives. We ended recruitment early due to over recruitment. Both clinics developed and implemented practice change activities. The mean acceptability score was 3.7 (SD=0.3) on a 4-point Likert scale. PCPs had a statistically significant increase in their mental illness management self-efficacy [change = 0.9, p-value= <.01]. Focus group comments were largely positive, with PCPs requesting additional coaching. CONCLUSIONS: RELATED was feasible and highly acceptable. It led to positive changes in PCP self-efficacy in Mental Illness Management. If confirmed as an effective implementation strategy, RELATED has the potential to significantly impact implementation of evidence-based interventions for patients with mental illness in primary care.

Designing the relational team development intervention to improve management of mental health in primary care using iterative stakeholder engagement.

BACKGROUND: Team-based models of care are efficacious in improving outcomes for patients with mental and physical illnesses. However, primary care clinics have been slow to adopt these models. We used iterative stakeholder engagement to develop an intervention to improve the implementation of team-based care for this complex population. METHODS: We developed the initial framework for Relational Team Development (RELATED) from a qualitative study of Primary Care Providers' (PCPs') experiences treating mental illness and a literature review of practice facilitation and psychology clinical supervision. Subsequently, we surveyed 900 Colorado PCPs to identify factors associated with PCP self-efficacy in management of mental illness and team-based care. We then conducted two focus groups for feedback on RELATED. Lastly, we convened an expert panel to refine the intervention. RESULTS: We developed RELATED, a two-part intervention delivered by a practice facilitator with a background in clinical psychology. The facilitator observes PCPs during patient visits and provides individualized coaching. Next, the facilitator guides the primary care team through a practice change activity with a focus on relational team dynamics. CONCLUSION: The iterative development of RELATED using stakeholder engagement offers a model for the development of interventions tailored to the needs of these stakeholders. TRIAL REGISTRATION: Not applicable.

Development and evaluation of a standardized research definition for opioid overdose outcomes.

Background: Increasing epidemiologic and intervention research is being conducted on opioid overdose, a serious and potentially fatal outcome. However, there is little consensus on how to verify opioid overdose outcomes for research purposes. To ensure reproducibility, minimize misclassification, and permit data harmonization across studies, standardized and consistent overdose definitions are needed. The aims were to develop a case criteria classification scheme based on information commonly available in medical records and to compare it with reviewing physician clinical impression and simple encounter documentation. Methods: In 2 large health systems, we developed a case criteria classification scheme for opioid overdose based on prior literature, expert opinion, and pilot testing with sample medical records. We then identified emergency department and hospital encounters (n = 259) with at least 1 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code representing a broad range of opioid and non-opioid related poisonings. Physicians conducted structured medical record reviews to identify the proposed case criteria and generate a clinical impression, and trained abstractors verified documentation. We then compared the case criteria classification scheme with clinical impression and encounter documentation. Results: We developed a quantitative opioid overdose case criteria classification scheme that included 3 sets of major criteria and 9 minor criteria (supporting documentation). For the encounters identified using poisoning codes, the proportion verified as opioid overdoses using the case criteria classification scheme, clinical impression, and encounter documentation ranged from 50.4% to 52.7% at one site and 55.5% to 67.2% at the second site. Discrepancies across approaches and sites related to differences in available records and documentation of clinical signs of overdose. Conclusions: We propose a novel case criteria classification scheme for opioid overdose that could be used to rigorously and consistently define overdose across multiple research settings. However, prior to widespread use, further refinement and validation are needed.