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.

Prescription Opioid Dose Reductions and Potential Adverse Events: a Multi-site Observational Cohort Study in Diverse US Health Systems.

BACKGROUND: In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events. OBJECTIVE: Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality). DESIGN: This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of  ≥ 50 during six consecutive months. PATIENTS: We identified 60,040 non-cancer patients with  ≥ one 2-month dose reduction period (600,234 unique dose reduction periods). MAIN MEASURES: Analyses examined associations between dose reduction levels (1- < 15%, 15- < 30%, 30- < 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics. KEY RESULTS: Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1- < 15%, dose reductions of 30- < 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09-1.81), and all-cause mortality (OR 1.39, 95% CI 1.16-1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81-0.85). Dose reductions of 15- < 30%, compared to 1- < 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05-1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92-0.95), but were not associated with opioid overdose and all-cause mortality. CONCLUSIONS: Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored.

Cannabis Use for Medical Reasons Among Patients in a Large California Health Care System After Legalization of Nonmedical Use.

OBJECTIVE: In 2018, California legalized the sale of cannabis for adult nonmedical use. To understand use of cannabis after legalization, we surveyed a stratified random sample of adults in a large health system (ages 19-64 years) with and without documented chronic pain about their reasons for cannabis use from November 2018 to March 2019. METHOD: We compared patients with and without chronic pain on measures for medical, nonmedical, pain-related, and mental health-related cannabis use based on self-reported symptoms. RESULTS: Patients with chronic pain reported higher past-year medical use (34.6%) compared to patients without chronic pain (22.8%), past-year pain-related use (29.7% vs. 15.5%), and past-year mental health-related use (24.8% vs. 18.9%). In adjusted models, relative to patients without chronic pain, those with chronic pain had a 6.2% (95% CI [0.010, 0.11]) higher probability of past-year medical cannabis use and an 8.0% (95% CI [0.035, 0.13]) higher probability of past-year pain-related cannabis use. CONCLUSIONS: Compared to patients without chronic pain, patients with chronic pain were more likely to use cannabis for reasons related to medical and pain symptoms in the past year. Use for past-year mental health symptoms did not differ between these two groups. Cannabis use among patients with and without chronic pain is common after legalization for nonmedical use, and understanding reasons for use is important to improve overall patient care.

Development and implementation of a prescription opioid registry across diverse health systems.

Objective: Develop and implement a prescription opioid registry in 10 diverse health systems across the US and describe trends in prescribed opioids between 2012 and 2018. Materials and Methods: Using electronic health record and claims data, we identified patients who had an outpatient fill for any prescription opioid, and/or an opioid use disorder diagnosis, between January 1, 2012 and December 31, 2018. The registry contains distributed files of prescription opioids, benzodiazepines and other select medications, opioid antagonists, clinical diagnoses, procedures, health services utilization, and health plan membership. Rates of outpatient opioid fills over the study period, standardized to health system demographic distributions, are described by age, gender, and race/ethnicity among members without cancer. Results: The registry includes 6 249 710 patients and over 40 million outpatient opioid fills. For the combined registry population, opioid fills declined from a high of 0.718 per member-year in 2013 to 0.478 in 2018, and morphine milligram equivalents (MMEs) per fill declined from 985 MMEs per fill in 2012 to 758 MMEs in 2018. MMEs per member declined from 692 MMEs per member in 2012 to 362 MMEs per member in 2018. Conclusion: This study established a population-based opioid registry across 10 diverse health systems that can be used to address questions related to opioid use. Initial analyses showed large reductions in overall opioid use per member among the combined health systems. The registry will be used in future studies to answer a broad range of other critical public health issues relating to prescription opioid use.

Opioid misuse as a coping behavior for unmet mental health needs among U.S. adults.

BACKGROUND: Self-medication theory posits that opioids may be misused to cope with mental or emotional distress, especially if distress is not treated. Opioid misuse may lead to opioid use disorder, overdose, and death. We estimated the risk of opioid misuse associated with unmet mental health treatment needs (UMHN). METHODS: We used 2015-2018 data on U.S. adults from the National Survey of Drug Use and Health (n = 165,767). UMHN was the perceived need for mental health services in the past year without service receipt. The primary dependent variable was past year prescription opioid misuse (POM). Secondary analyses estimated POM and/or heroin misuse risk. Logistic regressions estimated the predicted probability for POM, controlling for demographics, social factors, a major depressive episode (MDE), and overall health. We also tested whether the association of UMHN on the predicted probability of POM varied by MDE. RESULTS: UMHN was associated with a 4.6 percentage point higher predicted probability of POM (p < 0.001; 95 % CI 0.04-0.05) and a 4.9 percentage point higher predicted probability of POM and/or heroin (p < 0.001; 95 % CI 0.04-0.06) compared to adults who accessed mental health services. MDE was associated with a significantly greater risk of POM (p < 0.001). POM risk was greater for adults potentially experiencing social isolation. CONCLUSION: Targeted mental health support strategies may reduce the likelihood of POM initiation and episodes. Future research should investigate the relationship between unmet mental health needs and initiation of POM episodes.

Identifying Patient Strengths Instruments and Examining Their Relevance for Chronic Disease Management: A Systematic Review.

INTRODUCTION: Most health care focuses on patients' deficits to encourage behavior change. A strengths-based approach, which relies on identifying patient strengths, has great potential to facilitate behavior change for chronic disease management. Little is known about instruments used to assess patient strengths. We conducted a systematic review to identify validated instruments that assess personal strengths by using a theory elaboration approach. METHODS: We searched 8 databases including Web of Science, Cumulative Index of Nursing and Allied Health (CINAHL), and PsycINFO (through July 2019) to identify peer reviewed, English-language studies that described strength-based instruments. Thereafter, we evaluated the validity and reliability of the instruments according to 18 Scientific Advisory Committee of the Medical Outcome Trust (SACMOT) criteria, and used an inductive, iterative editing process to identify constructs measured by the instruments. RESULTS: We identified 26 instruments that met our inclusion criteria. The instruments were validated in various clinical and nonclinical populations. Only 4 instruments met most of the SACMOT criteria for validation. We extracted 91 unique constructs that fell into 3 domains: inner strengths (49), external strengths (13), and personality constructs (29). CONCLUSION: A limited number of reliable and valid instruments are available to assess strengths for the adult population, particularly for clinical populations. Internal strengths can be leveraged to improve patient health; however, the development and validation of additional instruments to capture personal strengths is necessary to examine the multilevel influence of external strengths on individual behaviors and well-being.

The association between the supply of select nonpharmacologic providers for pain and use of nonpharmacologic pain management services and initial opioid prescribing patterns for Medicare beneficiaries with persistent musculoskeletal pain.

OBJECTIVE: To test the relationship between the supply of select nonpharmacologic providers (physical therapy (PT) and mental health (MH)) and use of nonpharmacologic services among older adults with a persistent musculoskeletal pain (MSP) episode. DATA SOURCES/STUDY SETTING: Claims data from a 5 percent random sample of Medicare beneficiaries enrolled fee-for-service (2007-2014) and the Area Health Resource File (AHRF). STUDY DESIGN: This retrospective study used generalized estimating equations to estimate the association between the county nonpharmacologic provider supply and individual service use with opioid prescriptions filled during Phase 1 (first three months of an episode) and Phase 2 (three months following Phase 1). DATA COLLECTION/EXTRACTION METHODS: We identified beneficiaries (>65 years) with ≥2 MSP diagnoses ≥90 days apart and no opioid prescription six months before the first pain diagnosis (N = 69 456). Beneficiaries' county characteristics were assigned using the AHRF. PRINCIPAL FINDINGS: About 13.9 percent of beneficiaries used PT, 1.8 percent used MH services, and 10.7 percent had an opioid prescription during the first three months of a persistent MSP episode. An additional MH provider/10 000 people/county [aOR: 0.97, 95% CI: 0.96-0.98] and PT/10 000 people/county [aOR: 0.98, 95% CI: 0.97-1.00] was associated with lower odds of filling an opioid prescription in Phase 1. An additional MH provider/10 000 people/county [aOR: 0.97, 95% CI: 0.96-0.98] and PT use in Phase 1 [aOR: 0.62, 95% CI: 0.58-0.67] were associated with lower odds of filling an opioid prescription in Phase 2. The associations between the supply of providers and nonpharmacologic service use in Phase 1 and Phase 1 opioid prescriptions significantly differed by metropolitan and rural counties (P-value: .019). CONCLUSIONS: Limited access to nonpharmacologic services is associated with opioid prescriptions at the onset of a persistent MSP episode. Initiating PT at the onset of an episode may reduce future opioid use. Strategies for engaging beneficiaries in nonpharmacologic services should be tailored for metropolitan and rural counties.

The role of substance use disorders in experiencing a repeat opioid overdose, and substance use treatment patterns among patients with a non-fatal opioid overdose.

BACKGROUND: A non-fatal opioid overdose (NFOO) increases the risk of another overdose and identifies high-risk patients. We estimated the risk of repeat opioid overdose for patients with and without substance use disorder (SUD) diagnoses and the change in substance use treatment utilization rates associated with the first NFOO. METHODS: We selected patients (>18 years of age) from Kaiser Permanente Northern California with a NFOO between 2009-2016 (n = 3,992). Cox proportional hazards models estimated the 1-year risk of opioid overdose associated with SUD diagnoses (opioid, alcohol, cannabis, amphetamine, sedative, and cocaine), controlling for patient characteristics. Among patients with an index NFOO, we calculated monthly utilization rates for outpatient substance use services and buprenorphine before and after the index overdose. Interrupted time series models estimated the change in level and trend in utilization rates associated with the index overdose. RESULTS: Approximately 7.2 % of patients had a repeat opioid overdose during the year after the index NFOO. The only SUD diagnosis significantly associated with greater risk of repeat overdose was opioid use disorder (OUD) (aHR: 1.51; 95 % CI: 1.13-2.01). Before the index overdose, 4.16 % of patients received outpatient substance use services and 1.32 % received buprenorphine. The index overdose was associated with a 5.94 % (standard error: 0.77 %) absolute increase in outpatient substance use services and a 1.29 % (standard error: 0.15 %) increase in buprenorphine. CONCLUSION: Patients with a NFOO and OUD are vulnerable to another overdose. Low initiation rates for substance use treatment after a NFOO indicate a need to address patient, provider, and system barriers.

The Association Between the Supply of Nonpharmacologic Providers, Use of Nonpharmacologic Pain Treatments, and High-risk Opioid Prescription Patterns Among Medicare Beneficiaries With Persistent Musculoskeletal Pain.

BACKGROUND: Opioids are prescribed more frequently than nonpharmacologic treatments for persistent musculoskeletal pain (MSP). We estimate the association between the supply of physical therapy (PT) and mental health (MH) providers and early nonpharmacologic service use with high-risk opioid prescriptions among Medicare beneficiaries with persistent MSP. RESEARCH DESIGN: We retrospectively studied Medicare beneficiaries (>65 y) enrolled in Fee-for-Service and Part D (2007-2014) with a new persistent MSP episode and no opioid prescription during the prior 6 months. Independent variables were nonpharmacologic provider supply per capita and early nonpharmacologic service use (any use during first 3 mo). One year outcomes were long-term opioid use (LTOU) (≥90 days' supply) and high daily dose (HDD) (≥50 mg morphine equivalent). We used multinomial regression and generalized estimating equations and present adjusted odds ratios (aORs). RESULTS: About 2.4% of beneficiaries had LTOU; 11.9% had HDD. The supply of MH providers was not associated with LTOU and HDD. Each additional PT/10,000 people/county was associated with greater odds of LTOU [aOR: 1.06; 95% confidence interval (CI), 1.01-1.11). Early MH use was associated with lower odds of a low-risk opioid use (aOR: 0.81; 95% CI, 0.68-0.96), but greater odds of LTOU (aOR: 1.93; 95% CI, 1.28-2.90). Among beneficiaries with an opioid prescription, early PT was associated with lower odds of LTOU (aOR: 0.75; 95% CI, 0.64-0.89), but greater odds of HDD (aOR: 1.25; 95% CI, 1.15-1.36). CONCLUSIONS: The benefits of nonpharmacologic services on opioid use may be limited. Research on effective delivery of nonpharmacologic services to reduce high-risk opioid use for older adults with MSP is needed.

Long-term opioid therapy definitions and predictors: A systematic review.

PURPOSE: This review sought to (a) describe definitions of long-term opioid therapy (LTOT) outcome measures, and (b) identify the predictors associated with the transition from short-term opioid use to LTOT for opioid-naïve individuals. METHODS: We conducted a systematic review of the peer-reviewed literature (January 2007 to July 2018). We included studies examining opioid use for more than 30 days. We classified operationalization of LTOT based on criteria used in the definitions. We extracted LTOT predictors from multivariate models in studies of opioid-naïve individuals. RESULTS: The search retrieved 5,221 studies, and 34 studies were included. We extracted 41 unique variations of LTOT definitions. About 36% of definitions required a cumulative duration of opioid use of 3 months. Only 17% of definitions considered consecutive observation periods, 27% used days' supply, and no definitions considered dose. We extracted 76 unique predictors of LTOT from seven studies of opioid-naïve patients. Common predictors included pre-existing comorbidities (21.1%), non-opioid prescription medication use (13.2%), substance use disorders (10.5%), and mental health disorders (10.5%). CONCLUSIONS: Most LTOT definitions aligned with the chronic pain definition (pain more than 3 months), and used cumulative duration of opioid use as a criterion, although most did not account for consistent use. Definitions were varied and rarely accounted for prescription characteristics, such as days' supply. Predictors of LTOT were similar to known risk factors of opioid abuse, misuse, and overdose. As LTOT becomes a central component of quality improvement efforts, researchers should incorporate criteria to identify consistent opioid use to build the evidence for safe and appropriate use of prescription opioids.

Characteristics of New Opioid Use Among Medicare Beneficiaries: Identifying High-Risk Patterns.

BACKGROUND: Opioid prescription patterns, including long-term use, multiple prescribers, and high opioid doses, increase the risk for adverse outcomes; however, previous research in older adult populations has primarily described opioid dose patterns using average daily dose measures or using very high thresholds (i.e., > 100 morphine milligram equivalents [MME] per day). OBJECTIVE: To describe prescription patterns by peak dose among older adults who have newly initiated opioid use in 2014 and describe long-term opioid use and the use of multiple pharmacies and prescribers among those with peak opioid doses over 50 and over 90 MME per day. METHODS: This was a retrospective cohort study of Medicare Part D prescription claims data (5% sample) for beneficiaries aged 65 years and older who were prescribed ≥ 1 opioid prescription in 2014 and did not have an opioid prescription in the preceding 180 days. Within a 1-year period of follow-up, we used prescription claims to characterize individuals' opioid exposure, measuring long-term opioid use (≥ 90 days of continuous opioid supply), unique opioid prescribers, and unique opioid-dispensing pharmacies. Peak MME was defined as the maximum daily MME received across all overlapping opioid prescriptions in the observation period. RESULTS: 144,127 beneficiaries without an opioid prescription in the previous 6 months filled ≥ 1 opioid prescription in 2014. During the 1-year follow-up period, 6.5% of beneficiaries transitioned to long-term opioid use; 39.5% received opioid prescriptions from > 1 prescriber; 18.1% filled opioid prescriptions from > 1 pharmacy; and 21.8% had a peak MME of 50-89. Among the 28.1% of beneficiaries exposed to a peak MME > 50, 8.6% developed long-term opioid use; 7.0% had 3 or more opioid dispensing pharmacies; and 28.0% had 3 or more opioid prescribers. Among the 6.2% of beneficiaries exposed to a peak MME ≥ 90, 18.5% developed long-term opioid use; 13.0% had 3 or more opioid dispensing pharmacies; and 39.6% had 3 or more opioid prescribers. CONCLUSIONS: High doses of opioids were prescribed for about one quarter (28%) of Medicare beneficiaries with new opioid use in 2014. Having multiple opioid prescribers or multiple opioid dispensing pharmacies was common, especially among those prescribed higher doses. These prescription patterns can be particularly helpful to identify older adults with increased opioid-related risk. DISCLOSURES: No funding supported this study. Raman reports research grants from GlaxoSmithKline not related to this study. Roberts was supported by a CTSA grant from NCATS awarded to the University of Kansas Medical Center for Frontiers: The Heartland Institute for Clinical and Translational Research (#KL2TR000119). The other authors have no potential conflicts to report.