Opioid Poisonings in Washington State Medicaid: Trends, Dosing, and Guidelines

Outcomes After a Statewide Policy to Improve Evidence-Based Treatment of Back Pain Among Medicaid Enrollees in Oregon

BACKGROUND

A novel Oregon Medicaid policy guiding back pain management combined opioid restrictions with emphasis on non-opioid and non-pharmacologic therapies.

OBJECTIVE

To examine the effect of the policy on prescribing, health outcomes, and health service utilization.

DESIGN

Using Medicaid enrollment, medical and prescription claims, prescription drug monitoring program, and vital statistics files, we analyzed the policy's association with selected outcomes using interrupted time series models.

SUBJECTS

Adult Medicaid patients with back pain enrolled between 2014 and 2018.

INTERVENTION

The Oregon Medicaid back pain policy.

MAIN MEASURES

Opioid and non-opioid medication prescribing, procedural care, substance use and mental health conditions, and outpatient and inpatient healthcare utilization.

KEY RESULTS

The policy was associated with decreases in the percentage of Medicaid enrollees with back pain receiving any opioids (- 2.68 percentage points [95% CI - 3.14, - 2.23] level, - 1.01 pp [95% CI - 1.1, - 0.92] slope), days of short-acting opioid use (- 0.4 days [95% CI - 0.53, - 0.26] slope), receipt of more than 7 days of short-acting opioids (- 2.36 pp [95% CI - 2.76, - 1.95] level, - 0.91 pp [95% CI - 1, - 0.83] slope), chronic opioid use (- 1.27 pp [95% CI - 1.59, - 0.94] level, - 0.46 [95% CI - 0.53, - 0.39 slope), and spinal surgeries and procedures. Among secondary outcomes, we found no increase in opioid overdose and a small, statistically significant trend decrease in opioid use disorders. There were small increases in non-opioid substance use and mental health diagnoses and visits but no increase in self-harm.

CONCLUSIONS

A state Medicaid policy emphasizing evidence-based back pain management was associated with decreases in opioid prescribing, spinal surgeries, and opioid use disorder trends, but also short-term increases in mental health encounters and an increase in non-opioid substance use disorder trends. Such policies may help reinforce evidence-based care, but must be designed with consideration of potential harms.

Opioid therapy trajectories of patients with chronic non-cancer pain over 1 year of follow-up after initiation of short-acting opioid formulations

OBJECTIVE

This study compared opioid utilization trajectories of persons initiating tramadol, short-acting hydrocodone, or short-acting oxycodone, and it characterized opioid dose trajectories and type of opioid in persistent opioid therapy subsamples.

METHODS

A retrospective cohort study of adults with chronic non-cancer pain who were initiating opioid therapy was conducted with the IQVIA PharMetrics® Plus for Academics data (2008-2018). Continuous enrollment was required for 6 months before ("baseline") and 12 months after ("follow-up") the first opioid prescription ("index date"). Opioid therapy measures were assessed every 7 days over follow-up. Group-based trajectory modeling (GBTM) was used to identify trajectories for any opioid and total morphine milligram equivalent measures, and longitudinal latent class analysis was used for opioid therapy type.

RESULTS

A total of 40 276 tramadol, 141 023 hydrocodone, and 45 221 oxycodone initiators were included. GBTM on any opioid therapy identified 3 latent trajectories: early discontinuers (tramadol 39.0%, hydrocodone 54.1%, oxycodone 61.4%), late discontinuers (tramadol 37.9%, hydrocodone 39.4%, oxycodone 33.3%), and persistent therapy (tramadol 6.7%, hydrocodone 6.5%, oxycodone 5.3%). An additional fourth trajectory, intermittent therapy (tramadol 16.4%), was identified for tramadol initiators. Of those on persistent therapy, 2687 individuals were on persistent therapy with tramadol, 9169 with hydrocodone, and 2377 with oxycodone. GBTM on opioid dose resulted in 6 similar trajectory groups in each persistent therapy group. Longitudinal latent class analysis on opioid therapy type identified 6 latent classes for tramadol and oxycodone and 7 classes for hydrocodone.

CONCLUSION

Opioid therapy patterns meaningfully differed by the initial opioid prescribed, notably the presence of intermittent therapy among tramadol initiators and higher morphine milligram equivalents and prescribing of long-acting opioids among oxycodone initiators.

Outcome class imbalance and rare events: An underappreciated complication for overdose risk prediction modeling

BACKGROUND AND AIMS

Low outcome prevalence, often observed with opioid-related outcomes, poses an underappreciated challenge to accurate predictive modeling. Outcome class imbalance, where non-events (i.e. negative class observations) outnumber events (i.e. positive class observations) by a moderate to extreme degree, can distort measures of predictive accuracy in misleading ways, and make the overall predictive accuracy and the discriminatory ability of a predictive model appear spuriously high. We conducted a simulation study to measure the impact of outcome class imbalance on predictive performance of a simple SuperLearner ensemble model and suggest strategies for reducing that impact.

DESIGN, SETTING, PARTICIPANTS

Using a Monte Carlo design with 250 repetitions, we trained and evaluated these models on four simulated data sets with 100 000 observations each: one with perfect balance between events and non-events, and three where non-events outnumbered events by an approximate factor of 10:1, 100:1, and 1000:1, respectively.

MEASUREMENTS

We evaluated the performance of these models using a comprehensive suite of measures, including measures that are more appropriate for imbalanced data.

FINDINGS

Increasing imbalance tended to spuriously improve overall accuracy (using a high threshold to classify events vs non-events, overall accuracy improved from 0.45 with perfect balance to 0.99 with the most severe outcome class imbalance), but diminished predictive performance was evident using other metrics (corresponding positive predictive value decreased from 0.99 to 0.14).

CONCLUSION

Increasing reliance on algorithmic risk scores in consequential decision-making processes raises critical fairness and ethical concerns. This paper provides broad guidance for analytic strategies that clinical investigators can use to remedy the impacts of outcome class imbalance on risk prediction tools.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07477-6.

Oral and Topical Treatment of Painful Diabetic Polyneuropathy: Practice Guideline Update Summary: Report of the AAN Guideline Subcommittee

OBJECTIVE

To update the 2011 American Academy of Neurology (AAN) guideline on the treatment of painful diabetic neuropathy (PDN) with a focus on topical and oral medications and medical class effects.

METHODS

The authors systematically searched the literature from January 2008 to April 2020 using a structured review process to classify the evidence and develop practice recommendations using the AAN 2017 Clinical Practice Guideline Process Manual.

RESULTS

Gabapentinoids (standardized mean difference [SMD] 0.44; 95% confidence interval [CI], 0.21-0.67), serotonin-norepinephrine reuptake inhibitors (SNRIs) (SMD 0.47; 95% CI, 0.34-0.60), sodium channel blockers (SMD 0.56; 95% CI, 0.25-0.87), and SNRI/opioid dual mechanism agents (SMD 0.62; 95% CI, 0.38-0.86) all have comparable effect sizes just above or just below our cutoff for a medium effect size (SMD 0.5). Tricyclic antidepressants (TCAs) (SMD 0.95; 95% CI, 0.15-1.8) have a large effect size, but this result is tempered by a low confidence in the estimate.

RECOMMENDATIONS SUMMARY

Clinicians should assess patients with diabetes for PDN (Level B) and those with PDN for concurrent mood and sleep disorders (Level B). In patients with PDN, clinicians should offer TCAs, SNRIs, gabapentinoids, and/or sodium channel blockers to reduce pain (Level B) and consider factors other than efficacy (Level B). Clinicians should offer patients a trial of medication from a different effective class when they do not achieve meaningful improvement or experience significant adverse effects with the initial therapeutic class (Level B) and not use opioids for the treatment of PDN (Level B).

Claims-based measures of prescription opioid utilization: A practical guide for researchers

BACKGROUND

Given the increased attention to the opioid epidemic and the role of inappropriate prescribing, there has been a marked increase in the number of studies using claims data to study opioid use and policies designed to curb misuse. Our objective is to review the medical literature for recent studies that use claims data to construct opioid use measures and to develop a guide for researchers using these measures.

METHODS

We searched for articles relating to opioid use measured in health insurance claims data using a defined set of search terms for the years 2014-2020. Original research articles based in the United States that used claims-based measures of opioid utilization were included and information on the study population and measures of any opioid use, quantity of opioid use, new opioid use, chronic opioid use, multiple providers, and overlapping prescriptions was abstracted.

RESULTS

A total of 164 articles met inclusion criteria. Any opioid use was the most commonly included measure, defined by 85 studies. This was followed by quantity of opioids (68 studies), chronic opioid use (53 studies), overlapping prescriptions (28 studies), and multiple providers (8 studies). Each measure contained multiple, distinct definitions with considerable variation in how each was operationalized.

CONCLUSIONS

Claims-based opioid utilization measures are commonly used in research, but definitions vary significantly from study to study. Researchers should carefully consider which opioid utilization measures and definitions are most appropriate for their study and recognize how different definitions may influence study results.

Changes in Opioid Prescribing Following the Implementation of State Policies Limiting Morphine Equivalent Daily Dose in a Commercially Insured Population

BACKGROUND

Prescription opioid mortality doubled 2002-2016 in the United States. Given the association between high-dose opioid prescribing and opioid mortality, several states have enacted morphine equivalent daily dose (MEDD) policies to limit high-dose prescribing. The study objective is to evaluate the impact of state-level MEDD policies on opioid prescribing among the privately insured.

METHODS

Claims data, 2010-2015 from 9 policy states and 2 control states and a comparative interrupted time series design were utilized. Primary outcomes were any monthly opioid use and average monthly MEDD. Stratified analyses evaluated theorized weaker policies (guidelines) and theorized stronger policies (passive alert systems, legislative acts, and rules/regulations) separately. Patient groups explicitly excluded from policies (eg, individuals with cancer diagnoses or receiving hospice care) were also examined separately. Analyses adjusted for covariates, state fixed effects, and time trends.

RESULTS

Both guideline and strong policy implementation were both associated with 15% lower odds of any opioid use, relative to control states. However, there was no statistically significant change in the use of high-dose opioids in policy states relative to control states. There was also no difference in direction and significance of the relationship among targeted patient groups.

CONCLUSIONS

MEDD policies were associated with decreased use of any opioids relative to control states, but no change in high-dose prescribing was observed. While the overall policy environment in treatment states may have discouraged opioid prescribing, there was no evidence of MEDD policy impact, specifically. Further research is needed to understand the mechanisms through which MEDD policies may influence prescribing behavior.

Inappropriate Opioid Prescribing in Oregon's Coordinated Care Organizations

OBJECTIVES

The objective of this study is to identify demographic and clinical characteristics of patients with a pain diagnosis who fill potentially inappropriate opioid prescriptions within the Oregon Medicaid population.

METHODS

Using de-identified Oregon Medicaid claims data (2010-2014), a series of logistic regression models was estimated to identify factors associated with receipt of potential inappropriate opioid prescriptions among patients with acute or chronic pain. Analyses included a total of 204,364 records, representing 118,671 unique patients.

RESULTS

The percentage of patients with a pain diagnosis filling at least 1 inappropriate opioid prescription decreased over the study period, falling from 32.5% in 2010 to 22.3% in 2014. Multivariate logistic regression results indicated that white and older enrollees were more likely to fill an inappropriate prescription over the study period. The odds of filling an inappropriate opioid prescription were also greater for patients with chronic health conditions, psychiatric disorders, and substance use disorder. Results were similar for patients diagnosed with either acute or chronic pain, chronic pain only, or acute pain only.

CONCLUSIONS

Inappropriate opioid prescribing for patients with pain diagnoses decreased over the study period, which stands in stark contrast to other state Medicaid programs. However, in 2014, almost 23% of patients in the Oregon Medicaid program filled at least 1 inappropriate opioid prescription, suggesting additional strategies are needed to further reduce potential inappropriate prescribing. Medicaid programs may consider adopting enhanced prescription drug monitoring program features, enacting pain clinic legislation, and implementing additional prior authorization policies to reduce inappropriate prescribing of opioids.

Effect of Changing Electronic Health Record Opioid Analgesic Dispense Quantity Defaults on the Quantity Prescribed: A Cluster Randomized Clinical Trial

IMPORTANCE

Interventions to improve judicious prescribing of opioid analgesics for acute pain are needed owing to the risks of diversion, misuse, and overdose.

OBJECTIVE

To assess the effect of modifying opioid analgesic prescribing defaults in the electronic health record (EHR) on prescribing and health service use.

DESIGN, SETTING, AND PARTICIPANTS

A cluster randomized clinical trial with 2 parallel arms was conducted between June 13, 2016, and June 13, 2018, in a large urban health care system comprising 32 primary care and 4 emergency department (ED) sites in the Bronx, New York. Data were analyzed using a difference-in-differences method from 6 months before implementation through 18 months after implementation. Data were analyzed from January 2019 to February 2020.

INTERVENTIONS

A default dispense quantity for new opioid analgesic prescriptions of 10 tablets (intervention) vs no change (control) in the EHR.

MAIN OUTCOMES AND MEASURES

The primary outcome was the quantity of opioid analgesics prescribed with the new default prescription. Secondary outcomes were opioid analgesic reorders and health service use within 30 days after the new prescription. Intention-to-treat analysis was conducted.

RESULTS

Overall, 21 331 patients received a new opioid analgesic prescription from 490 prescribers. Comparing the intervention and control arms, site, prescriber, and patient characteristics were similar. For the new prescription, compared with the control arm, patients in the intervention arm had significantly more prescriptions for 10 tablets or fewer (7.6 percentage points; 95% CI, 6.1-9.2 percentage points), a lower number of tablets prescribed (-2.1 tablets; 95% CI, -3.3 to -0.9 tablets), and lower morphine milligram equivalents (MME) prescribed (-14.6 MME; 95% CI, -22.6 to -6.6 MME). Within 30 days after the new prescription, significant differences remained in the number of tablets prescribed (-2.7 tablets; 95% CI, -4.8 to -0.6 tablets), but not MME (-15.8 MME; 95% CI, -33.8 to 2.2 MME). Within this 30-day period, there were no significant differences between the arms in health service use.

CONCLUSIONS AND RELEVANCE

In this study, implementation of a uniform reduced default dispense quantity of 10 tablets for opioid analgesic prescriptions led to a modest reduction in the quantity prescribed initially, without significantly increasing health service use. However, during 30 days after implementation, the influence on prescribing was mixed. Reducing EHR default dispense quantities for opioid analgesics is a feasible strategy that can be widely disseminated and may modestly reduce prescribing.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03003832.

Variations in Long-term Opioid Therapy Definitions: A Systematic Review of Observational Studies Using Routinely Collected Data (2000-2019)

Routinely collected data have been increasingly used to assess long-term opioid therapy (LTOT) patterns, with very little guidance on how to measure LTOT from these data sources. We conducted a systematic review of studies published between January 2000 and July 2019 to catalogue LTOT definitions, the rationale for definitions and LTOT rates in observational research using routinely collected data in nonsurgical settings. We screened 4056 abstracts, 210 full-text manuscripts and included 128 studies, mostly from the United States (81%) and published between 2015 and 2019 (69%). We identified 78 definitions of LTOT, commonly operationalised as 90 days of use within a year (23%). Studies often used multiple criteria to derive definitions (60%), mostly based on measures of duration, such as supply days/days of use (66%), episode length (21%) or prescription fills within specified time periods (12%). Definitions were based on previous publications (63%), clinical judgment (16%) or empirical data (3%); 10% of studies applied more than one definition. LTOT definition was not provided with enough details for replication in 14 studies and 38 studies did not specify the opioids evaluated. Rates of LTOT within study populations ranged from 0.2% to 57% according to study design and definition used. We observed a substantial rise in the last 5 years in studies evaluating LTOT with large variability in the definitions used and poor reporting of the rationale and implementation of definitions. This variation impacts on research reproducibility, comparability of findings and the development of strategies aiming to curb therapy that is not guideline-recommended.

Association between supportive interventions and healthcare utilization and outcomes in patients on long-term prescribed opioid therapy presenting to acute healthcare settings: a systematic review and meta-analysis

BACKGROUND

Long-term prescription of opioids by healthcare professionals has been linked to poor individual patient outcomes and high resource utilization. Supportive strategies in this population regarding acute healthcare settings may have substantial impact.

METHODS

We performed a systematic review and meta-analysis of primary studies. The studies were included according to the following criteria: 1) age 18 and older; 2) long-term prescribed opioid therapy; 3) acute healthcare setting presentation from a complication of opioid therapy; 4) evaluating a supportive strategy; 5) comparing the effectiveness of different interventions; 6) addressing patient or healthcare related outcomes. We performed a qualitative analysis of supportive strategies identified. We pooled patient and system related outcome data for each supportive strategy.

RESULTS

A total of 5664 studies were screened and 19 studies were included. A total of 9 broad categories of supportive strategies were identified. Meta-analysis was performed for the "supports for patients in pain" supportive strategy on two system-related outcomes using a ratio of means. The number of emergency department (ED) visits were significantly reduced for cohort studies (n = 6, 0.36, 95% CI [0.20-0.62], I2 = 87%) and randomized controlled trials (RCTs) (n = 3, 0.71, 95% CI [0.61-0.82], I2 = 0%). The number of opioid prescriptions at ED discharge was significantly reduced for RCTs (n = 3, 0.34, 95% CI [0.14-0.82], I2 = 78%).

CONCLUSION

For patients presenting to acute healthcare settings with complications related to long-term opioid therapy, the intervention with the most robust data is "supports for patients in pain".

Nonconsensual Dose Reduction Mandates are Not Justified Clinically or Ethically: An Analysis

This manuscript describes the institutional and clinical considerations that apply to the question of whether to mandate opioid dose reduction in patients who have received opioids long-term. It describes how a calamitous rise in addiction and overdose involving opioids has both led to a clinical recalibration by healthcare providers, and to strong incentives favoring forcible opioid reduction by policy making agencies. Neither the 2016 Guideline issued by the Centers for Disease Control and Prevention nor clinical evidence can justify or promote such policies as safe or effective.

The Impact of Morphine Equivalent Daily Dose Threshold Guidelines on Prescribed Dose in a Workers' Compensation Population

BACKGROUND

Prescription opioid overdose has increased markedly and is of great concern among injured workers receiving workers' compensation insurance. Given the association between high daily dose of prescription opioids and negative health outcomes, state workers' compensation boards have disseminated Morphine Equivalent Daily Dose (MEDD) guidelines to discourage high-dose opioid prescribing.

OBJECTIVE

To evaluate the impact of MEDD guidelines among workers' compensation claimants on prescribed opioid dose.

METHODS

Workers' compensation claims data, 2010-2013 from 2 guideline states and 3 control states were utilized. The study design was an interrupted time series with comparison states and average monthly MEDD was the primary outcome. Policy variables were specified to allow for both instantaneous and gradual effects and additional stratified analyses examined evaluated the policies separately for individuals with and without acute pain, cancer, and high-dose baseline use to determine whether policies were being targeted as intended.

RESULTS

After adjusting for covariates, state fixed-effects, and time trends, policy implementation was associated with a 9.26 mg decrease in MEDD (95% confidence interval, -13.96 to -4.56). Decreases in MEDD also became more pronounced over time and were larger in groups targeted by the policies.

CONCLUSIONS

Passage of workers' compensation MEDD guidelines was associated with decreases in prescribed opioid dose among injured workers. Disseminating MEDD guidelines to doctors who treat workers' compensation cases may address an important risk factor for opioid-related mortality, while still allowing for autonomy in practice. Further research is needed to determine whether MEDD policies influence prescribing behavior and patient outcomes in other populations.

Evaluation of a Safer Opioid Prescribing Protocol (SOPP) for Patients Being Discharged From a Trauma Service

The aims of this study were to evaluate the effects on opioid medication prescribing, patient opioid safety education, and prescribing of naloxone following implementation of a Safer Opioid Prescribing Protocol (SOPP) as part of the electronic health record (EHR) system at a Level I trauma center. This was a prospective observational study of the EHR of trauma patients pre- (n = 191) and post-(n = 316) SOPP implementation between 2014 and 2016. At a comparison Level I trauma site not implementing SOPP, EHRs for the same time period were assessed for any historical trends in opioid and naloxone prescribing. After SOPP implementation, the implementation site increased the use of nonnarcotic pain medication, decreased dispensing high opioid dose (≥100 MME [milligram morphine equivalent]), significantly increased the delivery of opioid safety education to patients, and initiated prescribing naloxone. These changes were not found in the comparison site. Opioid prescribing for acute pain can be effectively reduced in a busy trauma setting with a guideline intervention incorporated into an EHR. Guidelines can increase the use of nonnarcotic medications for the treatment of acute pain and increase naloxone coprescription for patients with a higher risk of overdose.

Associations between stopping prescriptions for opioids, length of opioid treatment, and overdose or suicide deaths in US veterans: observational evaluation

OBJECTIVE

To examine the associations between stopping treatment with opioids, length of treatment, and death from overdose or suicide in the Veterans Health Administration.

DESIGN

Observational evaluation.

SETTING

Veterans Health Administration.

PARTICIPANTS

1 394 102 patients in the Veterans Health Administration with an outpatient prescription for an opioid analgesic from fiscal year 2013 to the end of fiscal year 2014 (1 October 2012 to 30 September 2014).

MAIN OUTCOME MEASURES

A multivariable Cox non-proportional hazards regression model examined death from overdose or suicide, with the interaction of time varying opioid cessation by length of treatment (≤30, 31-90, 91-400, and >400 days) as the main covariates. Stopping treatment with opioids was measured as the time when a patient was estimated to have no prescription for opioids, up to the end of the next fiscal year (2014) or the patient's death.

RESULTS

2887 deaths from overdose or suicide were found. The incidence of stopping opioid treatment was 57.4% (n=799 668) overall, and based on length of opioid treatment was 32.0% (≤30 days), 8.7% (31-90 days), 22.7% (91-400 days), and 36.6% (>400 days). The interaction between stopping treatment with opioids and length of treatment was significant (P<0.001); stopping treatment was associated with an increased risk of death from overdose or suicide regardless of the length of treatment, with the risk increasing the longer patients were treated. Hazard ratios for patients who stopped opioid treatment (with reference values for all other covariates) were 1.67 (≤30 days), 2.80 (31-90 days), 3.95 (91-400 days), and 6.77 (>400 days). Descriptive life table data suggested that death rates for overdose or suicide increased immediately after starting or stopping treatment with opioids, with the incidence decreasing over about three to 12 months.

CONCLUSIONS

Patients were at greater risk of death from overdose or suicide after stopping opioid treatment, with an increase in the risk the longer patients had been treated before stopping. Descriptive data suggested that starting treatment with opioids was also a risk period. Strategies to mitigate the risk in these periods are not currently a focus of guidelines for long term use of opioids. The associations observed cannot be assumed to be causal; the context in which opioid prescriptions were started and stopped might contribute to risk and was not investigated. Safer prescribing of opioids should take a broader view on patient safety and mitigate the risk from the patient's perspective. Factors to address are those that place patients at risk for overdose or suicide after beginning and stopping opioid treatment, especially in the first three months.

Prevalence of and Risk Factors Associated With Nonfatal Overdose Among Veterans Who Have Experienced Homelessness

IMPORTANCE

Individuals with a history of homelessness are at increased risk for drug or alcohol overdose, although the proportion who have had recent nonfatal overdose is unknown. Understanding risk factors associated with nonfatal overdose could guide efforts to prevent fatal overdose.

OBJECTIVES

To determine the prevalence of recent overdose and the individual contributions of drugs and alcohol to overdose and to identify characteristics associated with overdose among veterans who have experienced homelessness.

DESIGN, SETTING, AND PARTICIPANTS

This survey study was conducted from November 15, 2017, to October 1, 2018, via mailed surveys with telephone follow-up for nonrespondents. Eligible participants were selected from the records of 26 US Department of Veterans Affairs medical centers and included veterans who had received primary care at 1 of these Veterans Affairs medical centers and had a history of experiencing homelessness according to administrative data. Preliminary analyses were conducted in October 2018, and final analyses were conducted in January 2020.

MAIN OUTCOMES AND MEASURES

Self-report of overdose (such that emergent medical care was obtained) in the previous 3 years and substances used during the most recent overdose. All percentages are weighted according to propensity to respond to the survey, modeled from clinical characteristics obtained in electronic health records.

RESULTS

A total of 5766 veterans completed the survey (completion rate, 40.2%), and data on overdose were available for 5694 veterans. After adjusting for the propensity to respond to the survey, the mean (SD) age was 56.4 (18.3) years; 5100 veterans (91.6%) were men, 2225 veterans (38.1%) were black, and 2345 veterans (40.7%) were white. A total of 379 veterans (7.4%) reported any overdose during the past 3 years; 228 veterans (4.6%) reported overdose involving drugs, including 83 veterans (1.7%) who reported overdose involving opioids. Overdose involving alcohol was reported by 192 veterans (3.7%). In multivariable analyses, white race (odds ratio, 2.44 [95% CI, 2.00-2.98]), self-reporting a drug problem (odds ratio, 1.66 [95% CI, 1.39-1.98]) or alcohol problem (odds ratio, 2.54 [95% CI, 2.16-2.99]), and having witnessed someone else overdose (odds ratio, 2.34 [95% CI, 1.98-2.76]) were associated with increased risk of overdose.

CONCLUSIONS AND RELEVANCE

These findings suggest that nonfatal overdose is relatively common among veterans who have experienced homelessness. While overdose involving alcohol was more common than any specific drug, 1.7% of veterans reported overdose involving opioids. Improving access to addiction treatment for veterans who are experiencing homelessness or who are recently housed, especially for those who have experienced or witnessed overdose, could help to protect this population.

The Association of State Opioid Misuse Prevention Policies With Patient- and Provider-Related Outcomes: A Scoping Review

Policy Points This scoping review reveals a growing literature on the effects of certain state opioid misuse prevention policies, but persistent gaps in evidence on other prevalent state policies remain. Policymakers interested in reducing the volume and dosage of opioids prescribed and dispensed can consider adopting robust prescription drug monitoring programs with mandatory access provisions and drug supply management policies, such as prior authorization policies for high-risk prescription opioids. Further research should concentrate on potential unintended consequences of opioid misuse prevention policies, differential policy effects across populations, interventions that have not received sufficient evaluation (eg, Good Samaritan laws, naloxone access laws), and patient-related outcomes.

CONTEXT

In the midst of an opioid crisis in the United States, an influx of state opioid misuse prevention policies has provided new opportunities to generate evidence of policy effectiveness that can inform policy decisions. We conducted a scoping review to synthesize the available evidence on the effectiveness of US state interventions to improve patient and provider outcomes related to opioid misuse and addiction.

METHODS

We searched six online databases to identify evaluations of state opioid policies. Eligible studies examined legislative and administrative policy interventions that evaluated (a) prescribing and dispensing, (b) patient behavior, or (c) patient health.

FINDINGS

Seventy-one articles met our inclusion criteria, including 41 studies published between 2016 and 2018. These articles evaluated nine types of state policies targeting opioid misuse. While prescription drug monitoring programs (PDMPs) have received considerable attention in the literature, far fewer studies addressed other types of state policy. Overall, evidence quality is very low for the majority of policies due to a small number of evaluations. Of interventions that have been the subject of considerable research, promising means of reducing the volume and dosages of opioids prescribed and dispensed include drug supply management policies and robust PDMPs. Due to low study number and quality, evidence is insufficient to draw conclusions regarding interventions targeting patient behavior and health outcomes, including naloxone access laws and Good Samaritan laws.

CONCLUSIONS

Recent research has improved the evidence base on several state interventions targeting opioid misuse. Specifically, moderate evidence suggests that drug supply management policies and robust PDMPs reduce opioid prescribing. Despite the increase in rigorous evaluations, evidence remains limited for the majority of policies, particularly those targeting patient health-related outcomes.

Development of the Adverse Analgesic Drug Event Measure

BACKGROUND

Little is known about how people respond to an analgesic adverse drug event despite the significant incidence of deaths and hospitalizations associated with analgesic adverse drug events.

OBJECTIVE

The purpose of this two-phase instrument development study was to test the validity and reliability of the Analgesic Adverse Drug Event Measure (AADEM).

METHODS

Content validity was established during Phase I. Six experts rated the 58-item measure developed from a pilot survey of adults who had experienced an analgesic adverse drug event. Experts' ratings supported a 17-item AADEM with a scale content validity index of .86. Phase II consisted of online administration of the AADEM to a national Qualtrics panel who reported an adverse drug event from a self-administered analgesic. Exploratory factor analysis was conducted using principal axis factoring and oblique rotation including Direct Oblimin and Promax rotations with Kaiser normalization.

RESULTS

Four factors emerged from the analysis: sought care, consulted provider, discontinued or continued analgesic, and attributed adverse drug event with a total explained variance of 55.4%. Scale content validity index for the 13-item AADEM was .88. Internal consistency for the four subscales was acceptable, but low for the full 13-item AADEM.

DISCUSSION

Results establish preliminary evidence for the validity and reliability of the 13-item AADEM to measure response to an analgesic adverse drug event. Next steps involve confirmatory factor analysis in a different sample to examine the underlying construct of the AADEM. The AADEM might help identify people at risk for serious analgesic adverse drug events.

Reducing High-Dose Opioid Prescribing: State-Level Morphine Equivalent Daily Dose Policies, 2007-2017

OBJECTIVE

To describe current state-level policies in the United States, January 1, 2007-June 1, 2017, limiting high morphine equivalent daily dose (MEDD) prescribing.

METHODS

State-level MEDD threshold policies were reviewed using LexisNexis and Westlaw Next for legislative acts and using Google for nonlegislative state-level policies. The websites of each state's Medicaid agency, health department, prescription drug monitoring program, workers' compensation board, medical board, and pharmacy board were reviewed to identify additional policies. The final policy list was checked against existing policy compilations and academic literature and through contact with state health agency representatives. Policies were independently double-coded on the categories: state, agency/organization, policy type, effective date, threshold level, and policy exceptions.

RESULTS

Currently, 22 states have at least one type of MEDD policy, most commonly guidelines (14 states), followed by prior authorizations (four states), rules/regulations (four states), legislative acts (three states), claim denials (two states), and alert systems/automatic patient reports (two states). Thresholds range widely (30-300 mg MEDD), with higher thresholds generally corresponding to more restrictive policies (e.g., claim denial) and lower thresholds corresponding to less restrictive policies (e.g., guidelines). The majority of policies exclude some groups of opioid users, most commonly patients with terminal illnesses or acute pain.

CONCLUSIONS

MEDD policies have gained popularity in recent years, but considerable variation in threshold levels and policy structure point to a lack of consensus. This work provides a foundation for future evaluation of MEDD policies and may inform states considering adopting such policies.

Prescribing patterns before and after a non-fatal drug overdose using Tennessee's controlled substance monitoring database linked to hospital discharge data

We performed a statewide evaluation of prescribing patterns of controlled substances (CS) before and after an overdose, using Tennessee's Hospital Discharge Data System and the Controlled Substance Monitoring Database (CSMD). Adults' first non-fatal overdose discharges either from the emergency department (ED) or inpatient (IP) stay occurring between 2013 and 2016 were linked to prescriptions in the CSMD. The difference in the proportion of patients filling a prescription before versus after an overdose was calculated. Included were 49,398 patients with an overdose and a prescription record; most (60.5%) were treated in the ED. Among any drug type overdose the percentage of patients who filled a CS prescription within a year of experiencing an overdose was as follows: opioid analgesics: 59.1%, benzodiazepines: 37.3%, stimulants: 5.0%, muscle relaxants: 3.4%, concurrent opioid-benzodiazepines: 24.0% with the percent difference from before to after similar in both settings. Among patients treated for an opioid overdose, this represented a decrease in opioid analgesics filled by 9.7% (95%CI: -11.2, -8.3) among those treated in the ED, and by 7.1% (95% CI: -8.3, -5.9) among treated inpatients. Among patients treated for a heroin overdose, 12.2% (95%CI: -15.2, -9.3) fewer of those treated in the ED and 8.8% (95%CI: -15.0, -2.7%) fewer of treated inpatients filled a CS prescription in that year. The most common opioid analgesics included hydrocodone and oxycodone. The number of patients filling buprenorphine for treatment increased in the year after overdoses associated with any drug or opioids but decreased among those treated for a heroin overdose.

Opioid prescribing patterns after dental visits among beneficiaries of Medicaid in Washington state in 2014 and 2015

BACKGROUND

Dentists contribute to the prevailing opioid epidemic in the United States. Concerning the population enrolled in Medicaid, little is known about dentists' opioid prescribing.

METHODS

The authors performed a retrospective cohort study of beneficiaries of Medicaid in Washington state with dental claims in 2014 and 2015. The primary outcome was the proportion of dental visits associated with an opioid prescription. The authors categorized visits as invasive or noninvasive by using procedure codes and each beneficiary as being at low or high risk by using his or her prescription history from the prescription drug monitoring program.

RESULTS

A total of 126,660 (10.3%) of all dental visits, most of which were invasive (66.9%), among the population enrolled in Medicaid in Washington state was associated with opioid prescriptions. However, noninvasive dental visits and visits for beneficiaries who had prior high-risk prescription use were associated with significantly higher mean days' supply and mean quantity of opioids prescribed. Results from the multivariate logistic regression showed that the probability of having an opioid-associated visit increased by 35.6 percentage points when the procedures were invasive and by 11.1 percentage points when the beneficiary had prior high-risk prescription use.

CONCLUSIONS

This baseline of opioid prescribing patterns after dental visits among the population enrolled in Medicaid in Washington state in 2014 and 2015 can inform future studies in which the investigators examine the effect of policies on opioid prescribing patterns and reasons for the variability in the dosage and duration of opioid prescriptions associated with noninvasive visits.

PRACTICAL IMPLICATIONS

Dentists must exercise caution when prescribing opioids during invasive visits and to patients with prior high-risk prescription use.

Opioid-related hospitalizations in Pennsylvania: A latent class analysis

BACKGROUND

Opioid abuse is associated with substantial morbidity and often results in hospitalization. Despite this, patient-level factors associated with opioid-related hospitalizations are not well understood.

METHODS

We used the Pennsylvania Health Care Cost Containment Council dataset (2000-2014) to identify opioid-related hospitalizations using primary and/or secondary ICD-9-CM hospital discharge codes for opioid use disorder (OUD), opioid poisoning, and heroin poisoning. Latent class analyses (LCA) of patient-level factors including sociodemographic characteristics, pregnancy, alcohol, tobacco, other substance use, and psychiatric disorders were used to identify common patterns within hospitalizations.

RESULTS

Among 28,538,499 hospitalizations, 430,569 (1.5%) were opioid-related. LCA identified five latent class (LC) patient groups associated with opioid-related hospitalizations: pregnant women with OUD (LC1); women over 65 with opioid overdose (LC2); OUD, polysubstance use and co-occurring psychiatric disorders (LC3); patients with opioid overdose without co-occurring polysubstance use (LC4); and African American patients with OUD and co-occurring cocaine use (LC5). LC3 was the largest latent class (58.2%) with annual hospitalizations doubling over time.

DISCUSSION

Among patients with opioid-related discharges, we identified five subpopulations among this sample. These findings suggest increased outpatient OUD treatment, mental health service support for patients with co-occurring psychiatric disorders and polysubstance use to prevent overdose and hospitalization.

Challenges with Implementing the Centers for Disease Control and Prevention Opioid Guideline: A Consensus Panel Report

BACKGROUND

A national crisis of opioid-related morbidity, mortality, and misuse has led to initiatives to address the appropriate role of opioids to treat pain. Deployment of a guideline from the Centers for Disease Control and Prevention to reduce the risks of opioid therapy has raised substantial clinical and public policy challenges. The agency anticipated implementation challenges and committed to reevaluating the guideline for intended and unintended effects on clinician and patient outcomes.

OBSERVATIONS

A multidisciplinary expert panel met to review the influence of the core recommendations of the guideline on pain management practices, principally regarding the estimated 5 to 8 million Americans with chronic pain currently on opioids. The panel identified implementation challenges, including application of dosage ceilings and prescription duration guidance, failure to appreciate the importance of patient involvement in decisions to taper or discontinue opioids, barriers to diagnosis and treatment of opioid use disorder, and impeded access to recommended comprehensive, multimodal pain care. Furthermore, policy-making and regulatory bodies may misapply guideline recommendations without flexibility and, sometimes, without full awareness of what the guideline contains.

CONCLUSIONS AND RELEVANCE

The panel largely supported the guideline, endorsing its focal points of safety and comprehensive assessment and monitoring. To mitigate clinical and policy challenges identified with implementing the guideline, the panel discussed areas where viewpoints diverged and arrived at consensus proposals. The target audience includes the leaders and institutions that create policy and influence guideline implementation to include regulatory agencies, legislators, public and private payers, and health care systems.

Opioid Overdose Hospitalization Trajectories in States With and Without Opioid-Dosing Guidelines

OBJECTIVES

High-risk opioid-prescribing practices contribute to a national epidemic of opioid-related morbidity and mortality. The objective of this study was to determine whether the adoption of state-level opioid-prescribing guidelines that specify a high-dose threshold is associated with trends in rates of opioid overdose hospitalizations, for prescription opioids, for heroin, and for all opioids.

METHODS

We identified 3 guideline states (Colorado, Utah, Washington) and 5 comparator states (Arizona, California, Michigan, New Jersey, South Carolina). We used state-level opioid overdose hospitalization data from 2001-2014 for these 8 states. Data were based on the State Inpatient Databases and provided by the Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality, via HCUPnet. We used negative binomial panel regression to model trends in annual rates of opioid overdose hospitalizations. We used a multiple-baseline difference-in-differences study design to compare postguideline trends with concurrent trends for comparator states.

RESULTS

For each guideline state, postguideline trends in rates of prescription opioid and all opioid overdose hospitalizations decreased compared with trends in the comparator states. The mean annual relative percentage decrease ranged from 3.2%-7.5% for trends in rates of prescription opioid overdose hospitalizations and from 5.4%-8.5% for trends in rates of all opioid overdose hospitalizations.

CONCLUSIONS

These findings provide preliminary evidence that opioid-dosing guidelines may be an effective strategy for combating this public health crisis. Further research is needed to identify the individual effects of opioid-related interventions that occurred during the study period.

Deaths among opioid users: impact of potential inappropriate prescribing practices

OBJECTIVES

To examine the association between potential inappropriate prescribing practices of opioids and deaths among opioid users in the Georgia Medicaid population.

STUDY DESIGN

A retrospective analysis of individual pharmacy claims data from Georgia Medicaid from 2009 through 2014.

METHODS

The sample was restricted to patients without cancer aged 18 to 64 years with an opioid prescription and included 3,562,227 observations representing 401,488 individuals. A descriptive analysis and a multivariate logistic regression analysis were conducted.

RESULTS

Results indicate a total of 14,516 deaths among opioid users in the study sample, of whom approximately 42% experienced at least 1 incidence of potential inappropriate prescribing practices. Regression results indicate that the odds of opioid users experiencing death were 1.76 times higher for those who experienced at least 1 incidence of potential inappropriate prescribing practices of opioids compared with those who did not experience any incidence, even after controlling for other covariates (P <.001). Moreover, opioid users in managed care Medicaid were less likely to experience death compared with fee-for-service (FFS) enrollees.

CONCLUSIONS

The results indicate a positive and statistically significant association between potential inappropriate opioid prescribing practices and deaths among opioid users in Georgia Medicaid, with FFS enrollees experiencing higher rates of death compared with managed care enrollees. Appropriate policies and interventions targeted at reducing potential inappropriate prescribing practices may help reduce the risk factors associated with mortality among opioid users in this population.

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions

IMPORTANCE

Current approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk.

OBJECTIVE

To develop and validate a machine-learning algorithm to predict opioid overdose risk among Medicare beneficiaries with at least 1 opioid prescription.

DESIGN, SETTING, AND PARTICIPANTS

A prognostic study was conducted between September 1, 2017, and December 31, 2018. Participants (n = 560 057) included fee-for-service Medicare beneficiaries without cancer who filled 1 or more opioid prescriptions from January 1, 2011, to December 31, 2015. Beneficiaries were randomly and equally divided into training, testing, and validation samples.

EXPOSURES

Potential predictors (n = 268), including sociodemographics, health status, patterns of opioid use, and practitioner-level and regional-level factors, were measured in 3-month windows, starting 3 months before initiating opioids until loss of follow-up or the end of observation.

MAIN OUTCOMES AND MEASURES

Opioid overdose episodes from inpatient and emergency department claims were identified. Multivariate logistic regression (MLR), least absolute shrinkage and selection operator-type regression (LASSO), random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN) were applied to predict overdose risk in the subsequent 3 months after initiation of treatment with prescription opioids. Prediction performance was assessed using the C statistic and other metrics (eg, sensitivity, specificity, and number needed to evaluate [NNE] to identify one overdose). The Youden index was used to identify the optimized threshold of predicted score that balanced sensitivity and specificity.

RESULTS

Beneficiaries in the training (n = 186 686), testing (n = 186 685), and validation (n = 186 686) samples had similar characteristics (mean [SD] age of 68.0 [14.5] years, and approximately 63% were female, 82% were white, 35% had disabilities, 41% were dual eligible, and 0.60% had at least 1 overdose episode). In the validation sample, the DNN (C statistic = 0.91; 95% CI, 0.88-0.93) and GBM (C statistic = 0.90; 95% CI, 0.87-0.94) algorithms outperformed the LASSO (C statistic = 0.84; 95% CI, 0.80-0.89), RF (C statistic = 0.80; 95% CI, 0.75-0.84), and MLR (C statistic = 0.75; 95% CI, 0.69-0.80) methods for predicting opioid overdose. At the optimized sensitivity and specificity, DNN had a sensitivity of 92.3%, specificity of 75.7%, NNE of 542, positive predictive value of 0.18%, and negative predictive value of 99.9%. The DNN classified patients into low-risk (76.2% [142 180] of the cohort), medium-risk (18.6% [34 579] of the cohort), and high-risk (5.2% [9747] of the cohort) subgroups, with only 1 in 10 000 in the low-risk subgroup having an overdose episode. More than 90% of overdose episodes occurred in the high-risk and medium-risk subgroups, although positive predictive values were low, given the rare overdose outcome.

CONCLUSIONS AND RELEVANCE

Machine-learning algorithms appear to perform well for risk prediction and stratification of opioid overdose, especially in identifying low-risk subgroups that have minimal risk of overdose.

Laws limiting the prescribing or dispensing of opioids for acute pain in the United States: A national systematic legal review

BACKGROUND

Opioid overdose is a continuing public health crisis. In response to an increasing recognition of the negative outcomes sometimes associated with the use of opioid analgesics, states have taken a number of steps attempting to reduce inappropriate prescribing of these medications. These include the imposition of strict legal limitations on the amount or duration that opioid analgesics may be prescribed or dispensed to patients with acute pain.

METHODS

We conducted a systematic, multi-source legal review of state laws that impose mandatory limits on the ability of medical professionals to prescribe or dispense opioids for the treatment of acute pain. We also systematically searched for and examined publicly available documents on state legislative and regulatory bodies' websites. All relevant laws were downloaded and systematically coded.

RESULTS

By the end of 2017, twenty-six states had passed laws that impose mandatory limits on the prescribing or dispensing of opioids for acute pain. The oldest of these laws became effective as early as 1989, but most are much newer: approximately 65% (17/26) were passed in 2017. There is wide variation in the characteristics of these laws.

CONCLUSION

Just over half of all states have enacted laws that restrict the prescribing or dispensing of opioids for acute pain. To date, there is no data on whether and to what extent these laws mediate opioid-related morbidity and mortality, as well as whether they are associated with negative unintended outcomes. Research into these questions is urgently needed.

A systematic review of strategies to improve appropriate use of opioids and to reduce opioid use disorder and deaths from prescription opioids

Background

Abuse of prescription opioids is a serious problem in North America.

Aims

The aim of this study was to conduct a systematic review of peer-reviewed and grey literature to examine existing strategies aimed at improving the appropriate use of prescription opioids and/or reducing the misuse, abuse, and diversion of these drugs.

Methods

The following electronic databases were searched to September 2015 without language restrictions: MEDLINE, EMBASE, PsycINFO, and CINAHL; the grey literature was searched to May 2014. Reference lists of retrieved papers were also searched. Studies were eligible if a strategy was implemented and its impact on at least one of the primary outcomes of interest (appropriate prescription opioid use; misuse, abuse, opioid use disorder, diversion; overdose) was measured. Standardized, prepiloted forms were used for relevance screening, quality appraisal, and data extraction.

Results

A total of 65 studies that assessed 66 distinct strategies were identified. Due to the heterogeneity of the strategies, a qualitative synthesis was conducted. Many studies combined more than one type of strategy and measured various types of outcomes. The strategies with most promising results involved education, clinical practices, collaborations, prescription monitoring programs, public campaigns, opioid substitution programs, and naloxone distribution. We also found strategies that had some unintended consequences after implementation.

Conclusions

Our review identified successful strategies that have been implemented and evaluated in various jurisdictions. There is a need to replicate and disseminate these strategies where the problem of prescription opioid misuse and abuse has taken a toll on society.

Overview of Prescription Opioid Deaths in the Oklahoma State Medicaid Population, 2012-2016

BACKGROUND

Medicaid members are predisposed to unintentional prescription opioid overdose. However, little is known about their individual risk factors.

OBJECTIVES

To describe demographic and clinical characteristics, medical utilization, opioid use, concurrent use of benzodiazepines, risk factors, and substances involved in death for Oklahoma's Medicaid members who died of unintentional prescription opioid poisoning.

SUBJECTS

Decedents who were Medicaid eligible in Oklahoma during the year of death, had an opioid recorded in cause of death, and had ≥1 opioid prescription claim between January 1, 2011 and June 30, 2016 were cases. Controls were living Medicaid members and were matched 3:1 to cases through propensity score matching.

MEASURES

Demographics, clinical characteristics, and medical/pharmacy utilization were examined in the 12 months before the index date.

RESULTS

Of 639 members with fatal unintentional prescription opioid overdoses, 321 had ≥1 opioid prescription claim in the year before death; these were matched to 963 controls. Compared with controls, decedents had significantly greater proportions of nonopioid substance use disorders, opioid abuse/dependence, hepatitis, gastrointestinal bleeding, trauma not involving motor vehicle accidents, nonopioid poisonings, and mental illness disorders. Decedents had significantly higher daily morphine milligram equivalent doses (67.2±74.4 vs. 47.2±50.9 mg) and greater opioid/benzodiazepine overlap (70.4% vs. 35.9%). Benzodiazepines were involved in 29.3% of deaths.

CONCLUSIONS

Several comorbidities indicative of opioid use disorder and greater exposure to opioids and concomitant benzodiazepines were associated with unintentional prescription opioid overdose fatalities. Prescribers and state agencies should be aware of these addressable patient-level factors among the Medicaid population. Targeting these factors with appropriate policy interventions and education may prevent future deaths.

Reducing the default dispense quantity for new opioid analgesic prescriptions: study protocol for a cluster randomised controlled trial

INTRODUCTION

As opioid analgesic consumption has grown, so have opioid use disorder and opioid-related overdoses. Reducing the quantity of opioid analgesics prescribed for acute non-cancer pain can potentially reduce risks to the individual receiving the prescription and to others who might unintentionally or intentionally consume any leftover tablets. Reducing the default dispense quantity for new opioid analgesic prescriptions in the electronic health record (EHR) is a promising intervention to reduce prescribing.

METHODS AND ANALYSIS

This study is a prospective cluster randomised controlled trial with two parallel arms. Primary care sites (n=32) and emergency departments (n=4) will be randomised in matched pairs to either a modification of the EHR so that new opioid analgesic prescriptions default to a dispense quantity of 10 tablets (intervention) or to no EHR change (control). The dispense quantity will remain fully modifiable by providers in both arms. From 6 months preintervention to 18 months postintervention, patient-level data will be analysed (ie, the patient is the unit of inference). Patient eligibility criteria are: (A) received a new opioid analgesic prescription, defined as no other opioid analgesic prescription in the prior 6 months; (B) age ≥18 years; and (C) no cancer diagnosis within 1 year prior to the new opioid analgesic prescription. The primary outcome will be the quantity of opioid analgesics prescribed in the initial prescription. Secondary outcomes will include opioid analgesic reorders and health service utilisation within 30 days after the initial prescription. Outcomes will be compared between study arms using a difference-in-differences analysis.

ETHICS AND DISSEMINATION

This study has been approved by the Montefiore Medical Center/Albert Einstein College of Medicine Institutional Review Board with a waiver of informed consent (2016-6036) and is registered on ClinicalTrials.gov (NCT03003832, 6 December 2016). Findings will be disseminated through publication, conferences and meetings with health system leaders.

TRIAL REGISTRATION NUMBER

NCT03003832; Pre-results.

Endogenous Opiates and Behavior: 2016

This paper is the thirty-ninth consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2016 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior, and the roles of these opioid peptides and receptors in pain and analgesia, stress and social status, tolerance and dependence, learning and memory, eating and drinking, drug abuse and alcohol, sexual activity and hormones, pregnancy, development and endocrinology, mental illness and mood, seizures and neurologic disorders, electrical-related activity and neurophysiology, general activity and locomotion, gastrointestinal, renal and hepatic functions, cardiovascular responses, respiration and thermoregulation, and immunological responses.

Prescribed Dose of Opioids and Overdose: A Systematic Review and Meta-Analysis of Unintentional Prescription Opioid Overdose

BACKGROUND

The rate of an unintentional drug overdose involving prescription opioids continues to rise. An understanding of the threshold dose and dose(s) associated with unintentional prescription opioid overdose will help to mitigate this epidemic.

OBJECTIVE

The objective of this systematic review is to systematically synthesise and meta-analyse studies on doses of prescription opioids and ascertain the doses of opioids that are associated with increased risk of severe opioid poisoning or mortality.

DATA SOURCES

A search of PubMed, EMBASE, CINAHL and Web of Science from inception to 16 January 2017 was conducted using search strategies and the MeSH (Medical Subject Headings) terms for studies of adult patients using prescription opioids who experienced an accidental overdose.

STUDY SELECTION

Of the 1332 studies identified, 117 were selected for full article review. Ten met the inclusion criteria for qualitative analysis, but only seven studies were meta-analysed. The included studies were in English, and participants met predetermined International Classification of Diseases (ICD) codes. Studies were excluded if they included only paediatric participants or the participants met the ICD code for intentional self-harm.

DATA EXTRACTION AND SYNTHESIS

Two researchers elaborated and validated a data extraction form. Data were then independently extracted by both reviewers as per this form. We assessed study quality using the Newcastle-Ottawa Scale (NOS) for non-randomised studies in meta-analyses. We performed a meta-regression using a random-effect model and summarised the results using relative risk (RR) and 95% confidence intervals (CIs). The threshold dose for an unintentional overdose is 20 morphine milligram equivalents (MME)/day. There were higher risks with larger doses: (1) ≤ 20 versus ≥ 21 MME/day: RR 2.81, 95% CI 1.09-7.22, p < 0.001; (2) ≤ 50 versus > 50 MME/day: RR 3.87, 95% CI 2.36-6.33, p < 0.001; (3) ≤ 100 versus > 100 MME/day: RR 4.28, 95% CI 2.61-7.1, p < 0.001; and (4) ≤ 50 versus > 50-100 MME/day: RR 3.09, 95% CI 1.84-5.18, p < 0.001). Heterogeneity was explained by the type of overdose event, inpatient or outpatient status, and length of observation. Type of pain (cancer or non-cancer pain) had no impact on heterogeneity.

LIMITATIONS

The definition of exposure in studies included in the meta-analysis was heterogeneous. Some studies defined exposure as the filling of a prescription while others defined exposure as the prescription of an opioid to the patient, and all studies assumed that patients took the prescribed opioid. Medications that may contribute to overdose, such as benzodiazepines and other drugs, were not considered.

CONCLUSIONS

A significantly increased risk of inadvertent prescription opioid overdose was found with 20-50 MME/day, with fatality more likely with opioid doses above 50 MME/day, although extensive heterogeneity was found with the dose comparisons. Clinicians should inform patients of this risk and monitor them closely.

PROTOCOL REGISTRATION

This protocol was registered with PROSPERO 2017: CRD42017058426.

Effect of a high dosage opioid prior authorization policy on prescription opioid use, misuse, and overdose outcomes

BACKGROUND

High dosage opioid use is a risk factor for opioid-related overdose commonly cited in guidelines, recommendations, and policies. In 2012, the Oregon Medicaid program developed a prior authorization policy for opioid prescriptions above 120 mg per day morphine equivalent dose (MED). This study aimed to evaluate the effects of that policy on utilization, prescribing patterns, and health outcomes.

METHODS

Using administrative claims data from Oregon and a control state (Colorado) between 2011 and 2013, we used difference-in-differences analyses to examine changes in utilization, measures of high risk opioid use, and overdose after introduction of the policy. We also evaluated opioid utilization in a cohort of individuals who were high dosage opioid users before the policy.

RESULTS

Following implementation of Oregon's high dosage policy, the monthly probability of an opioid fill over 120 mg MED declined significantly by 1.7 percentage points (95% confidence interval [CI]; -2.0% to -1.4%), whereas it increased significantly by 1.0 percentage points (95% CI 0.4% to 1.7%) for opioid fills &lt; 61 mg MED. Fills of medications used to treat neuropathic pain also increased by 1.2 percentage points (95% CI 0.7% to 1.8%). The monthly probability of multiple pharmacy use declined by 0.1 percentage points (-0.2% to -0.0) following the prior authorization, but there were no significant changes in ED encounters or hospitalizations for opioid overdose. Among individuals who were using a high dosage opioid before the policy, there was a 20.3 percentage point (95% CI -15.3% to -25.3%) decline in estimated probability of having a high dosage fill after the policy.

CONCLUSIONS

Oregon's prior authorization policy was effective at reducing high dosage opioid prescriptions. While multiple pharmacy use also declined, we found no impact on opioid overdose were observed.

Influence of Ethanol on Oxycodone-induced Respiratory Depression

Background

Respiratory depression is a potentially fatal complication of opioid use, which may be exacerbated by simultaneous ethanol intake. In this three-way sequential crossover dose-escalating study, the influence of coadministration of oral oxycodone and intravenous ethanol was assessed on resting ventilation, apneic events and the hypercapnic ventilatory response in healthy young and older volunteers.

Methods

Twelve young (21 to 28 yr) and 12 elderly (66 to 77 yr) opioid-naive participants ingested one 20 mg oxycodone tablet combined with an intravenous infusion of 0, 0.5, or 1 g/l ethanol. Resting respiratory variables and the primary outcome, minute ventilation at isohypercapnia (end-tidal partial pressure of carbon dioxide of 55 mmHg or VE55), were obtained at regular intervals during treatment.

Results

Oxycodone reduced baseline minute ventilation by 28% (P &lt; 0.001 vs. control). Ethanol caused a further decrease of oxycodone-induced respiratory depression by another 19% at 1 g/l ethanol plus oxycodone (P &lt; 0.01 vs. oxycodone). Ethanol combined with oxycodone caused a significant increase in the number of apneic events measured in a 6-min window with a median (range) increase from 1 (0 to 3) at 0 g/l ethanol to 1 (0 to 11) at 1 g/l ethanol (P &lt; 0.01). Mean (95% CI) VE55 decreased from 33.4 (27.9 to 39.0) l/min (control) to 18.6 (15.6 to 21.6) l/min (oxycodone, P &lt; 0.01 vs. control) and to 15.7 (12.7 to 18.6) l/min (oxycodone combined with ethanol, 1 g/l; P &lt; 0.01 vs. oxycodone).

Conclusions

Ethanol together with oxycodone causes greater ventilatory depression than either alone, the magnitude of which is clinically relevant. Elderly participants were more affected than younger volunteers.

Assessing the accuracy of opioid overdose and poisoning codes in diagnostic information from electronic health records, claims data, and death records

PURPOSE

The purpose of this study is to assess positive predictive value (PPV), relative to medical chart review, of International Classification of Diseases (ICD)-9/10 diagnostic codes for identifying opioid overdoses and poisonings.

METHODS

Data were obtained from Kaiser Permanente Northwest and Northern California. Diagnostic data from electronic health records, submitted claims, and state death records from Oregon, Washington, and California were linked. Individual opioid-related poisoning codes (e.g., 965.xx and X42), and adverse effects of opioids codes (e.g., E935.xx) combined with diagnoses possibly indicative of overdoses (e.g., respiratory depression), were evaluated by comparison with chart audits.

RESULTS

Opioid adverse effects codes had low PPV to detect overdoses (13.4%) as assessed in 127 charts and were not pursued. Instead, opioid poisoning codes were assessed in 2100 individuals who had those codes present in electronic health records in the period between the years 2008 and 2012. Of these, 10/2100 had no available information and 241/2100 were excluded potentially as anesthesia-related. Among the 1849 remaining individuals with opioid poisoning codes, 1495 events were accurately identified as opioid overdoses; 69 were miscodes or misidentified, and 285 were opioid adverse effects, not overdoses. Thus, PPV was 81%. Opioid adverse effects or overdoses were accurately identified in 1780 of 1849 events (96.3%).

CONCLUSIONS

Opioid poisoning codes have a predictive value of 81% to identify opioid overdoses, suggesting ICD opioid poisoning codes can be used to monitor overdose rates and evaluate interventions to reduce overdose. Further research to assess sensitivity, specificity, and negative predictive value are ongoing. Copyright © 2017 John Wiley & Sons, Ltd.

Cohort Study of the Impact of High-Dose Opioid Analgesics on Overdose Mortality

OBJECTIVE

Previous studies examining opioid dose and overdose risk provide limited granularity by milligram strength and instead rely on thresholds. We quantify dose-dependent overdose mortality over a large spectrum of clinically common doses. We also examine the contributions of benzodiazepines and extended release opioid formulations to mortality.

DESIGN

Prospective observational cohort with one year follow-up.

SETTING

One year in one state (NC) using a controlled substances prescription monitoring program, with name-linked mortality data.

SUBJECTS

Residential population of North Carolina (n = 9,560,234), with 2,182,374 opioid analgesic patients.

METHODS

Exposure was dispensed prescriptions of solid oral and transdermal opioid analgesics; person-years calculated using intent-to-treat principles. Outcome was overdose deaths involving opioid analgesics in a primary or additive role. Poisson models were created, implemented using generalized estimating equations.

RESULTS

Opioid analgesics were dispensed to 22.8% of residents. Among licensed clinicians, 89.6% prescribed opioid analgesics, and 40.0% prescribed ER formulations. There were 629 overdose deaths, half of which had an opioid analgesic prescription active on the day of death. Of 2,182,374 patients prescribed opioids, 478 overdose deaths were reported (0.022% per year). Mortality rates increased gradually across the range of average daily milligrams of morphine equivalents. 80.0% of opioid analgesic patients also received benzodiazepines. Rates of overdose death among those co-dispensed benzodiazepines and opioid analgesics were ten times higher (7.0 per 10,000 person-years, 95 percent CI: 6.3, 7.8) than opioid analgesics alone (0.7 per 10,000 person years, 95 percent CI: 0.6, 0.9).

CONCLUSIONS

Dose-dependent opioid overdose risk among patients increased gradually and did not show evidence of a distinct risk threshold. There is urgent need for guidance about combined classes of medicines to facilitate a better balance between pain relief and overdose risk.

The effect of an abuse-deterrent opioid formulation (OxyContin) on opioid abuse-related outcomes in the postmarketing setting

An extended‐release opioid analgesic (OxyContin, OC) was reformulated with abuse‐deterrent properties to deter abuse. This report examines changes in abuse through oral and nonoral routes, doctor‐shopping, and fatalities in 10 studies 3.5 years after reformulation. Changes in OC abuse from 1 year before to 3 years after OC reformulation were calculated, adjusted for prescription changes. Abuse of OC decreased 48% in national poison center surveillance systems, decreased 32% in a national drug treatment system, and decreased 27% among individuals prescribed OC in claims databases. Doctor‐shopping for OC decreased 50%. Overdose fatalities reported to the manufacturer decreased 65%. Abuse of other opioids without abuse‐deterrent properties decreased 2 years later than OC and with less magnitude, suggesting OC decreases were not due to broader opioid interventions. Consistent with the formulation, decreases were larger for nonoral than oral abuse. Abuse‐deterrent opioids may mitigate abuse and overdose risks among chronic pain patients.

Trends in Opioid Dosing Among Washington State Medicaid Patients Before and After Opioid Dosing Guideline Implementation

By 2007, opioid-related mortality in Washington state (WA) was 50% higher than the national average, with Medicaid patients showing nearly 6 times the mortality of commercially-insured patients. In 2007, the WA Interagency Guideline on Opioid Dosing for Chronic Non-cancer Pain was released, which recommended caution in prescribing >120 mg morphine-equivalent dose per day for patients not showing clinically meaningful improvement in pain and function. We report on opioid dosing in the WA Medicaid fee-for-service population for 273,200 adults with a paid claim for an opioid prescription between April 1, 2006 and December 31, 2010. Linear regression was used to test for trends in dosing over that time period, with quarter-year as the independent variable and median daily dose as the dependent variable. Prescription opioid use among WA Medicaid adults peaked in 2009, as evidenced by the unique number of opioid users (105,232), the total number of prescriptions (556,712), and the total person-years of prescription opioid use (29,442). Median opioid dose was unchanged from 2006 to 2010 at 37.5 mg morphine-equivalent dose, but doses at the 75th, 90th, 95th, and 99th percentiles declined significantly (P < .001). These results suggest that opioid treatment guidelines with dosing guidance may be able to reduce high-dose opioid use without affecting the median dose used.

PERSPECTIVE

Some fear that opioid dosing guidelines might restrict access to opioid therapy for patients who could benefit. However, there is evidence that high-dose opioid therapy entails significant risks without demonstrated benefit. These findings indicate that high-dose opioid therapy can be reduced without altering median opioid dose in a Medicaid population.