The effect of state policies on rates of high-risk prescribing of an initial opioid analgesic

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.

Disparities in access but not outcomes: Medicaid versus non-Medicaid patients in multidisciplinary chronic pain rehabilitation

Purpose: There are known disparities in chronic pain severity, treatment, and opioid-related risks amongst individuals from lower socioeconomic status, including Medicaid beneficiaries, but little is known about whether Medicaid beneficiaries benefit in a similar way from multidisciplinary chronic pain rehabilitation. This study investigated differences in clinical outcomes between Medicaid and non-Medicaid beneficiaries who completed a 3-week multidisciplinary chronic pain rehabilitation program.Methods: Participants (N = 131) completed a broad range of clinical measures pre- and post-treatment including pain severity, pain interference, depression, anxiety, objective physical functioning, and opioid misuse risk. Patients with Medicaid were compared with non-Medicaid patients in terms of baseline characteristics and rate of change, utilizing two-factor repeated measures analyses of variance.Results: There were baseline characteristic differences, with Medicaid beneficiaries being more likely to be African American, have higher rates of pain, worse physical functioning, and lower rates of opioid use. Despite baseline differences, both groups demonstrated significantly improved outcomes across all measures (p<.001) and no significant difference in rate of improvement.Conclusions: Results suggest that pain rehabilitation is as effective for Medicaid recipients as non-Medicaid recipients. Patients with Medicaid are particularly vulnerable to disparities in treatment, so efforts to expand access to multidisciplinary pain treatments are warranted.

Impact of Statewide Statute Limiting Days' Supply to Opioid-Naive Patients

INTRODUCTION

To address the ongoing opioid crisis, states use policy enactment to restrict prescribing by licensed healthcare providers and mandate the use of Prescription Drug Monitoring Programs. There have been mixed results regarding the effectiveness of such state policies. The purpose of this study is to evaluate the impact of Colorado Senate Bill 18-022, which limits opioid prescriptions to ≤7-day supply among patients without an opioid prescription in the previous year (i.e., are opioid naive).

METHODS

This is a retrospective interrupted time-series analysis of opioid prescribing to evaluate the weekly percentage of opioid prescriptions consistent with statutory limits for ≤7-day supply among opioid-naive patients before and after enactment using Prescription Drug Monitoring Programs data from May 21, 2017 to May 25, 2019. Statistical analysis was performed in 2021-2022.

RESULTS

The weekly percentage of opioid prescriptions ≤7-day supply increased by an average of 0.12% per week (p<0.0001) from 79.7% to 87.4% in the week before enactment. The week after enactment, the average increased by 0.2% (p=0.67). The year after enactment, the average weekly percentage change was 0.07% per week, a 0.05% decrease (p=0.01).

CONCLUSIONS

Statutory limits on days' supply among opioid-naive patients had little impact on opioid prescribing in Colorado. Legislating limits on opioid prescribing should be evaluated using Prescription Drug Monitoring Program data and considered for deimplementation when not impactful.

Association between prescription drug monitoring programs use mandates and prescription stimulants received by Medicaid enrollees

INTRODUCTION

Prescription drug monitoring program (PDMP) use mandates are an important policy tool to curb nonmedical opioid use. However, data are scarce about their efficacy on other commonly used prescription drugs such as stimulants.

METHODS

We used 2010-2020 state-level secondary data from Medicaid State Drug Utilisation Data and quasi-experimental difference-in-differences research design to estimate the association between PDMP use mandates and population-adjusted stimulants (amphetamines and methylphenidate) prescribing outcomes: (i) number of prescriptions filled; and (ii) total amount reimbursed in US dollars. To account for heterogeneity in mandates across US states, two policy variables were considered: limited and expansive. Limited PDMP use mandates require prescribers or dispensers to check the PDMP only when prescribing/dispensing opioids or benzodiazepines, while expansive PDMP use mandates are non-specific to opioids/benzodiazepines and require prescribers or dispensers to check the PDMP when prescribing/dispensing targeted controlled substances in Drug Enforcement Agency Schedule II-V. The sample included 49 US states and the District of Columbia. Nevada was excluded since it implemented the PDMP mandate before the period of analysis.

RESULTS

The state-wide implementation of the PDMP use mandate, either limited or expansive, was not associated with the number of prescriptions filled or the total amount reimbursed in US dollars for stimulants among Medicaid enrollees.

DISCUSSION AND CONCLUSION

There was no evidence for the associations between PDMP use mandates and stimulant prescribing among Medicaid enrollees. Future works are encouraged to replicate the study in other populations and with longer post-period analysis when the impact of the mandates might be more successfully materialised.

Prescription drug monitoring programs use mandates and prescription stimulant and depressant quantities

BACKGROUND

While the mandate to check patients' prescription history in Prescription Drug Monitoring Program (PDMP) database before prescribing/dispensing controlled drugs has been shown to be an important tool to curb opioid abuse, less is known about whether the mandate can reduce the misuse of other commonly abused prescription drugs. We examined whether PDMP use mandates were associated with changes in prescription stimulant and depressant quantities.

METHODS

Using data from Automated Reports and Consolidate Ordering System (ARCOS), we employed difference-in-differences design to estimate the association between PDMP use mandates and prescription stimulant and depressant quantities in 50 U.S. states and the District of Columbia from 2006 to 2020. Limited PDMP use mandate was specific only to opioids or benzodiazepines. Expansive PDMP use mandate was non-specific to opioid or benzodiazepine and required prescribers/dispensers to check PDMP when prescribing/dispensing targeted controlled substances in Schedule II-V. The main outcomes were population-adjusted prescription stimulant (amphetamine, methylphenidate, lisdexamfetamine) and depressant (amobarbital, butalbital, pentobarbital, secobarbital) quantities in grams.

RESULTS

There was no evidence that limited PDMP use mandate was associated with a reduction in the prescription stimulant and depressant quantities. However, expansive PDMP use mandate that was non-specific to opioid or benzodiazepine and required prescribers/dispensers to check PDMP when prescribing/dispensing targeted controlled substances in Schedule II-V was associated with 6.2% (95% CI: -10.06%, -2.08%) decline in prescription amphetamine quantity.

CONCLUSION

Expansive PDMP use mandate was associated with a decline in prescription amphetamine quantity. Limited PDMP use mandate did not appear to change prescription stimulant and depressant quantities.

Association of a State Prescribing Limits Policy with Opioid Prescribing and Long-term Use: an Interrupted Time Series Analysis

BACKGROUND

Prescription opioids were a major initial driver of the opioid crisis. States have attempted to reduce overprescribing by enacting policies that limit opioid prescriptions, but the impacts of such policies on new prescribing and subsequent transitions to long-term use are not fully understood.

OBJECTIVE

To examine the association of implementation of a state prescribing limits policy with opioid prescribing and transitions to long-term opioid use.

DESIGN

Interrupted time series analyses assessing trends in new opioid prescriptions and long-term use before and after policy implementation.

PATIENTS

A total of 130,591 New Jersey Medicaid enrollees ages 18-64 who received an initial opioid prescription from January 2014 to December 2019.

INTERVENTIONS

New Jersey's opioid prescribing limit policy implemented in March 2017.

MAIN MEASURES

Total new opioid prescriptions, percentage of new prescriptions with >5 days' supply, and transition to long-term opioid use, defined as having opioid supply on day 90 after the initial prescription.

KEY RESULTS

Policy implementation was associated with a significant monthly increase in new opioid prescriptions of 0.86 per 10,000 enrollees, halving the pre-policy decline in the prescribing rate. Among new opioid prescriptions, the percentage with >5 days' supply decreased by about 1 percentage point (-0.76 percentage points, 95% CI -0.89, -0.62) following policy implementation. However, policy implementation was associated with a significant monthly increase in the rate of initial prescriptions with supply on day 90 (9.95 per 10,000 new prescriptions, 95% CI 4.80, 15.11) that reversed the downward pre-implementation trend.

CONCLUSIONS

The New Jersey policy was associated with a reduction in initial prescriptions with >5 days' supply, but not with an overall decline in new opioid prescriptions or in the rate at which initial prescriptions led to long-term use. Given their only modest benefits, policymakers and clinicians should carefully weigh potential unintended consequences of strict prescribing limits.

An Exploratory Analysis of Differential Prescribing of High-Risk Opioids by Insurance Type Among Patients Seen by the Same Clinician

BACKGROUND

Insurance status may influence quality of opioid analgesic (OA) prescribing among patients seen by the same clinician.

OBJECTIVE

To explore how high-risk OA prescribing varies by payer type among patients seeing the same prescriber and identify clinician characteristics associated with variable prescribing DESIGN: Retrospective cohort study using the 2016-2018 IQVIA Real World Data - Longitudinal Prescription PARTICIPANTS: New OA treatment episodes for individuals ≥ 12 years, categorized by payer and prescriber. We created three dyads: prescribers with ≥ 10 commercial insurance episodes and ≥ 10 Medicaid episodes; ≥ 10 commercial insurance episodes and ≥ 10 self-pay episodes; and ≥ 10 Medicaid episodes and ≥ 10 self-pay episodes.

MAIN OUTCOME(S) AND MEASURE(S)

Rates of high-risk episodes (initial opioid episodes with > 7-days' supply or prescriptions with a morphine milliequivalent daily dose >90) and odds of being an unbalanced prescriber (prescribers with significantly higher percentage of high-risk episodes paid by one payer vs. the other payer) KEY RESULTS: There were 88,352 prescribers in the Medicaid/self-pay dyad, 172,392 in the Medicaid/commercial dyad, and 122,748 in the self-pay/commercial dyad. In the Medicaid/self-pay and the commercial-self-pay dyads, self-pay episodes had higher high-risk episode rates than Medicaid (16.1% and 18.4%) or commercial (22.7% vs. 22.4%). In the Medicaid/commercial dyad, Medicaid had higher high-risk episode rates (21.1% vs. 20.4%). The proportion of unbalanced prescribers was 11-12% across dyads. In adjusted analyses, surgeons and pain specialists were more likely to be unbalanced prescribers than adult primary care physicians (PCPs) in the Medicaid/self-paydyad (aOR 1.2, 95% CI 1.16-1.34 and aOR 1.2, 95% CI 1.03-1.34). For Medicaid/commercial and self-pay/commercial dyads, surgeons had lower odds of being unbalanced compared to PCPs (aOR 0.6, 95% CI 0.57-0.66 and aOR 0.6, 95% CI 0.61-0.68).

CONCLUSIONS

Clinicians prescribe high-risk OAs differently based on insurance type. The relationship between insurance and opioid prescribing quality goes beyond where patients receive care.

The effects of opioid policy changes on transitions from prescription opioids to heroin, fentanyl and injection drug use: a qualitative analysis

BACKGROUND

Beginning in the 1990s, nonmedical use of prescription opioids (POs) became a major public health crisis. In response to rising rates of opioid dependence and fatal poisonings, measures were instituted to decrease the prescription, diversion, and nonmedical use of POs including prescription drug monitoring programs (PDMPs), pain clinic laws, prescription duration limits, disciplining doctors who prescribed an excessive number of POs, and the advent of abuse deterrent formulations of POs. This paper explores the unintended effects of these policies in the descriptions of why people who use opioids transitioned from PO to injection or heroin/fentanyl use.

METHODS

We conducted 148 in-depth-interviews with people who use prescription opioids nonmedically, fentanyl or heroin from a rural, urban and suburban area in three states, Connecticut, Kentucky and Wisconsin. Interviews with people who use opioids (PWUO) focused on how they initiated their opioid use and any transitions they made from PO use to heroin, fentanyl or injection drug use.

RESULTS

The majority of participants reported initiating use with POs, which they used for medical or nonmedical purposes. They described needing to take more POs or switched to heroin or fentanyl as their tolerance increased. As more policies were passed to limit opioid prescribing, participants noticed that doctors were less likely to prescribe or refill POs. This led to scarcity of POs on the street which accelerated the switch to heroin or fentanyl. These transitions likely increased risk of overdose and HIV/HCV infection.

CONCLUSIONS

A careful analysis of how and why people say they transitioned from PO to heroin or fentanyl reveals many unintended harms of policy changes to prevent overprescribing and diversion. Results highlight the importance of mitigating harms that resulted from policy changes.

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.

Effects of State Opioid Prescribing Laws on Use of Opioid and Other Pain Treatments Among Commercially Insured U.S. Adults

BACKGROUND

There is concern that state laws to curb opioid prescribing may adversely affect patients with chronic noncancer pain, but the laws' effects are unclear because of challenges in disentangling multiple laws implemented around the same time.

OBJECTIVE

To study the association between state opioid prescribing cap laws, pill mill laws, and mandatory prescription drug monitoring program query or enrollment laws and trends in opioid and guideline-concordant nonopioid pain treatment among commercially insured adults, including a subgroup with chronic noncancer pain conditions.

DESIGN

Thirteen treatment states that implemented a single law of interest in a 4-year period and unique groups of control states for each treatment state were identified. Augmented synthetic control analyses were used to estimate the association between each state law and outcomes.

SETTING

United States, 2008 to 2019.

PATIENTS

7 694 514 commercially insured adults aged 18 years or older, including 1 976 355 diagnosed with arthritis, low back pain, headache, fibromyalgia, and/or neuropathic pain.

MEASUREMENTS

Proportion of patients receiving any opioid prescription or guideline-concordant nonopioid pain treatment per month, and mean days' supply and morphine milligram equivalents (MME) of prescribed opioids per day, per patient, per month.

RESULTS

Laws were associated with small-in-magnitude and non-statistically significant changes in outcomes, although CIs around some estimates were wide. For adults overall and those with chronic noncancer pain, the 13 state laws were each associated with a change of less than 1 percentage point in the proportion of patients receiving any opioid prescription and a change of less than 2 percentage points in the proportion receiving any guideline-concordant nonopioid treatment, per month. The laws were associated with a change of less than 1 in days' supply of opioid prescriptions and a change of less than 4 in average monthly MME per day per patient prescribed opioids.

LIMITATIONS

Results may not be generalizable to non-commercially insured populations and were imprecise for some estimates. Use of claims data precluded assessment of the clinical appropriateness of pain treatments.

CONCLUSION

This study did not identify changes in opioid prescribing or nonopioid pain treatment attributable to state laws.

PRIMARY FUNDING SOURCE

National Institute on Drug Abuse.