Prescription drug monitoring programs: Assessing the association between "best practices" and opioid use in Medicare

Assessing Policy Impacts on Chronic Disease Risk Reduction: The Science and Art of Policy Measurement and Rating Systems

Public policies have been instrumental in influencing population health, and the desire to study their impact led to the development of the fields of policy surveillance and legal epidemiology. The standardized practice of creating policy measurement systems allows researchers to track and evaluate policy impacts across jurisdictions and over time. Policy measures may take many forms, including dichotomous measures, ordinal ratings, composite measures, or scale measures. The policy measures are determined largely based on the research question but should also consider factors impacting policy implementation and equity. Many sources of evidence, including expert input, national standards, scientific evidence, and existing policies, can be used in the development of policy measurement and rating systems. Any system must be tested, reliable, and clearly documented to create a robust and rigorous dataset. This article reviews key considerations for the development of policy measurement and rating systems for use in public health research.

State-level policies and receipt of CDC-informed opioid thresholds among commercially insured new chronic opioid users

OBJECTIVES

To evaluate the association of state-level policies on receipt of opioid regimens informed by Centers for Disease Control and Prevention (CDC) morphine milligram equivalent (MME)/day recommendations.

DESIGN

A retrospective cohort study of new chronic opioid users (NCOUs).

SETTING

Commercially insured plans across the United States using IQVIA PharMetrics® Plus for Academics database with new chronic use between January 2014 and March 2015.

PARTICIPANTS

NCOUs with ≥60-day coverage of opioids within a 90-day period with ≥30-day opioid-free period prior to the date of the first qualifying opioid prescription.

INTERVENTIONS

State-level policies including Prescription Drug Monitoring Program (PDMP) robustness and cannabis policies involving the presence of medical dispensaries and state-wide decriminalization.

MAIN OUTCOME MEASURES

NCOUs were placed in three-tiered risk-based average MME/day thresholds: low (>0 to <50), medium (≥50 to <90), and high (≥90). Multinomial logistic regression was used to estimate the association of state-level policies with the thresholds while adjusting for relevant patient-specific factors.

RESULTS

NCOUs in states with medium or high PDMP robustness had lower odds of receiving medium (adjusted odds ratio [AOR] 0.74; 95 percent confidence interval [CI]: 0.62-0.69) and high (AOR 0.74; 95 percent CI: 0.59-0.92) thresholds. With respect to cannabis policies, NCOUs in states with medical cannabis dispensaries had lower odds of receiving high (AOR 0.75; 95 percent CI: 0.60-0.93) thresholds, while cannabis decriminalization had higher odds of receiving high (AOR 1.24; 95 percent CI: 1.04-1.49) thresholds.

CONCLUSION

States with highly robust PDMPs and medical cannabis dispensaries had lower odds of receiving higher opioid thresholds, while cannabis decriminalization correlated with higher odds of receiving high opioid thresholds.

Identifying Persistent Opioid Use After Surgery: The Reliability of Pharmacy Dispensation Databases

OBJECTIVE

The present study assessed concordance in perioperative opioid fulfillment data between Michigan's prescription drug monitoring program (PDMP) and a national pharmacy prescription database.

BACKGROUND

PDMPs and pharmacy dispensation databases are widely utilized, yet no research has compared their opioid fulfilment data postoperatively.

METHODS

This retrospective study included participants (N=19,823) from 2 registry studies at Michigan Medicine between July 1, 2016, and February 7, 2019. We assessed the concordance of opioid prescription fulfilment between the Michigan PDMP and a national pharmacy prescription database (Surescripts). The primary outcome was concordance of opioid fill data in the 91 to 180 days after surgical discharge, a time period frequently used to define persistent opioid use. Secondary outcomes included concordance of opioid dose and number of prescriptions fulfilled. Multinomial logistic regression analysis examined concordance across key subgroups.

RESULTS

In total, 3076 participants had ≥1 opioid fulfillments 91 to 180 days after discharge, with 1489 (49%) documented in PDMP only, 243 (8%) in Surescripts only, and 1332 (43%) in both databases. Among participants with fulfillments in both databases, there were differences in the number (n=239; 18%) and dose (n=227; 17%). The PDMP database was more likely to capture fulfillment among younger and publicly insured participants, while Surescripts was more likely to capture fulfillment from counties bordering neighboring states. The prevalence of persistent opioid use was 10.7% using PDMP data, 5.5% using Surescripts data only, and 11.7% using both data resources.

CONCLUSIONS

The state PDMP appears reliable for detecting opioid fulfillment after surgery, detecting 2 times more patients with persistent opioid use compared with Surescripts.

Mapping the research addressing prescription drug monitoring programs: A scoping review

ISSUES

Prescription drug monitoring programs are a harm minimisation intervention and clinical decision support tool that address the public health concern surrounding prescription drug misuse. Given the large number of studies published to date and the ongoing implementation of these programs, it is important to map the literature and identify areas for further research to improve practice.

APPROACH

A scoping review was undertaken to identify the research on prescription drug monitoring programs published between January 2015 and April 2021.

KEY FINDINGS

A total of 153 citations were included in this scoping review. The majority of the studies originated from the USA and were quantitative. Results on program effectiveness are mixed and mainly examine their association with opioid-related outcomes. Unintended consequences are revealed in the literature and this review also highlights barriers to program use.

IMPLICATIONS

Overall, findings are mixed despite the large number of studies published to date. Mapping the literature identifies priority areas for further research that can advise policymakers and clinicians on practice improvement.

CONCLUSION

Results on prescription drug monitoring program effectiveness are mixed and mainly examine their association with opioid-related outcomes. This review highlights barriers to prescription drug monitoring program effectiveness related to program use and system integration. Further research is needed in these areas to improve prescription drug monitoring program use and patient outcomes.

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.

Impact of Electronic Prescribing of Controlled Substances on Opioid Prescribing: Evidence From I-STOP Program in New York

New York's Internet System for Tracking Over-Prescribing (I-STOP) Act, requires prescribers in the state to electronically prescribe controlled substances (EPCS). We examine the effects of this mandate on prescribing patterns of opioids for Medicare Part D beneficiaries. Using 2014-2017 CMS Medicare Part D Prescriber Data, we apply a lagged dependent variable regression approach to identify the impact of I-STOP on the prescription of opioids. In the first year of implementation, the number of opioid prescriptions per prescriber decreased by 5.7 per year. The policy had a larger effect on the prescription of short-acting opioids and on prescribers prescribing medication for predominantly younger beneficiaries. Overall, I-STOP resulted in a reduction in the number of beneficiaries being prescribed opioids and in the number of opioid claims in the state of New York, suggesting positive implications for other states intending to curtail opioid overprescribing and misuse through the use of EPCS.

A Rapid Review of the Impact of Systems-Level Policies and Interventions on Population-Level Outcomes Related to the Opioid Epidemic, United States and Canada, 2014-2018

OBJECTIVES

In the United States, rising rates of overdose deaths and recent outbreaks of hepatitis C virus and HIV infection are associated with injection drug use. We updated a 2014 review of systems-level opioid policy interventions by focusing on evidence published during 2014-2018 and new and expanded opioid policies.

METHODS

We searched the MEDLINE database, consistent with the 2014 review. We included articles that provided original empirical evidence on the effects of systems-level interventions on opioid use, overdose, or death; were from the United States or Canada; had a clear comparison group; and were published from January 1, 2014, through July 19, 2018. Two raters screened articles and extracted full-text data for qualitative synthesis of consistent or contradictory findings across studies. Given the rapidly evolving field, the review was supplemented with a search of additional articles through November 17, 2019, to assess consistency of more recent findings.

RESULTS

The keyword search yielded 535 studies, 66 of which met inclusion criteria. The most studied interventions were prescription drug monitoring programs (PDMPs) (59.1%), and the least studied interventions were clinical guideline changes (7.6%). The most common outcome was opioid use (77.3%). Few articles evaluated combination interventions (18.2%). Study findings included the following: PDMP effectiveness depends on policy design, with robust PDMPs needed for impact; health insurer and pharmacy benefit management strategies, pill-mill laws, pain clinic regulations, and patient/health care provider educational interventions reduced inappropriate prescribing; and marijuana laws led to a decrease in adverse opioid-related outcomes. Naloxone distribution programs were understudied, and evidence of their effectiveness was mixed. In the evidence published after our search's 4-year window, findings on opioid guidelines and education were consistent and findings for other policies differed.

CONCLUSIONS

Although robust PDMPs and marijuana laws are promising, they do not target all outcomes, and multipronged interventions are needed. Future research should address marijuana laws, harm-reduction interventions, health insurer policies, patient/health care provider education, and the effects of simultaneous interventions on opioid-related outcomes.

Advances in prescription drug monitoring program research: a literature synthesis (June 2018 to December 2019)

PURPOSE OF REVIEW

Nearly every U.S. state operates a prescription drug monitoring program (PDMP) to monitor dispensing of controlled substances. These programs are often considered key policy levers in the ongoing polydrug epidemic. Recent years have seen rapid growth of peer-reviewed literature examining PDMP consultation and the impacts of these programs on diverse patient populations and health outcomes. This literature synthesis presents a review of studies published from June 2018 to December 2019 and provides relevant updates from the perspective of three researchers in this field.

RECENT FINDINGS

The analyzed studies were primarily distributed across three overarching research focus areas: outcome evaluations (n = 29 studies), user surveys (n = 23), and surveillance (n = 22). Identified themes included growing awareness of the unintended consequences of PDMPs on access to opioids, effects on benzodiazepines and stimulant prescribing, challenges with workflow integration across multiple specialties, and new opportunities for applied data science.

SUMMARY

There is a critical gap in existing PDMP literature assessing how these programs have impacted psychiatrists, their prescribing behaviors, and their patients. Although PDMPs have improved population-level monitoring of controlled substances from medical sources, their role in responding to a drug epidemic shifting to illicitly manufactured drugs is under scrutiny.

Prescription drug monitoring programs: Assessing the association between "best practices" and opioid use in Medicare

OBJECTIVE

To estimate the impact of implementing prescription drug monitoring program (PDMP) best practices on prescription opioid use.

DATA SOURCES

2007-2012 Medicare claims for noncancer pain patients, and PDMP attributes from the Prescription Drug Abuse Policy System.

STUDY DESIGN

We derived PDMP composite scores using the number of best practices adopted by states (range: 0-14), classifying states as either no PDMP, low strength (0 < score < median), or high strength (score ≥ median). Using generalized linear models, we quantified the association between the PDMP score category and opioid use measures-overall and stratified by disability/age. Sensitivity analyses assessed the general Medicare sample regardless of pain diagnoses, individual PDMP characteristics, and compared GEE model findings to models with state fixed effects.

PRINCIPAL FINDINGS

Compared to non-PDMP states, strong PDMP states had lower opioid cumulative doses (-296 mg; 95% CI: -512, -132), days supplied (-7.84; 95% CI: -10.6, -5.04), prescription fill rates (0.97; 95% CI: 0.95, 0.98), and mean daily doses (-2.31 mg; 95% CI: -3.14, -1.48) but greater prevalence of high opioid doses in disabled adults, whereas there was little or no change in older adults. Findings in states with weak PDMPs were substantively similar to those of strong PDMPs. Results from sensitivity analyses were mostly consistent with main findings except there was a null relationship with mean daily doses and high doses in models with state fixed effects.

CONCLUSIONS

Comprehensive or minimal adoption of PDMP best practices was associated with mostly comparable effects on Medicare beneficiaries' opioid use; however, these effects were concentrated among nonelderly disabled adults.