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Video of the talk is available at: https://vimeo.com/560799955, Conference website with transcript: https://www.fda.gov/drugs/news-events-human-drugs/morphine-milligram-equivalents-current-applications-and-knowledge-gaps-research-opportunities-and, Presentation by Dr. Nabarun Dasgupta at FDA Workshop on June 7-8, 2021. All slides and images are available for free reuse (perpetual, universal) without restrictions., This study was supported by funding from the US Food and Drug Administration and the US Department of Justice (Bureau of Justice Assistance). Funding agencies had no involvement in design, analysis, or interpretation. Views presented are not necessarily those of the funders. Awards: HHSF223201810183C and 2017-PM-BX-K038

Background: Pharmacoepidemiologic studies utilize the days’ supply field in prescription (Rx) claims to classify exposures and outcomes; however, data on the accuracy of days’ supply are lacking. In the United States, days’ supply is calculated at the time of Rx filling. Pharmacists’ interpretation may influence days’ supply calculations leading to variability. Objectives: The objectives of this study are to assess consistency of pharmacists’ calculation of days’ supply for opioid Rxs and identify factors pharmacists consider when calculating days’ supply for a given Rx. Methods: A cross-sectional survey was designed to collect information from Kentucky-licensed pharmacists about opioid analgesic dispensing practices and days’ supply calculations. The survey was distributed electronically via email through the Kentucky Board of Pharmacy. Responses were collected anonymously over a 4-week period in December 2019. Inclusion criterion was experience dispensing opioid analgesics; other questions were voluntary. For days’ supply calculations, pharmacists saw 2 hypothetical opioid Rxs and calculated days’ supply. Additional questions examined factors influencing days’ supply and pharmacists’ perception of the importance of accuracy. Results: Of 753 responses, 643 were eligible. For hydrocodone tablets, 19.4% (n=347) of pharmacists assigned inaccurate days’ supply, ranging from 7 days to 90 days. Common mistakes were 40 and 45 days instead of the correct 30. For morphine solution, days’ supply was inaccurate in 10.0% (n=351), ranging from 2 to 90 days. Common mistakes were 10 and 15 days instead of the correct 7. Most reported considerations when assigning days’ supply were instructions from the prescriber on intended duration (75.5%), third-party payer restrictions (48.4%) and familiarity with practitioners prescribing habits (45.3%). Most pharmacists perceived that accurate days’ supply are important to determine when medication is due to be filled/refilled (89.8%) and to support safe medication use for patients (80.8%), although fewer perceive accuracy as important for calculating morphine milligram equivalents (61.8%) and assessment of doctor shopping in the state prescription drug monitoring program (63.7%). Conclusions: Between 10-20% of pharmacists inaccurately assigned days’ supply values to opioid analgesic Rx. While most believe accuracy in days’ supply is important to dispensing decisions, fewer consider it important for other activities such as surveillance monitoring. The estimated error rate from the survey will be used to inform the design of a validation study using stratification-sampled pharmacy records.

In February 2021, the North Carolina Survivors Union and the Opioid Data Lab detected a substance called xylazine alongside heroin, fentanyl, and some sugars (a common filler). Xylazine is a veterinary tranquilizer that causes central nervous system depression. While it was assessed for human use by the FDA several decades ago, it was ultimately not approved for human use. People who inject xylazine may experience unexpected symptoms, including a slowed pulse, slowed breathing, low blood pressure, and excessive fatigue. Xylazine has also been linked to skin ulceration among people who inject xylazine. In order to inform people who use drugs about xylazine, we developed a flyer containing background information and tips.

Background Morphine-standardized analgesic doses account for molecular potency. 90 milligrams of morphine equivalents (MME) per day are considered a “high dose” risk threshold. Although ubiquitously cited, the “CDC definition” of daily MME lacks a clearly defined denominator. Objectives Assess the sensitivity of denominator-dependency on “high dose” classification across 4 competing definitions. Methods Review of 27 studies cited in the CDC Pain Management Guideline yielded 4 unique definitions. Using Prescription Drug Monitoring Programs data (Jul-Sep 2018), we conducted a population-based cohort study of 3,916,461 patients receiving opioid analgesics in California (CA) and Florida (FL). The outcome was patients deemed “high dose” (>90 MME/day) across 4 definitions. Results In a simple example, a 30-day supply of 2 partially overlapping oxycodone prescriptions have daily MME varying across 4 definitions: 76mg (total days supply); 93mg (on-therapy days); 31mg (fixed observation window); or 105mg (maximum daily dose). Among 9,436,640 prescriptions, 42% overlapped, impacting daily MME. Across definitions, average daily MME varied 3-fold [range: 17-52 (CA), 23-65 mg (FL)]. Across definitions, prevalence of “high dose” individuals ranged 5.9%-14.2% (FL), 3.5%-10.3% (CA). Definitional variation would impact a hypothetical surveillance study trying to establish how much more “high dose” prescribing was present in FL than CA: from 34% to 79% more. Conclusions Previously unrecognized definitional variation confounds surveillance metrics and constrains real-world applicability of observational studies. While 90 MME may have cautionary mnemonic benefits, without harmonization of calculation, its utility is limited. Comparison between studies using daily MME requires explicit attention to definitional variation for validity.

Short panel presentation in Rockefeller Institute Drug Policy Conference, October 14, 2021. Session on: Evidence of Impacts from COVID-19 Policy Changes for Substance Use Disorder Treatments.

Public comments on COVID-19 vaccine side effect surveillance at the US Food and Drug Administration (FDA) Advisory Committee on February 26, 2021. The Janssen (Johnson & Johnson) vaccine was discussed at this meeting. We declare no conflicts of interest.

Supplemental Material, sj-pdf-1-jah-10.1177_08982643211039338 for Sociodemographic and Clinical Predictors of Prescription Opioid Use in a Longitudinal Community-Based Cohort Study of Middle-Aged and Older Adults by Kristin Y. Shiue, Nabarun Dasgupta, Rebecca B. Naumann, Amanda E. Nelson and Yvonne M. Golightly in Journal of Aging and Health

Paper under review at Clinical Journal of Pain. This is the revised version submitted in response to reviewer comments.

Additional file 1. SRQR Guidelines for Reporting Qualitative Research Studies.

Additional file 2. Key Themes of Organizational Communications, Prescriber and Patient Education, and Changes to the EMR System.

Presentation at the National Overdose Prevention Leadership Summit on November 8, 2021. PLENARY SESSION 9:15 am PT - 10:15 am PT. Understanding Opioid DATA from multiple perspectives

In November 2020, Oregon voters passed an historic measure to decriminalize possession of small amounts of all drugs and invest substantially in healthcare, substance use disorder treatment, and harm reduction and social services for people who use drugs. Already several jurisdictions across the U.S. are looking to replicate and improve upon Measure 110 (M110 also known as the Drug Addiction Treatment and Recovery Act of 2020), and there is broad interest in evaluating the impact of the measure. Too often, however, researchers neglect to consult with people on the ground who are directly impacted by policy changes when they craft their evaluations. The failure to do so can lead to evaluations that ask the wrong questions, do not answer questions of interest to the community, or fail to take into account significant confounding variables and complexities that can affect outcomes. In addition, some evaluators focus on outcome measures but never look at how the implementation of a policy (or the failure to implement it fully) impacts those outcomes. High quality evaluations will address how M110 is being operationalized, outcomes linked to those activities, and how the broader context may or may not affect those outcomes. To encourage thoughtful policy evaluations, we describe how M110 changes existing laws related to unregulated substances, and then provide evaluation principles and candidate metrics derived from interviews with people who use drugs (PWUD) in Oregon and our working group.

Meta-analyses Applying a Food and Drug Administration (FDA) method for opioid measurement dilemmas, we used meta-analytic techniques to quantify how much heterogeneity would have been observed across hypothetical state-comparison studies, each applying one of the 4 variants on the same sample (fixed effects). In preliminary analyses, Florida generally had higher opioid use than California, presumably due to an older population, scope of practice legislation and other factors.

Background: Gabapentinoids are increasingly incorporated into multimodal analgesia protocols for surgery. However, these drugs are not approved by the US FDA for use in managing surgical pain , and little is known regarding the effects of this off-label use on prolonged post-surgical opioid use following surgery. Objectives: We estimate the association between preoperative day-of-surgery gabapentinoid administration on the risk of prolonged postsurgical opioid use. Methods: We identified older adults (65+ years) undergoing surgery using electronic health records (EHR) from a large integrated healthcare system in the southeast (2016-2019) . Exposure to preoperative gabapentinoids was measured using inpatient medication administration records on the day of surgery, and the outcome of prolonged opioid use was measured using outpatient medication order s. We used stabilized inverse probability of treatment weights with 1% asymmetric trimming to adjust for patient demographics, baseline health indicators, preoperative pain score, and surgical details. We used log-binomial regression to estimate risk ratios and 95% confidence intervals (Cl) of prolonged opioid use comparing patients who received preoperative gabapentinoids to those who did not. Results: Overall, 17,435 surgical patients met inclusion criteria, of whom 17.2% received preoperative gabapentinoids. The overall observed 90-day risk of prolonged opioid use following surgery was 1.20% (95% Cl: 1.05, 1.38) patients. The adjusted risk ratio of prolonged opioid use comparing patients who received a dose of preoperative gabapentinoids on the day of surgery to those who did not was 1.67 (95% Cl: 0.85,3.23). Conclusions: Using data from a large integrated health system, we did not find evidence that preoperative gabapentinoids reduced the risk of prolonged opioid use in patients undergoing a broad range of surgeries. Off-label use of these medications to manage surgical pain should be carefully evaluated.

The collective purchasing organization, Opioid Safety and Naloxone Network (OSNN) Buyers Club, provides over half of all community-based naloxone distributed in the country and is able to do so at a 30x lower cost than retail nasal spray. But, dwindling supply of the overdose reversal antidote is currently forcing community-based programs to heavily ration. The projected shortfall for 2021 is 1 million naloxone doses. We estimate 12,000 to 18,000 avoidance overdose deaths. In this white paper, we provide a summary about the OSNN Buyers Club purchasing patterns and the estimated toll of the naloxone shortage.

Verbatim extracts of methods used in the evidence base cited in the 2016 CDC Guideline for chronic non-cancer pain with opioids. Source documentation: Ranapurwala SI, Naumann RB, Austin AE, Dasgupta N, Marshall SW. Methodologic limitations of prescription opioid safety research and recommendations for improving the evidence base. Pharmacoepidemiol Drug Saf. 2019 Jan;28(1):4-12. doi: 10.1002/pds.4564. Epub 2018 Jun 3. PMID: 29862602.

Presentation at FDA Workshop on June 7-8, 2021

Verbatim extracts of methods used in the evidence base cited in the 2016 CDC Guideline for chronic non-cancer pain with opioids. Source documentation: Ranapurwala SI, Naumann RB, Austin AE, Dasgupta N, Marshall SW. Methodologic limitations of prescription opioid safety research and recommendations for improving the evidence base. Pharmacoepidemiol Drug Saf. 2019 Jan;28(1):4-12. doi: 10.1002/pds.4564. Epub 2018 Jun 3. PMID: 29862602.

Background: Morphine-standardized analgesic doses are used in clinical practice and research to account for molecular potency. 90 milligrams of morphine equivalents (MME) per day are considered a “high dose” risk threshold in guidelines and laws. Theoretically total MME (numerator) is divided by days supply (denominator) to calculate daily MME. Although ubiquitously cited the “CDC definition” of daily MME lacks a clearly defined denominator. Objectives: To assess the sensitivity of denominator-dependency on “high dose” classification across 4 competing definitions of daily MME. Methods: To identify definitional variants, we examined text descriptions from 27 studies cited in the 2016 CDC Pain Management Guideline, literature, and electronic prescribing tools; our review yielded 4 unique definitions. Using Prescription Drug Monitoring Programs data (Jul-Sep 2018), we conducted a population-based cohort study of 3,916,461 patients who received outpatient opioid analgesics in California (CA) and Florida (FL). The binary outcome was whether patients were deemed “high dose” (>90 MME/day), which we compared across the 4 definitions. We calculated I^2 for heterogeneity attributable solely to definition, and stratified by extended/immediate release. Results: In a simple example, a 30-day supply of 2 partially overlapping oxycodone prescriptions have daily MME varying across 4 definitions: 76mg (total days supply); 93mg (on-therapy days); 31mg (fixed observation window); or 105mg (maximum daily dose). Among 9,436,640 prescriptions, 42% overlapped, which led denominator definitions to impact daily MME values. Across definitions, average daily MME varied 3-fold [range: 17-52 (CA) and 23-65 mg (FL)]. Across the definitions, prevalence of “high dose” individuals ranged 5.9%-14.2% (FL) and 3.5%-10.3% (CA). Definitional variation would impact a hypothetical surveillance study trying to establish how much more “high dose” prescribing was present in FL than CA: from 34% to 79% more. Meta-analyses revealed strong heterogeneity (I^2 range 86%-99%) based solely on MME definition, impacting immediate- and extended-release differentially. In the sensitivity analysis, including unit interval 90.0-to-90.9 in the boundary increased the “high dose” population fraction by 15.4%. Conclusions: Previously unrecognized definitional variation confounds surveillance metrics and constrains real-world applicability of observational studies. While 90 MME may have cautionary mnemonic benefits, without harmonization of calculation, its utility is limited. Comparison between studies using daily MME requires explicit attention to definitional variation for validity.

Background: In drug studies, research designs requiring no prior exposure to certain drug classes may restrict research on important populations. For example, currently marketed abuse-deterrent formulation (ADF) opioids are routinely used in patients with prior prescription opioid exposure. The traditional new user design excludes patients with prior exposure to prescription opioids, hence incident ADF users are not representative of the overall ADF user population. A prevalent new user design, wherein patients are prescribed similar treatments (or potential comparators) before starting the new treatment, likely better represents the intended ADF patient population. Objectives: To evaluate the appropriateness of new user versus prevalent new user design for estimating post-market effectiveness of ADFs and examine patterns of ADF initiation. Methods: We used pharmaceutical claims data from a large private insurer in North Carolina [USA] from 2009-2018. Included patients were new ADF users age 18-64 with 6 months of continuous enrollment prior to their first ADF claim. Incident users were identified as those with no prescription opioid claims in a 6-month washout period prior to ADF initiation. Prevalent new users were identified as those with non-ADF opioid claims during the 6 months before ADF initiation, so long as they also had a 6-month washout period of no opioid claims prior to first non-ADF opioid claim. We compared sample sizes by study design and described ADF utilization patterns. Results: We identified 8,841 eligible patients who initiated an ADF. Of these, 2,332 (26%) were classified as incident users, whereas 6,509 (74%) were prevalent new users and would be excluded in a traditional new user design. Most incident ADF users started with both an ADF and an immediate-release (IR) opioid concurrently (85%). Among prevalent new users, common ADF initiation patterns were: adding an ADF to an IR opioid regimen (43%), an immediate switch from IR opioids to an ADF (15%), and a delayed switch from IR opioids to an ADF (14%). Conclusions: Three-quarters of patients initiating ADFs had prior prescription opioid use and would be excluded in a traditional new user study design. A prevalent new user design would increase sample size and better capture clinically meaningful patients. These findings may apply to studies of other medications where prior exposure is a labeled prerequisite, such as higher dose ER opioids and second-line therapies. Future work will explore prevalent new user designs and consider nuances in ADF initiation such as immediate versus delayed switching by incorporating time-matching to address opioid tolerance.

PowerPoint version of the supplemental images and data.

Background: Abuse-deterrent formulations (ADFs) of extended-release (ER) opioids are manufactured to address opioid abuse. However, little is known about characteristics of patients who initiate ADF opioids, which is important to identify appropriate comparators to address confounding by indication. Objectives: To describe demographics and medical characteristics of patients prescribed ADF and non-ADF ER opioids in two sources of commercial claims. Methods: Using IBM Marketscan commercial claims (Data A) and a large private insurance provider in North Carolina [USA] (Data B) (both 2009-2018), we conducted a retrospective cohort study to examine patterns of ADF opioid use compared to non-ADF ER opioid use. Patients who initiated ADF and non-ADF ER opioids (18-64 years-old) were selected using both a traditional new user design (no opioid claims during the washout period, defined as six-months prior to ER opioid initiation) and a prevalent new user design (allowed non-ER opioid claims during the washout period and excluded the patients with no six-months eligibility prior to the first immediate-release (IR) opioid claim). Patient characteristics including demographics, medications (gabapentin, benzodiazepine, antidepressants, IR opioids), pain-related symptoms, and cancer were measured during the washout period for patients with ADF and non-ADF ER opioids. Results: Among eligible ER opioid initiators in Data A (N=330,728) and B (N=20,992), 31% and 34% initiated with ADF opioids, respectively. Among these patients, demographics were as follows (Data A and B): age [mean (SD)] = 49.4 (11.8) and 48.4 (11.8); male sex = 51.2% and 55.4%. Among patients with non-ADF ER opioids, demographics were as follows (Data A and Data B): age [mean (SD)] = 49.2 (11.4) and 47.8 (11.3); male sex = 45.8% and 50.4%. About 50% and 62% of patients with ADF opioids initiated with IR opioids, whereas 29%and 34% of patients with non-ADF ER opioids initiated with IR opioids in Data A and B, respectively. In both data sources, the prevalence of several types of pain was higher among patients with ADF opioids than in non-ADF ER group, including acute pain (Data A: 54.5% vs. 40.3%; Data B: 56.7% vs. 41.5%), arthritis pain (35.7% vs. 20.1%; 36.4% vs. 22.7%), and chronic pain (84.8% vs. 76.3%; 89.5% vs. 85.3%). The prevalence of use of medications and cancer was higher in patients with non-ADF ER opioids than in patients with ADF opioids in both data sources. Conclusions: Both data sources revealed differences in characteristics between patients with ADF and non-ADF ER opioids. The implications for research design include identifying appropriate comparator groups when examining ADF opioid use related outcomes.

Background: The inability to identify dates of death in insurance claims data is a major limitation to retrospective claims based research. If not an outcome, death is a competing risk and poses a threat to validity when treated as non-informative right censoring. Objectives: We aim to develop a user-friendly public algorithm to predict death within the year of disenrollment using an administrative claims database. Methods: We identified adults (18+ years) with at least 2 years of continuous enrollment prior to disenrollment between 01/2007 and 01/2018. Leveraging unique linkages in addition to data that are typically unavailable in the publicly licensed data, we ascertained date of death from the Social Security Death Index, inpatient discharge status, and death indicators in the administrative data. Models including candidate predictors for age, sex, Census region, month of disenrollment, year of disenrollment, chronic condition indicators (components of the Elixhauser score), and prior healthcare utilization were estimated using used elastic net regression tuned by 5-fold cross-validation and final models evaluated in an independent testing set. Weighted analysis adjusts for rare outcome (i.e., class imbalance). Sensitivity, specificity, and ROC associated with various thresholds of predicted probability to classify death at disenrollment were calculated. Results: Overall, we identified 13,360,460 beneficiaries who disenrolled during the study period, with 5% of patients who died within the year of disenrollment. The strongest predictors of death were age at disenrollment, diagnosis of metastatic cancer in the year prior to death, and type of care received (e.g., inpatient stay, hospice care). Using a prediction threshold of 30%, the algorithm classified death at disenrollment with a sensitivity of 0.684 and specificity of 0.985 (ROC=0.97. At the same prediction threshold, the weighted algorithm classified death with a sensitivity of .947 and a specificity of 0.898 (ROC=.973). Conclusions: Our algorithm uses publicly defined chronic conditions and utilization patterns that are easy to implement in claims data and predicts death at disenrollment with high specificity and varying sensitivity depending on the chosen prediction threshold. Users can easily implement the algorithm and can choose the prediction threshold (balancing sensitivity and specificity) to meet the needs of the specific study at hand.

Skin and soft tissue infections include abscesses and cellulitis. These infections can result in serious health complications among people who use drugs, particularly if high-quality treatment is unavailable. Traditional healthcare treatment settings are often unwelcoming and inaccessible to people who use drugs, potentially leading to delays in getting necessary care. Our team conducted a health needs assessment among participants of five syringe services programs in North Carolina. Representatives from the syringe services programs administered surveys during July through September 2020. Participants were asked about their experiences with skin and soft tissue infections, healthcare experiences associated with these infections, and recommendations to improve quality of care. This project was conceptualized and led by people with lived experience of drug use. This project includes a survey tool that was designed by a multidisciplinary team with expertise in a wide range of fields. Team members include those with lived experience of drug use and those with training in public health, epidemiology, clinical care, and qualitative research. Additional survey results are forthcoming.

Background: Timely drug overdose mortality surveillance is key to informing public health action to reduce overdose-related fatalities. States are increasingly using linked data sources to enhance surveillance activities, yet approaches to their effective utilization and analyses are needed. Objectives: The objective of this study is to describe the development and utilization of analytical tools for rapid, ongoing monitoring of drug overdose trends in Kentucky (KY) and decedents’ exposure to prescribed controlled substances (CS). Methods: KY established a monthly process of linking all-cause death certificate (DC) with prescription drug monitoring program (DC-PDMP) data to enhance mortality surveillance. Using provisional 2018-2020 DC-PDMP data we developed scheduled quarterly analytical reports. Drug overdose deaths are identified based on underlying cause of death (ICD-10 X40-X44, X60-X64, X85, or Y10-Y14); involved drugs/drug classes are identified from multiple cause of death codes (T36 – T50). Common contributing substances are identified from DC cause of death section text fields. Drugs listed on DCs are compared with decedents’ past 90 days CS prescriptions. Results: KY resident drug overdose deaths accounted for 2.8% of all-cause mortality, but among age group 26-40 years, 28.6% of all-cause deaths were due to drug overdose. Drug overdose decedents were disproportionally male (65.4% vs. 51.8% among all-cause deaths). From 2018 to 2020, the number of drug overdose deaths increased 42%. Deaths involving synthetic opioids and psychostimulants increased (56.2%vs 71.7% and 27.3% vs 35.1%, respectively) and deaths involving heroin (10.4% vs 6.0%), benzodiazepines (24.1% vs 15.3%), cocaine (9.6% vs 8.4%) and natural/semi-synthetic opioids (22.7% vs 21.3%) declined. The five substances most frequently listed in the DC in 2020 were fentanyl, methamphetamine, 4-ANPP, gabapentin, and acetyl fentanyl. Sixty-three percent of deaths involving natural/semi- synthetic opioids and 76% of cases involving benzodiazepines had no dispensed prescriptions for those drug classes in the previous 90 days, suggesting possible diversion. A historically high level of drug overdose deaths was observed in the first months of COVID-19 pandemic, with April-June 2020 overdose deaths (n=557), 80%higher than the same period in 2019. Conclusions: The analytical enhancement of KY’s drug overdose surveillance supports rapid assessment to inform public health action and provides a rich dataset for pharmacoepidemiologic studies.

Equations describing 4 definitions for calculating milligrams of morphine equivalents (MME) per day for opioid analgesics.

Clinical consequences of injecting solid pharmaceutical excipients (talc, starch) include serious vascular and pulmonary damage. Yet other harms have not been systematically cataloged. We conducted a comprehensive literature search in December 2019 across four bibliographic databases, including PubMed, Embase, Scopus, and Sociological Abstracts. Search terms were developed that focused on three elements: brand & generic drugs in four classes (barbiturates, benzodiazepines, stimulants and opioids), inactive ingredients, and injection.

We had been developing new statistical theories and methods to address differential dropouts during trial enrollment, as part of a dissertation project at the University of North Carolina Gillings School of Global Public Health, in the Department of Biostatistics (Elizableth Ajazi, Committee Chair: Todd Schwartz, Advisor: Steve Marshall). The applied example we been working on uses recent publicly released data files from NIDA-CTN-0051 (ClinicalTrials.gov NCT02032433). The primary study report was published in The Lancet on January 27, 2018, entitled "Comparative effectiveness of extended-release naltrexone versus buprenorphine-naloxone for opioid relapse prevention (X:BOT): a multicentre, open-label, randomised controlled trial" by Lee et al. We were able to replicate the findings for the primary endpoints on efficacy. However, our attempt to replicate the primary safety outcome, overdose, failed. Suspecting we were not replicating the study properly, we examined the adverse event data meticulously. To our surprise we found more patients with overdose in the public file than in the published report.

Background: In response to concerns about opioid addiction, some states now limit the days supplied (DS) for initial postoperative prescriptions. However, few studies have examined the impact of these policy changes on prolonged opioid use in the population. Objectives: To a) examine the gradient of risk of prolonged postsurgical opioid use based on the initial prescription duration, and b) estimate the potential impact of varying prescribing limits on risk of prolonged postsurgical opioid use. Methods: We used a 20% random sample of Medicare claims (2007-2016) to identify opioid naive patients undergoing invasive surgery. Prolonged use was defined as at least 1 Rx in each of 3 consecutive 30-day windows immediately following surgery. We calculated 90-day risk of prolonged use comparing patients at a given DS level to patients receiving longer initial prescriptions. Adjusted risk differences (aRD) were obtained via standardized mortality ratio weights (adjusted for demographics, surgical characteristics, baseline medication use and comorbidities), comparing patients with a Rx greater than a given prescribing limit versus those at the limit. Estimated number of averted cases was also quantified. Results: We identified 749,269 patients who received a perioperative opioid (median DS=5, mean age=73yr, 44% male). The overall risk of prolonged use was 14.0 (95%CI: 13.7, 14.3) per 1000 exposed patients, increasing with days supplied (14.7 for >2 days to 34.4 for >15 days). Among patients with >2 DS (n=615,490; 92%), we estimated 3.3 (1.0, 5.6)/1000 additional cases of prolonged opioid use compared to those receiving 2 DS. Among patients receiving >7 days (n=143,408; 22%), a common limit in state laws, the aRD was nearly null (-0.1/1000). At 15+ days (n=21,382; 3%), we estimated 3.5 (-0.6, 7.6)/1,000 additional cases compared to those receiving exactly 15 days. The estimated number of potentially averted cases of prolonged opioid use ranged from 10,144 (2 days) to 373 (15 days). Conclusions: We illustrate a method to examine potential impacts of prescribing limits. While risk of prolonged postsurgical opioid use increased as patients received larger initial DS, the number of prolonged use cases theoretically preventable by prescribing limits differed by orders of magnitude depending on the number of patients above the proposed limit. While most laws focus on DS limits, results for quantity and dosage dispensed show similar trends and will also be presented, along with procedure specific (knee arthroplasty, hernia repair, cholecystectomy) results.