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Official websites use. Share sensitive information only on official, secure websites. Using data from Truven Health MarketScan Commercial Claims and Encounters Database between and , we studied the effects of medical and recreational marijuana laws on opioid prescribing in employer-sponsored health insurance. The reduction associated with MMLs was predominately in people aged 55—64, whereas the reduction associated with RMLs was largely in people aged 35—44 and aged 45— Our findings suggest that both MMLs and RMLs have the potential to reduce opioid prescribing in the privately insured population, especially for the middle-aged population. Keywords: medical marijuana laws, pain management, prescription opioids, recreational marijuana laws. The opioid epidemic in the United States has reached a crisis level. Excessive prescribing of opioids for pain management is viewed as a major driver of the ongoing opioid epidemic in the United States Manchikanti et al. Prescription opioids are primarily used for adult pain management in the United States e. We contribute to the growing literature by examining how state MMLs and RMLs may affect opioid prescribing in the working age population age from 18 to 64 with employer-sponsored health insurance and by exploring the heterogeneous effects of the marijuana laws in different age groups. Our study population is of particular importance in the current opioid crisis, which is largely a crisis in the working age population. The opioid overdose death rates of working age population age from 18 to 64 are substantially higher than those of other age groups and have increased significantly since Supplementary Figure A1. Particularly, the United States opioid crisis is also a midlife crisis. Drug overdose deaths, especially opioid-related drug overdose deaths, disproportionally contributed to the mortality rate of individuals aged 45 to 54 Supplementary Figure A1. Our study looks into different age groups among individuals with employer-sponsored health insurance, thus better capturing the at-risk population than the previously studied Medicare and Medicaid populations Bradford et al. The effects of MMLs and RMLs on opioid prescribing depend on whether marijuana is a substitute for or complement to prescription opioids as both laws de facto lower the price of qualified marijuana use through removing legal penalties and increasing marijuana supply. State MMLs authorize both adults and minors to use marijuana to treat qualified conditions. Conditions qualified for medical marijuana use vary from state to state, but generally include severe or chronic pain, as well as other conditions, such as cancer, glaucoma, acquired immunodeficiency syndrome AIDS or human immunodeficiency virus HIV positive , and Hepatitis C. The majority of the medical marijuana states require patient registration, meaning that patients generally need to provide a physician written certification, in exchange for legal protection. Some states provide affirmative defense for medical use of marijuana even if self-claimed medical marijuana patients fail to register with states PDAPS, ; ProCon. State RMLs i. Therefore, the laws provide additional legal protection for people who were not qualified as medical marijuana patients to use marijuana for various purposes, including self-medicating. Bradford et al. Wen and Hockenberry find that MMLs and RMLs are associated with reductions in opioid prescribing rates and spending in Medicaid enrollees between and Shi et al. McMichael et al. MMLs and RMLs are also found to reduce harms related to opioid use, such as opioid-related overdose deaths Bachhuber et al. We used the Truven Health MarketScan Commercial Claims and Encounters Database between and , which captures medical claims and encounters of a national and state representative sample of active employees and their dependents, early retirees, and Consolidated Omnibus Budget Reconciliation Act COBRA enrollees. We also limited our sample to those aged 18—64 with at least one-year continuous enrollment enrollment span greater than or equal to days. Please see Supplementary Table A1 for the number of enrollees in each state and each year. Our main outcome is monthly MME 3 , 4 per enrollee. MME is the most commonly used and best available way to standardize prescription opioids according to the formulation, strength, and dosage. We identified opioid prescriptions based on Medispan Generic Product Identifiers. We also excluded buprenorphine prescriptions that are commonly prescribed for medication-assisted treatment of opioid addiction e. We further studied MME per enrollee separately by age groups i. MME per enrollee in each age group was calculated as the total MME prescribed in an age group divided by the total number of enrollees in that age group. We also looked into the sources of changes in MME i. Considering that prescription opioids are primarily used in pain management, while off-label drug use is also a common practice in the United States, we estimated the effects of MMLs and RMLs in pain patients and nonpain patients separately. We identified pain patients based on ICD-9 or ICD codes and included all diagnoses likely to be associated with chronic or acute pain conditions Centers for Disease Control and Prevention, ; Ilgen et al. To explore the intensive margin i. The key independent variables are the implementation of an MML and the implementation of an RML in a given state during a given month. We defined an RML in a state to be in effect if the state provides legal protection for adults who possess or use marijuana for nonmedical purposes complying with the law. Then, we read legal documents through the ProCon. When there was inconsistency in an effective date, we relied on the legal documents to adopt the most possible date. Connecticut and Minnesota had MML in effect at the end of the months, so the effective month is the next month. State-level time-varying covariates include concurrent polices i. Please see Supplementary Table A2 for the descriptive summary of the study variables. To estimate the effects of MMLs and RMLs on opioid prescribing, we used a differences-in-differences DD approach, operationalized through a two-way fixed-effects model:. Y s,t represents the opioid-related outcomes. X s,t is a vector of state-level covariates. Figure 1 lends support to the parallel-trend assumption regarding our policy indicators—that is, in the prepolicy period, changes in MME per enrollee in policy states overtime are not different from those in control states. Notes : Estimates were simultaneously estimated, controlling for state-level covariates, state fixed effects, year-month fixed effects, and state-specific linear time trends. Standard errors were clustered at the state level. One month prior to a law effect month was the excluded dummy in the estimation. Specifically, the implementation of MMLs was associated with a reduction of 2. The implementation of RMLs was associated with a reduction of 4. Notes : Standard errors in parentheses. Baseline predicted mean was calculated as the average of predicted values when setting mml i,t and rml i , t to 0, and leaving the other covariates as the observed values. An event analysis with lag and lead policy indicators allows us to estimate the differential effects of MMLs and RMLs on the basis of the current month relative to the effective date Model, ; Figure 1. We discerned no prepolicy difference in MME per enrollee between states with and without marijuana laws, which lends weight to the parallel-trend assumption of the DD approach. When examining the changes in MME per enrollee across age groups Figure 1 ; Supplementary Table A5 , we found that the reduction associated with MMLs was concentrated in the age 45—54 group, whereas the reduction associated with RMLs was concentrated in the age 35—44 and 45—54 groups. In patients with chronic or acute pain conditions, MMLs and RMLs were shown to reduce MME per enrollee through reducing both MME per pain patient prescribed opioids intensive margin and the number of pain patients prescribed opioids per enrollees extensive margin; Table 4 ; Supplementary Table A6. In addition to the policy effects in pain patients, the implementation of MMLs was associated with a reduction in MME per nonpain patient prescribed opioids but not the number of nonpain patients prescribed opioids per enrollees. In comparison, the implementation of RMLs was associated with a reduction in the number of nonpain patients prescribed opioids per enrollees while not MME per nonpain patient prescribed opioids. Some primary diagnoses of the nonpain patients were abdominal pain, chest pain and headache. We classified patients with these conditions as nonpain patients, because for them opioids were not considered appropriate nor commonly prescribed. An MML or RML taking effect does not necessarily mean that the targeted population immediately have legal access to marijuana if the law only protects marijuana use but not commercial production, sales or home cultivation. In the main model, we defined an MML or RML to be in effect as long as the law provides legal protection for marijuana users. Here we define an MML or RML to be in effect if 1 a law or agency rule explicitly allowing medical or recreational marijuana home cultivation has been in effect for at least 2 months the minimum time to grow useable marijuana is about eight weeks 9 , or 2 there is at least one active medical or recreational marijuana dispensary, whichever comes first Supplementary Table A8 and A9. We found that the physical availability of recreational marijuana was associated with a reduction of 8. The effect of the physical availability of recreational marijuana was larger than that of the RML in the main model. However, the physical availability of medical marijuana had no discernable effect on MME per enrollee. This suggests that for medical marijuana users, legal protection may be more important than legal availability of medical marijuana. Effects of legal physical availability of medical marijuana and legal physical availability of recreational marijuana on morphine milligram equivalent MME per enrollee. Baseline predicted mean was calculated as the average of predicted values when setting legal physical availability of medical marijuana in effect and legal physical availability of recreational marijuana in effect to 0 and leaving the other covariates as the observed values. This study advances our understanding of the impact of both MMLs and RMLs on opioid prescribing in the privately insured population. The reduction associated with MMLs was concentrated in the age 55—64 group, whereas the reduction associated with RMLs was largely in the age 35—44 and 45—54 groups Figure 2 ; Supplementary Table A5. With respect to the source of reductions, MMLs and RMLs may have reduced opioid prescribing at both intensive and extensive margins for patients with chronic or acute pain conditions Table 4 ; Supplementary Table A6. The physical availability of recreational marijuana was associated with further reductions in MME beyond the effect of only providing legal protection for recreational marijuana use. The reduction in MME per enrollee aged 45 to 54 associated with RMLs was the largest across all age groups, and the economically significant reductions associated with both laws were concentrated in the middle-aged population. Those results were consistent with the studies that found the use of marijuana among middle-aged adults increased significantly from to Han et al. The increasing use of marijuana by middle-aged people might have steered them away from opioid-related harms. However, our study has the following limitations. First, due to the nature of our claim data, we were unable to observe the individual drug substitution mechanism. We only have the records of prescribed opioids that were covered by the employer-sponsored insurance. Therefore, we did not know whether those individuals used marijuana or not, or whether those individuals also bought opioids with cash. It is also possible that random attrition of employers could affect the estimates. Thus, our results did not mean to imply causality. It merits future research to explore the mechanisms between marijuana liberalization and changes in opioid prescribing in the privately insured population. Second, the differential changes in enrollment across states, particularly from to following the implementation of the Affordable Care Act, could potentially bias our main findings and result in spurious correlations. Third, we also do not know the medical potential of marijuana. Marijuansa is still a schedule I drug at the federal level and there was no large-scale clinical trial to investigate its medical use. State MMLs based on limited clinical evidence suggest its use on certain pain conditions, such as neuropathic pain, due to its analgesic effect in humans Abrams et al. More studies, perhaps individual-level surveys, are needed to further discuss the mechanisms of possible opioid and marijuana substitutions among privately insured population. Finally, we were unable to test the underlying mechanisms through which state policies may influence individual behavior. Future research may look into the potential pathways such as price and risk perception. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Restrictions apply to the availability of these data, which were used under license for this study. Research data cannot be not shared under our data use agreement. There are two categories of cannabinoid drugs in the United States. First, we multiplied the unit strength of a prescription opioid by the number of units; second, we multiplied the total strength obtained in the first step by the MME conversion factor; third, we added up the total MME by month for each state. The CDC exempts hospice, palliative care or cancer treatment which often involve intense or prolonged treatment for pain from its guidelines for opioid prescribing Centers for Disease Control and Prevention CDC , Opioid use in noncancer conditions is more likely to be subject to abuse or misuse. The current opioid crisis is largely caused by the use of opioids in the treatment of noncancer pain e. Although most MML and RML states did not have home cultivation rules and legal dispensaries when the legal protection was in place, patients may obtain marijuana through illegal home cultivation or black market purchase Murphy, Nonetheless, anecdotal evidence suggests that even without legal marijuana access, people could grow marijuana at home illegally, or purchase marijuana from the black market. Additional supporting information may be found online in the Supporting Information section at the end of this article. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. Health Econ. Published in final edited form as: Health Econ. Find articles by Jiebing Wen. Find articles by Hefei Wen. Find articles by J S Butler. Find articles by Jeffery C Talbert. Issue date May. PMC Copyright notice. The publisher's version of this article is available at Health Econ. State medical marijuana law MML effective dates, as of December 10, Open in a new tab. State recreational marijuana law effective dates, as of December 10, Marginal effects MME per enrollee The physical availability of medical marijuana 0. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel. The physical availability of medical marijuana. The physical availability of recreational marijuana.

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