Assignment 2: Introduction and Revised PICOT QuestionRevise your PICOT question on the basis of the feedback you received on Week 3 Assignment 2. Submit your introduction and revised PICOT question as

Impact of Medicaid Expansion on Access to Opioid Analgesic Medications and Medication-Assisted Treatment Alana Sharp, MPH, Austin Jones, MA, Jennifer Sherwood, MSPH, Oksana Kutsa, BS, Brian Honermann, JD, and Gregorio Millett, MPH Objectives.To assess the impact of the expansion of Medicaid eligibility in the United States on the opioid epidemic, as measured through increased access to opioid analgesic medications and medication-assisted treatment.

Methods.Using Medicaid enrollment and reimbursement data from 2011 to 2016 in all states, we evaluated prescribing patterns of opioids and the 3 Food and Drug Admin- istration–approved medications used in treating opioid use disorders by using 2 sta- tistical models. We used difference-in-differences and interrupted time series models to measure prescribing rates before and after state expansions.

Results.Although opioid prescribing per Medicaid enrollee increased overall, we observed no statistical difference between expansion and nonexpansion states. By contrast, per-enrollee rates of buprenorphine and naltrexone prescribing increased more than 200% after states expanded eligibility, while increasing by less than 50% in states that did not expand. Methadone prescribing decreased in all states in this period, with larger decreases in expansion states.

Conclusions.The Medicaid expansion enrolled a population no more likely to be prescribed opioids than the base Medicaid population while signiﬁcantly increasing uptake of 2 drugs used in medication-assisted treatment. (Am J Public Health.2018;108:

642–648. doi:10.2105/AJPH.2018.304338) See also Humphreys, p. 589. T he United States is in the midst of an epidemic of opioid drug use, constituting one of the worst public health crises in recent history. In 2015, more than 52 000 people died from drug overdoses, and early estimates suggest continuing increases in mortality in 2016 and 2017. 1,2 Today, drug overdose is the leading cause of accidental death in the country and contributes to more deaths than do motor vehicle accidents. 3,4 The response to rising opioid use and mortality will require increased access to evidence-based treatment options for people who use drugs. Currently, methadone, buprenorphine, and naltrexone are the only Food and Drug Administration (FDA)– approved medications produced for and used in the treatment of opioid dependence.

According to the World Health Organization and Centers for Disease Control and Pre- vention (CDC), medication-assistedtreatment (MAT) is the most effective regi- men for reducing drug use and is effective in reducing overdose rates, HIV transmission, and criminal activity, while increasing treat- ment retention. 5,6 Yet nearly 9 out of 10 people with substance use disorders do not access treatment services, and lack of health insurance is cited as a primary barrier to accessing treatment by nearly one third of those with an identiﬁed need for treatment. 6 Medicaid is a major funder of substance use treatment programs and in 2015 covered services for 17% of all adults with substance use disorder. 7,8 The Patient Protection and Affordable Care Act (ACA) included severalprovisions that increased access to substance use disorder treatment. In addition to en- abling states to expand Medicaid eligibility to low-income adults, the ACA established guidance such that state benchmark plans must include a speciﬁed set of essential health beneﬁts, including mental health and sub- stance use disorder services. 9In addition, the Mental Health Parity and Addiction Equity Act, which mandates that mental health services be offered at parity with other types of medical care, is expanded to apply to plans in the expansion. Previous workﬁnds that the number of Medicaid-reimbursed pre- scriptions for buprenorphine increased in states that expanded Medicaid, although many low-income adults with substance use disorders in all states continue to have limited access to affordable treatment.

10In addition, Medicaid expansion may increase access by increasing health system capacity, as shown by documented increases in the number of Drug Addiction Treatment Act of 2000–waived physicians eligible to prescribe buprenor- phine in states that expanded Medicaid. 11 While the Medicaid expansion has in- creased access to MAT, it may have similarly increased access to opioid analgesic medica- tions. Historical analyses have found opioid prescribing rates for the Medicaid population to be more than double the rates for non- Medicaid enrollees, raising concerns that Medicaid expansion may inadvertently act as a driver of opioid abuse and addiction. 12 Citing increased access to pharmaceuticals as a potential driver of opioid use and addiction, both in the Medicaid population and also ABOUT THE AUTHORSAll of the authors are with amfAR, The Foundation for AIDS Research, Washington, DC.

Correspondence should be sent to Alana Sharp, 1100 Vermont Ave NW, Suite 600, Washington, DC 20005 (e-mail: alana.

[email protected]). Reprints can be ordered at http://www.ajph.org by clicking the“Reprints”link.

This article was accepted January 14, 2018.

doi: 10.2105/AJPH.2018.304338 642ResearchPeer ReviewedSharp et al.AJPHMay 2018, Vol 108, No. 5 AJPHPOLICY generally, several states have instituted poli- cies to reduce access to opioids, including setting limits on the number of opioid pills that can be prescribed or requiring prior authorization before prescribing. 13–17 However, despite the role of Medicaid as a major payer of substance use disorder treatment, 18the expansion’simpactonthe opioid epidemic has not been sufﬁciently quantiﬁed. Recently, at least 1 analysis has refuted the assertion that Medicaid expansion has contributed to rising opioid use and mor- tality, but no previous work has quantitatively described the impact of the ACA’schanges to Medicaid eligibility on both opioid drug use and treatment.

19Using both a difference-in- differences model and an interrupted time series model, this analysis describes prescribing pat- terns for opioids and the 3 FDA–approved medications for opioid use disorder treatment before and after Medicaid expansion, providing an important body of evidence on the role of Medicaid programs in the opioid epidemic. METHODS We used data on prescriptions reimbursed by Medicaid from Medicaid’s State Drug Utilization Data for years 2011 through 2016.

20We calculated the number of pre- scriptions reimbursed quarterly by the Med- icaid program by state for opioid analgesics, buprenorphine–naloxone (hereafter, bupre- norphine), methadone, and naltrexone (oral and injectable formulations) used for substance use treatment, by using the FDA’s National Drug Code Directory and the CDC’s dataﬁle of oral morphine milligram equivalent (MME) conversion factors. 21,22 Where the number of prescriptions of a medication was fewer than 11 per state per quarter, data were suppressed and therefore were unavailable. These sup- pressed values, on average of per-quarter, per-drug observations across all years, com- prised 46.2% of observations for opioids, 38.6% for buprenorphine, 49.3% for methadone, and 40.4% for naltrexone. At the maximum number requiring suppression, the overall count of prescriptions reimbursed was de- creased by only 0.020% because of suppression.

We measured quarterly rates of prescribing of each medication per annual count of Medicaid enrollees by using Centers for Medicare and Medicaid Services enrollment reports. 23,24 Wemeasured both the number of prescriptions and the number of units prescribed, for both opioids and MAT drugs. A“unit”is deﬁned by drug, typically representing a capsule, gram, milliliter, tablet, or transdermal patch. To assess trends in the strength of opioid drugs prescribed over time, we calculated the number of MMEs, a standardized measure of opioid dosage, by using CDC conversion factors. 22We excluded states in which Medicaid does not reimburse methadone (n = 17) or naltrexone (n = 1) for substance use disorders from those drug-speciﬁc analyses; all states reimburse buprenorphine. 25 We categorized all states and the District of Columbia as“expansion”states if they eventually expanded Medicaid (n = 32) and “nonexpansion”if they did not expand by the endof2016(n=19).Wetookthedateof Medicaid expansion for each state from the Kaiser Family Foundation’s database. 26In both expansion and nonexpansion states, we cen- tered dates at theﬁrst quarter of 2014, the date when Medicaid expansion went into effect for most states. For the states that expanded eligibility after January 1, 2014 (n = 7), we centered dates at the state-speciﬁcdateofex- pansion. We measured the impact of Medicaid expansion on opioid and medications for substance use disorders with 2 models: (1) a difference-in-differences model with state- levelﬁxed effects and (2) an interrupted time series method with state-levelﬁxed effects, with temporal interaction terms, on the period 2011 to 2016. We selected these models to both assess the overall effect size of the expansion onprescribingaswellastoprovideamore nuanced assessment of both the pre–post changes and the temporal changes in trends in this period.

These models are described as follows: ð1ÞRx it¼b 0þb 1Ptþb 2EiPtþg iþo´ it ð2ÞRx it¼b 0þb 1Ptþb 2tþb 3Eit þb 4ptþb 5EiPttþb 6EiPtt þg iþo´ it wherebcoefﬁcients measure the estimated effect size on prescribing for the following indicators:E iis an indicator for Medicaid expansion states (0 = states that did not ex- pand; 1 = states that did expand),P tis an indicator for the postexpansion time period (0 = preexpansion; 1 = postexpansion), and tis a continuous measure of time at 3-month quarterly intervals (from 2011 to 2016). Theg iis state-levelﬁxed effects and o´ itis an error term. The models are assessed whereRx it represents the number of prescriptions, the count of units prescribed, and the MMEs.

To measure the overall impact of the Medicaid expansion on prescribing rates in this period, we tested the following hypotheses: for the difference-in-differences model (Equation 1), we measured the impact by testing the signiﬁcance of theb 2coefﬁcient, while in the interrupted time series model (Equation 2), we assessed the impact of the expansion byb 5and b 6,whereb 5measures changes in prescribing rates at the transition from before expansion to after expansion, and whereb 6represents changes in the trend in prescribing in the postexpansion period. We measured the overall trends in prescribing rates by postestimation tests of linear combinations of coefﬁcients. For example, we tested the difference in trends after expansion in states that expanded Medicaid relative to those that did not by ð3ÞH 0:b 3þb 4þb 5þb 7 ðÞ b 3þb 5 ðÞ¼0;a¼0:05 We performed all analyses with Stata ver- sion 15 (StataCorp LP, College Station, TX). RESULTS A total of 181 485 806 opioid prescriptions, totaling 10 745 379 857 units (e.g., pills, tablets, sprays, milligrams) of opioids, were reimbursed by Medicaid from 2011 to 2016. In 2013, the year preceding the Medicaid expansion, Med- icaid expansion states had an average of 12 138 opioid prescriptions per 100 000 Medicaid enrollees (Table 1). In nonexpansion states, opioid prescribing rates were 10 861 per 100 000 enrollees in 2013. Similarly, both the number of units prescribed and the MMEs per 100 000 were higher in expansion states than in non- expansion states during the preexpansion period (Figure A, available as a supplement to the online version of this article at http://www.ajph.org). Postexpansion Opioid Prescription Differences On average, in all states, opioid prescribing rates increased from preexpansion to post- expansion periods (Figure 1, Table 1).

According to the difference-in-differences model, average prescription rates increased by AJPHPOLICY May 2018, Vol 108, No. 5AJPHSharp et al.Peer ReviewedResearch643 5985 per 100 000 in nonexpansion states and by 4366 per 100 000 in expansion states (Table 2). This difference in the differences in prescribing rates in expansion relative to nonexpansion states was not statistically sig- niﬁcant. We saw similar patterns in rates of opioid units prescribed and MME prescribing (Figure A, Table A, and Table B, available as supplements to the online version of this article at http://www.ajph.org).

In the interrupted time series model, the mean level of opioid prescriptions per 100 000 enrollees increased in all states between the preexpansion and postexpansion period, again with no signiﬁcant difference between ex- pansion and nonexpansion states (Table 3). In the period before the expansion, quarterly prescribing rates increased by an average of 62 prescriptions per 100 000 each quarter in expansion states and by 217 per quarter in nonexpansion states, although these trends were not signiﬁcant, nor were theysigniﬁcantly different from each other. After an increase in prescribing at the time of the ex- pansion, prescribing rates began to decline slightly in all states, with the rate of prescribing decreasing by 448 prescriptions per 100 000 every quarter in the nonexpansion states and by 230 per quarter in expansion states; again, this trend was not signiﬁcant in either group.

Overall, this model showed an increase in opioid prescribing in this time period, with the expansion of Medicaid eligibility not differ- entially impacting the overall growth in opioid prescribing rates nor the quarterly trends. We observed the same pattern for the number of units prescribed per 100 000 enrollees (Tables A and C, available as supplements to the online version of this article at http://www.ajph.org) and the MME prescribing rate (Table B). Medication-Assisted Treatment From 2011 to 2016, 11 166 525 pre- scriptions of buprenorphine, 3 267 551 ofmethadone, and 892 402 of naltrexone were reimbursed by Medicaid. The number of MAT prescriptions per 100 000 Medicaid enrollees was higher in 2013, the year before the expansion, for all 3 drugs in states that expanded Medicaid relative to those that did not expand (Table 1).

In the difference-in-differences model, buprenorphine prescribing increased across all states from the period before the expansion to the period after, with signiﬁcantly larger in- creases in expansion states (P<.001). In ex- pansion states, the rate of buprenorphine prescriptions increased by 1211 prescriptions per 100 000 from the preexpansion period to the postexpansion period, while in states that did not expand prescribing, they increased by 214 prescriptions per 100 000 (Table 2).

Overall, expansion states increased bupre- norphine prescribing rates by 997 units per 100 000 more than did nonexpansion states.

In the analysis of units prescribed, we TABLE 1—Prescribing Characteristics in the First Quarter (January–March) of 2013 and in the First Quarter of 2015, in States That Expanded and Did Not Expand Medicaid Eligibility: United States Characteristics Did Not Expand, Mean (SE) Expanded, Mean (SE) Difference (95% CI) Q1 2013 Prescriptions per 100 000 enrollees Opioids 10 861.0 (4 476.8) 12 138.1 (3 978.1)–1 277.1 (–3 703.1, 1 148.9) Buprenorphine 536.6 (1 142.0) 969.0 (1 527.2)–432.4 (–1 263.4, 398.7) Methadone 196.8 (143.8) 318.8 (224.2)–122.0 (–237.5,–6.5) Naltrexone 42.7 (35.1) 49.9 (48.6)–7.2 (–34.8, 20.4) Units reimbursed per 100 000 enrollees Opioids 607 987.0 (276 481.6) 773 705.1 (448 303.3)–165 718.1 (–395 028.5, 63 592.2) Buprenorphine 18 100.6 (31 750.1) 26 943.1 (28 774.5)–8 842.5 (–26 532.7, 8 847.5) Methadone 25 816.5 (19 378.9) 45 315.3 (33 034.3)–19 498.8 (–36 245.0, 2 747.7) Naltrexone 1 296.2 (974.8) 1 427.5 (1 248.4)–131.3 (–853.3, 590.5) MMEs per 100 000 enrollees: opioids 647 158.7 (370 754.1) 907 012.1 (535 205.4)–259 853.4 (–540 019.0, 20 312.2) Q1 2015 Prescriptions per 100 000 enrollees Opioids 22 719.9 (40 602.0) 20 001.5 (24 714.9) 2 718.4 (–15 613.1, 21 049.9) Buprenorphine 621.9 (1 064.6) 1 756.0 (2 579.9)–1 134.1 (–2 418.5, 150.1) Methadone 315.4 (568.9) 300.0 (291.9) 15.4 (–229.4, 260.2) Naltrexone 101.3 (205.8) 104.2 (136.6)–2.9 (–102.5, 96.8) Units reimbursed per 100 000 enrollees Opioids 1 331 492.5 (227 620.4) 1 168 961.8 (1 450 756.1) 162 530.7 (–888 073.4, 1 213 135.4) Buprenorphine 19 660.8 (24 042.5) 56 499.6 (93 709.3)–36 838.8 (–82 248.6, 8571.1) Methadone 38 489.9 (61 004.0) 38 421.2 (39 997.9) 68.7 (–28 603.0, 28 740.5) Naltrexone 3 437.2 (8 258.4) 2 547.3 (3 225.2) 889.9 (–2 465.3, 4 245.2) MMEs per 100 000 enrollees: opioids 1 380 219.6 (2 184 246.7) 1 472 694.4 (2 040 427.4)–92 474.8 (–1 311 461.3, 1 126 511.0) Note.CI = conﬁdence interval; MME = morphine milligram equivalents. Prescribing rates are per 100 000 Medicaid enrollees.

AJPHPOLICY 644ResearchPeer ReviewedSharp et al.AJPHMay 2018, Vol 108, No. 5 observed no signiﬁcant change in the level of units of buprenorphine prescribed per 100 000 in nonexpansion states, while the number of units prescribed increased signif- icantly for expansion states (Table A).

In the interrupted time series analysis of MAT, before the expansion, the quarterly rate of buprenorphine prescribing was in- creasing in both expansion (72.3 units per 100 000 per quarter) and nonexpansion states (43.5 units per 100 000 per quarter). Thisdifference was not statistically signiﬁcant (Table 3). After the expansion, the rate of buprenor- phine prescribing leveled off slightly in the nonexpansion states, while the prescribing rate increased by 136.3 units per 100 000 every quarter in the expansion states, a statistically signiﬁcant rate increase (P<.001). We ob- served a similar trend in the number of units prescribed per 100 000 enrollees (Table C).

By contrast, methadone prescribing exhibited an overall declining trend in the2011–2016 period. In the difference-in- differences model, the number of methadone prescriptions per 100 000 did not signiﬁcantly change in nonexpansion states but decreased by 65 per 100 000 in expansion states (P= .001; Table 2). The number of units of methadone prescribed decreased in both expansion and nonexpansion states, with a larger decrease in expansion than in nonexpansion states (–6551 per 100 000 in nonexpansion,–13 313 per 100 000 in expansion states;P<.001; Table A). 0 500 1 000 1 500 MAT Reimbursed per Enrollee 0 3 000 6 000 9 000 12 000 15 000 Opioid Reimbursed per Enrollee –10 –5 0 5 10 Quarters Before and After Expansion 0 500 1 000 1 500 MAT Reimbursed per Enrollee 0 3 000 6 000 9 000 12 000 15 000 Opioid Reimbursed per Enrollee –10 –5 0 5 10 Quarters Before and After Expansion Opioids Buprenorphine Naltrexone Methadone a b Note. MAT = medication-assisted treatment.

FIGURE 1—Number of Prescriptions per 100 000 Medicaid Enrollees From 2011 to 2016 in States That (a) Expanded and (b) Did Not Expand Medicaid: United States AJPHPOLICY May 2018, Vol 108, No. 5AJPHSharp et al.Peer ReviewedResearch645 Temporal trends in the quarterly number of per-enrollee methadone prescriptions revealed a signiﬁcant downward trend in the preexpansion period in both expansion (–9.50 units per 100 000 per quarter) and nonexpansion (–9.51 units per 100 000 per quarter) states (Table 3), as well as in units prescribed (Table C). The trends were not signiﬁcantly different in this period. In the postexpansion period, we observed a similar downward trend, with the rate of change again not signiﬁcantly different between the 2 groups.

Finally, the rate of naltrexone prescribing increased by 75 prescriptions per 100 000 in expansion states and by 36 prescriptions per 100 000 in nonexpansion states in the difference-in-differences model, with the increased prescribing signiﬁcantly higher in expansion states (P<.001; Table 2). The number of units of naltrexone prescribed per 100 000 similarly increased in this period, although we observed no difference in ex- pansion relative to nonexpansion states (Table Ag).

In the interrupted time series model, the trend in the rate of naltrexone prescriptions per 100 000 enrollees wasﬂat in all groups and periods, with the exception of a signiﬁcant increasing trend in prescribing rates (10.5prescriptions per 100 000 per quarter) in expansion states after the expansion (Table 3).

The trend in the rate of units prescribed similarly increased by 141.91 units per 100 000 every quarter in expansion states after the expansion (Table C) but did not change in any other period or group. DISCUSSION States that did and did not expand Med- icaid had similar growth in opioid prescribing rate per Medicaid enrollee after expansion, while per-enrollee rates of Medicaid- reimbursed MAT increased signiﬁcantly more in expansion states. The results from both models showed an overall increase in the rate of per-enrollee opioid prescribing in the period after January 2014, or after the date of Medicaid expansion for states that expanded later, through the end of 2016 in all states. This increase in opioid prescribing per state number of enrollees was not statistically different in states that ex- panded Medicaid to low-income adults under the ACA relative to those that did not expand.

Although there was an overall increase in the quarterly trend of opioid prescribing in the preexpansion period, the trends in opioidprescribing rates were not different in ex- pansion and nonexpansion states.

As with opioid prescribing, the per- enrollee rates of prescribing for all 3 MAT drugs was higher at the preexpansion baseline in states that ultimately expanded Medicaid relative to those that did not. For bupre- norphine, the quarterly growth in prescribing was signiﬁcantly higher in expansion states after the expansion, while the trend in nonexpansion states did not change. For methadone, we found overall declining rates of prescribing, with larger decreases in ex- pansion states across this period. Naltrexone prescribing was higher in expansion states in the pre- and postexpansion period, and both the growth in prescribing after the expansion as well as the change in the rate of prescribing were signiﬁcantly greater in states that ex- panded than in those that did not.

Theseﬁndings suggest that the population of low-income adults newly eligible for Medicaid as part of the ACA’s expansion were no more likely to be prescribed opioid medications than the base preexpansion population, while being more likely to access treatment of substance use disorders. States that expanded Medicaid had historically higher rates of per-enrollee opioid prescribing in the Medicaid population, although this did TABLE 3—Regression Table for Interrupted Time Series Model With State-Level Fixed Effects for Number of Prescriptions: United States, 2011–2016 Opioids, b (95% CI) Buprenorphine, b (95% CI) Methadone, b (95% CI) Naltrexone, b (95% CI) Post (1 = postexpansion; 0 = preexpansion) 7 376.54 (2 769.77, 11 983.3)–105.74 (–484.92, 273.43) 131.42 (26.78, 236.06) 25.49 (–3.01, 54.00) Post·expanded–2 090.27 (–7 884.19, 3 703.65)–107.95 (–366.44, 582.34)–78.90 (–206.34, 48.53)–18.75 (–54.21, 16.70) Time (quarters) 216.55 (–193.69, 626.79) 43.47 (8.98, 77.95)–9.51 (–18.83,–0.19) 0.59 (–1.93, 3.12) Time·post–664.25 (–1 331.90, 3.40)–32.54 (–87.52, 22.43)–4.28 (–19.46, 10.90) 0.63 (–3.48, 4.75) Time·expanded–154.61 (–643.18, 333.96) 28.84 (–12.45, 70.13)–0.02 (–11.05, 11.08) 0.74 (–2.24, 3.73) Time·expanded·post 372.33 (–463.47, 1 208.13) 96.49 (27.74, 165.24) 3.66 (–14.79, 22.11) 8.56 (3.47, 13.64) (Constant) 12 967.47 (11 268.62, 14 666.32) 1 135.77 (995.69, 1 275.85) 277.47 (240.71, 314.24) 55.62 (45.23, 66.02) Note.CI = conﬁdence interval. All prescribing rates are number of prescriptions reimbursed by Medicaid per 100 000 Medicaid enrollees.

TABLE 2—Regression Table for Difference-in-Differences Model With State-Level Fixed Effects for Number of Prescriptions: United States, 2011–2016 Opioids, b (95% CI) Buprenorphine, b (95% CI) Methadone, b (95% CI) Naltrexone, b (95% CI) Post (1 = postexpansion; 0 = preexpansion) 5 985.31 (3 700.49, 8 270.13) 214.07 (15.79, 412.35)–8.37 (–60.54, 43.80) 36.44 (21.98, 50.90) Post·expanded–1 619.79 (–4 541.75, 1 302.16) 996.67 (744.71, 1 248.64)–56.30 (–120.32, 7.73) 38.99 (20.69, 57.28) (Constant) 12 226.25 (11 291.60, 13 160.91) 760.71 (679.29, 842.14) 335.69 (315.56, 355.82) 48.87 (43.06, 54.67) Note.CI = conﬁdence interval. All prescribing rates are number of prescriptions reimbursed by Medicaid per 100 000 Medicaid enrollees.

AJPHPOLICY 646ResearchPeer ReviewedSharp et al.AJPHMay 2018, Vol 108, No. 5 not appear to be driven by the population of newly eligible enrollees. Rather, the expan- sion of Medicaid eligibility appears to have primarily served as an important source of access to MAT of low-income adults with substance use disorders.

Theﬁnding that the rate of MME pre- scribing increased in this time period contrasts with a recent analysis of per-capita MME prescribing in the total population, which found that national opioid prescribing rates have declined from 2010 to 2015. 27Our ﬁndings are corroborated by this analysis, which found that opioid prescribing rates were highest in communities with large populations without health insurance or en- rolled in Medicaid. It is outside of the scope of this analysis to determine why prescribing has increased among Medicaid enrollees yet de- clined nationally; as the indication for each prescription is not publicly available, neither the appropriateness of each prescription nor the condition each was intended to treat can be evaluated. It is nonetheless apparent that high prescribing in the Medicaid population predates the ACA, and we observed no dif- ferential effect on prescribing in states that expanded Medicaid relative to those that did not. Theseﬁndings are corroborated by other analyses that have found that the Medicaid expansion had no differential impact on drug-related mortality. 19 Trends in the number of opioid pre- scriptions, the units of opioids prescribed, and the number of MMEs prescribed were similar.

As such, we observed no distinct trends in the number of units per prescription or the rel- ative potency of prescriptions over time, suggesting that changes in the number of prescriptions were neither offset nor com- pounded by changes in the number of units prescribed or the comparative potency of the drugs prescribed. However, the number of MMEs per capita observed in these data was considerably higher than that described in the total population; thisﬁnding may be attrib- utable to the comparatively high proportion of Medicaid enrollees who have disabilities requiring long-term pain management or who are aged 65 years or older. 27,28 In addition, we found a general trend toward the use of buprenorphine in MAT and a shift away from methadone. Although naltrexone occupies a smaller proportion of the MAT prescribing in this population, itsuse increased in this period. This trend, whether driven by provider or patient, may be driven by the lower risk for addiction or overdose in buprenorphine and naltrexone relative to methadone. In addition, metha- done is typically administered via daily in-person clinic visits, whereas buprenor- phine and naltrexone can be administered by larger“take-home”doses or through long- term injectable formulations. The burden of patient visits, which may incurﬁnancial costs, opportunity costs, and increased stigma, may also contribute toward the shift away from methadone.

This analysis was limited by several factors.

First, the suppression of drugs or quarters with low prescribing rates limited our ability to fully describe all trends in prescribing, al- though this analysis nonetheless describes trends of the most commonly prescribed drugs in the Medicaid program. Second, the use of state-level data may mask microtrends within states or mask differential impacts by urbanicity, distribution of substance use treatment programs or services, or health facility practices. In future research, more granular assessments that measure subnational enrollment and prescribing patterns will fa- cilitate a more complete assessment of the impact of the Medicaid expansion.

Third, the prescribing data did not include the indication nor the patient diagnosis, which may confound theﬁndings. Indeed, methadone is used not just for treating opioid dependence, but is also used as an analgesic, and naltrexone is also approved for the treatment of alcohol addiction. Fourth, we identiﬁed 5 states where the proportion of data from managed care organizations was lower than would be predicted by the pro- portion of Medicaid enrollees in managed care organizations. The mainﬁndings are unchanged by excluding these states, except that in the difference-in-differences model opioid prescribing rates did expand signiﬁ- cantly in expansion states, while remaining nonsigniﬁcant for units, MMEs, and in the interrupted time series model. Finally, we were not able to measure trends in the number of days associated with each pre- scription, an important metric that can signify patterns of overprescribing. Nonetheless, the use of 3 distinct metrics of prescribing (number of prescriptions, number of units prescribed, and MMEs) providea multifaceted assessment that triangulates state-level trends in prescribing patterns.

This analysis of Medicaid prescribing data suggests that the expansion of insurance cov- erage in expansion states provided health in- surance coverage to a population no more likely to be prescribed opioids than the pre- expansion population, while signiﬁcantly in- creasing access to treatment for people with substance use disorders. Continuing to address the opioid epidemic should maintain a focus on increasing access to health care and increasing health system capacity to provide substance abuse treatment of all those in need. CONTRIBUTORSA. Sharp, B. Honermann, and G. Millett originated the research question. A. Sharp, A. Jones, J. Sherwood, and O. Kutsa contributed to data analysis and statistical design.

A. Sharp wrote the article. All authors contributed to discussions and analysis of results and review of the article.

HUMAN PARTICIPANT PROTECTIONThis analysis did not involve human participants or per- sonally identiﬁable information. Institutional review board approval was not required.

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13. Baker-White A. A look at state legislation limiting opioid prescriptions. Arlington, VA: Association of Stateand Territorial Health Of ﬁcials; 2017. 14. Dube N. Connecticut ’s opioid drug abuse law. Hartford, CT: Connecticut Of ﬁce of Legislative Research; 2016. 15. Vestal C. Maryland moves to limit opioid painkillers. The Pew Charitable Trusts. 2017. Available at: http://www.pewtrusts.org/en/research-and-analysis/blogs/stateline/2017/01/25/maryland-moves-to-limit-opioid-painkillers. Accessed December 1, 2017.

16. Opioid prior authorization requirements. Medstar Family Choice. 2017. Available at: http://www.medstarfamilychoice.com/maryland-healthchoice/for-maryland-healthchoice-physicians/pharmacy/opioid/ #q={}. Accessed December 1, 2017.

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20. State drug utilization data. Centers for Medicare and Medicaid Services. Available at: https://www.medicaid.gov/medicaid/prescription-drugs/state-drug-utilization- data/index.html. Accessed August 8, 2017.

21. National Drug Code Directory . US Food and Drug Administration. 2017. Available at: https://www.fda. gov/Drugs/InformationOnDrugs/ucm142438.htm. Accessed August 8, 2017.

22. Analyzing prescription data and morphine milligram equivalents. Centers for Disease Control and Prevention. 2017. Available at: https://www.cdc.gov/drugoverdose/media/index.html. Accessed August 8, 2017.

23. Medicaid Enrollment Report Centers for Medicare & Medicaid Services. Centers for Medicare & MedicaidServices. 2015. Available at: https://www.medicaid.gov/medicaid/managed-care/enrollment/index.html.Accessed August 8, 2017.

24. Medicaid enrollment data collected through MBES. Centers for Medicare and Medicaid Services. 2016.Available at: https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment- data/enrollment-mbes/index.html. Accessed August 8, 2017.

25. Advancing access to addiction medications: implica- tions for opioid addiction treatment. American Society of Addiction Medicine. 2013. Available at: https://www. asam.org/docs/default-source/advocacy/aaam_implications-for-opioid-addiction-treatment_ ﬁnal. Accessed August 8, 2017.

26. Status of state action on the Medicaid expansion decision. The Kaiser Family Foundation. 2017. Available at: http://www.kff.org/health-reform/state-indicator/ state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:% 22asc%22%7D. Accessed August 8, 2017.

27. Guy GP Jr, Zhang K, Bohm M, et al. Vital signs: changes in opioid prescribing in the United States, 2006 – 2015. MMWR Morb Mortal Wkly Rep. 2017;66(26): 697 –704. 28. Medicaid enrollees by enrollment group. The Kaiser Family Foundation. 2014. Available at: http://www. kff.org/medicaid/state-indicator/distribution-of- medicaid-enrollees-by-enrollment-group/?dataView=1&currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22s ort%22:%22asc%22%7D. Accessed August 8, 2017. AJPH POLICY 648 Research Peer Reviewed Sharp et al. AJPH May 2018, Vol 108, No. 5 Copyright ofAmerican JournalofPublic Health isthe property ofAmerican PublicHealth Association anditscontent maynotbecopied oremailed tomultiple sitesorposted toa listserv without thecopyright holder'sexpresswrittenpermission. However,usersmayprint, download, oremail articles forindividual use.