Medicaid Expansion and Prescription Trends: Opioids, Addiction Therapies, and Other Drugs.
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ABSTRACT: Background
Opioid overdose deaths in the United States have climbed since 1999. In 2014, the Affordable Care Act prompted some states to expand Medicaid programs, providing low-cost prescription access to millions of Americans. Some have questioned whether Medicaid expansion might worsen the opioid crisis.Objective
To test the association between the expansion of state Medicaid programs and Medicaid-paid prescriptions of opioid pain relievers and opioid addiction therapies.Research design
We analyzed the 2010-2016 Medicaid State Drug Utilization Data using a difference-in-differences regression approach, comparing prescriptions per enrollee between states that expanded Medicaid in 2014 and states that did not. We compared opioid pain relievers and opioid addiction therapies to 5 other commonly prescribed drug types important to the Medicaid expansion population (antidepressants, antihypertensives, diabetes medications, cholesterol treatments, and contraceptives) and to overall prescription volume. A secondary analysis compared opioid pain relievers and opioid addiction therapies, between states with high and low overdose death rates.Results
We found overall prescription use per enrollee was higher after 2014. Relative growth in opioid pain reliever prescriptions was modest compared with growth in medications for depression, hypertension, diabetes, and high cholesterol. Growth in prescriptions used to treat opioid use disorder greatly outpaced other drugs, suggesting important gains in access to addiction treatments; growth was higher in states with higher pre-2014 overdose death rates.Conclusions
Our results suggest Medicaid expansion benefited a population with unique needs, and that Medicaid expansion could be a valuable tool in addressing the opioid overdose epidemic.
SUBMITTER: Cher BAY
PROVIDER: S-EPMC6375792 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Opioid abuse and overdose constitute an ongoing health emergency. Many presume opioids have little potential for iatrogenic addiction when used as directed, particularly in short courses, as is typical of the emergency department (ED) setting. We preliminarily explore the possibility that initial exposure to opioids by EDs could be related to subsequent opioid misuse.This cross-sectional study surveyed a convenience sample of patients reporting heroin or nonmedical opioid use at an urban, academic ED. We estimated the proportion whose initial exposure to opioids was a legitimate medical prescription and the proportion of those prescriptions that came from an ED. Secondary measurements included the proportion of patients receiving nonopioid substances before initial opioid exposure, the source of opioids between initial exposure and onset of regular nonmedical use, and time from initial prescription to opioid use disorder.Of 59 subjects, 35 (59%; 95% confidence interval [CI] 47% to 71%) reported they were first exposed to opioids by a legitimate medical prescription, and for 10 of 35 (29%; 95% CI 16% to 45%), the prescription came from an ED. Most medically exposed subjects (28/35; 80%; 95% CI 65% to 91%) reported nonopioid substance use or treatment for nonopioid substance use disorders preceding the initial opioid exposure. Emergency providers were a source of opioids between exposure and onset of regular nonmedical use in 11 of 35 cases (31%; 95% CI 18% to 48%). Thirty-one of the 35 medically exposed subjects reported the time of onset of nonmedical use; median time from exposure to onset of nonmedical use was 6 months for use to get high (N=25; interquartile range [IQR] 2 to 36), 12 months for regular use to get high (N=24; IQR 2 to 36), 18 months for use to avoid withdrawal (N=26; IQR 2 to 38), and 24 months for regular use to avoid withdrawal (N=27; IQR 2 to 48). Eleven subjects (36%; 95% CI 21% to 53%) began nonmedical use within 2 months, and 9 of 11 (82%; 95% CI 53% to 96%) reported nonopioid substance use or treatment for alcohol abuse before initial opioid exposure.Although short-term opioid administration by emergency providers is unlikely to cause addiction by itself, ED opioid prescriptions may contribute to the development of addiction in some patients. There is an urgent need for further research to estimate long-term risks of short-course opioid therapy so that the risk of iatrogenic addiction can be appropriately balanced with the benefit of analgesia.
| S-EPMC4958587 | biostudies-literature
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| S-EPMC6417939 | biostudies-literature
Project description:ObjectiveTo test whether Medicaid expansion is associated with (a) a greater number of naloxone prescriptions dispensed and (b) a higher proportion of naloxone prescriptions paid by Medicaid.Data sources/study settingWe used the IQVIA National Prescription Audit to obtain data on per state per quarter naloxone prescription dispensing for the period 2011-16.Study designIn this quasi-experimental design study, the impact of Medicaid expansion on naloxone prescription dispensing was examined using difference-in-difference estimation models. State-level covariates including pharmacy-based naloxone laws (standing/protocol orders and direct authority to dispense naloxone), third-party prescribing laws, opioid analgesic prescribing rates, opioid-involved overdose death rates, and population size were controlled for in the analysis.Principal findingsMedicaid expansion was associated with 38 additional naloxone prescriptions dispensed per state per quarter compared to nonexpansion controls, on average (P = .030). Also, Medicaid expansion resulted in an average increase of 9.86 percent in the share of naloxone prescriptions paid by Medicaid per state per quarter (P < .001).ConclusionsOur study found that Medicaid expansion increased naloxone availability. This finding suggests that it will be important to consider naloxone access when making federal- and state-level decisions affecting Medicaid coverage.
| S-EPMC7080392 | biostudies-literature
Project description:Prescription drug monitoring programs are promising tools to use in addressing the prescription opioid epidemic, yet prescribers' participation in these state-run programs remained low as of 2014. Statutory mandates for prescribers to register with their state's program, use it, or both are believed to be effective tools to realize the programs' full potential. Our analysis of aggregate Medicaid drug utilization data indicates that state mandates for prescriber registration or use adopted in 2011-14 were associated with a reduction of 9-10 percent in population-adjusted numbers of Schedule II opioid prescriptions received by Medicaid enrollees and amounts of Medicaid spending on these prescriptions. This effect was largely associated with mandates of registration, which were comprehensive in all adopting states, and not with mandates of use, which were largely limited in scope or strength before 2015. Our findings support the use of mandates of registration in prescription drug monitoring programs as an effective and relatively low-cost policy. Future research should further assess the value of strong mandates of use to ensure safer and more appropriate prescribing of opioids.
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Project description:Evaluate the effect of short-term use of precribed opioids on DNA methylation
2020-05-30 | GSE151485 | GEO
Project description:Purpose"Lock-in" programs (LIPs) are used by health insurers to address potential substance (eg, opioid) misuse among beneficiaries. We sought to (1) examine heterogeneity in trajectories of dispensed opioids (in average daily morphine milligram equivalents (MMEs)) over time: prior to, during, and following release from a LIP, and (2) assess associations between trajectory patterns and beneficiary characteristics.MethodsMedicaid claims were linked to Prescription Drug Monitoring Program records for a cohort of beneficiaries enrolled in the North Carolina Medicaid LIP (n = 2701). Using latent class growth analyses, we estimated trajectories of average daily MMEs of opioids dispensed to beneficiaries across specific time periods of interest.ResultsFive trajectory patterns appeared to sufficiently describe underlying heterogeneity. Starting values and slopes varied across the 5 trajectory groups, which followed these overall patterns: (1) start at a high level of MMEs, end at a high level of MMEs (13.1% of cohort); (2) start medium, end medium (13.2%); (3) start medium, end low (21.5%); (4) start low, end medium (22.6%); and (5) start low, end low (29.6%). We observed strong associations between patterns and beneficiaries' demographics, substance use-related characteristics, comorbid conditions, and healthcare utilization.ConclusionsIn its current form, the Medicaid LIP appeared to have limited impact on beneficiaries' opioid trajectories. However, strong associations between trajectory patterns and beneficiary characteristics provide insight into potential LIP design modifications that might improve program impact (eg, LIP integration of substance use disorder assessment and referral to treatment, assessment and support for alternate pain therapies).
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Project description:BACKGROUND:Pain is more common among people living with HIV (PLWH) than their counterparts; however, it is unclear whether analgesic use differs by HIV status. METHODS:We analyzed Medicaid pharmacy claims from adults in 14 US states from 2001 to 2009 to identify opioid and non-opioid analgesic prescriptions and compared prescribing trends by HIV status. We accounted for clinical and demographic differences by using inverse probability weights and by restricting the sample to a subgroup with a common comorbidity, diabetes, chosen for its high prevalence and association with lifestyle and chronic pain. We estimated the incidence of chronic opioid therapy (COT) (≥90 consecutive days with an opioid prescription) among opioid-naïve individuals. RESULTS:Rates of opioid and non-opioid use increased approximately two-fold from 2001 to 2009. PLWH received approximately twice as many prescriptions as those without HIV. In an unadjusted Cox regression, PLWH were three times more likely to receive COT compared to those without HIV (hazard ratio (HR) = 3.06, 95% CI 2.76-3.39). When restricting to patients with diabetes and adjusting for age, sex, state, comorbidity score, depression, bipolar disorder, and schizophrenia, the HR decreased to 1.26 (95% CI 0.97-1.63). CONCLUSIONS:Higher opioid use among PLWH was largely a function of patients' demographic characteristics and health status. The high incidence of COT among PLWH underscores the importance of practice guidelines that minimize adverse events associated with opioid use.
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Project description:ImportanceIt is not yet known how many children and adolescents die each year from opioid poisonings and how mortality rates have changed over time.ObjectiveTo examine national trends in pediatric deaths from prescription and illicit opioids.Design, setting, and participantsCross-sectional in which serial mortality data from the Centers for Disease Control and Prevention were analyzed. The population included 8986 children and adolescents (age, <20 years) who died in all US settings from opioid poisonings between 1999 and 2016. Data were collected and analyzed between June 1 and October 31, 2018.ExposuresAll opioids.Main outcomes and measuresAge-specific mortality rates per 100?000 were estimated with smoothing spline Poisson regression.ResultsOf the 8986 children and adolescents who died between 1999 and 2016 from prescription and illicit opioid poisonings, 6567 (73.1%) were male, 7921 (88.1%) were among adolescents aged 15 to 19 years, and 605 (6.7%) were among children aged 0 to 4 years. The overall pediatric mortality rate increased from 0.22 (95% CI, 0.19-0.25) to 0.81 (95% CI, 0.76-0.88) per 100?000, an increase of 268.2% (P for time effect <.001). The highest annual rates were among adolescents aged 15 to 19 years, but time trends revealed a steady linear increase among children aged 0 to 4 years and those aged 5 to 9 years as well as a steady linear increase until 2008 among the cohorts aged 10 to 14 years and 15 to 19 years, when rates briefly declined before rising again. Among adolescents aged 15 to 19 years, heroin was implicated in 1872 deaths: rates increased from 0.21 (95% CI, 0.17-0.25) to 1.06 (95% CI, 0.97-1.17), an increase of 404.8%, whereas rates for prescription opioids increased by 94.7% from 0.57 (95% CI, 0.49-0.66) to 1.11 (95% CI, 0.99-1.25) (all P for time effect <.001). Between 2014 and 2016, there were 1508 opioid deaths among adolescents aged 15 to 19 years; of these, 468 (31.0%) were attributed to synthetic opioids. Across time, 7263 (80.8%) of all pediatric deaths were unintentional, 5537 (61.6%) occurred outside of a medical facility, and 3419 (38.0%) children died at home or another residential setting. Among children younger than 5 years, 148 (24.5%) deaths were attributed to homicide.Conclusions and relevanceOver 18 years, nearly 9000 children and adolescents died from opioid poisonings, and the mortality rate increased nearly 3-fold. These findings suggest that the opioid epidemic is likely to remain a growing public health problem in the young unless legislators, public health officials, clinicians, and parents take a wider view of the opioid crisis and implement protective measures that are pediatric specific and family centered.
| S-EPMC6324338 | biostudies-literature
Project description:Importance:Although prescription opioid use disorder is associated with substantial harms, strategies to identify patients with pain among whom prescription opioids can be safely prescribed have not been systematically reviewed. Objective:To review the evidence examining factors associated with opioid addiction and screening tools for identifying adult patients at high vs low risk of developing symptoms of prescription opioid addiction when initiating prescription opioids for pain. Data Sources:MEDLINE and Embase (January 1946 to November 2018) were searched for articles investigating risks of prescription opioid addiction. Study Selection:Original studies that were included compared symptoms, signs, risk factors, and screening tools among patients who developed prescription opioid addiction and those who did not. Data Extraction and Synthesis:Two investigators independently assessed quality to exclude biased or unreliable study designs and extracted data from higher quality studies. The Preferred Reporting Items for Systematic Reviews and Meta-analyses of Diagnostic Accuracy Studies (PRISMA-DTA) reporting guideline was followed. Main Outcomes and Measures:Likelihood ratios (LRs) for risk factors and screening tools were calculated. Results:Of 1287 identified studies, 6 high-quality studies were included in the qualitative synthesis and 4 were included in the quantitative synthesis. The 4 high-quality studies included in the quantitative synthesis were all retrospective studies including a total of 2 888 346 patients with 4470 cases that met the authors' definitions of prescription opioid addiction. A history of opioid use disorder (LR range, 17-22) or other substance use disorder (LR range, 4.2-17), certain mental health diagnoses (eg, personality disorder: LR, 27; 95% CI, 18-41), and concomitant prescription of certain psychiatric medications (eg, atypical antipsychotics: LR, 17; 95% CI, 15-18) appeared useful for identifying patients at high risk of opioid addiction. Among individual findings, only the absence of a mood disorder (negative LR, 0.50; 95% CI, 0.45-0.52) was associated with a lower risk of opioid addiction. Despite their widespread use, most screening tools involving combinations of questions were based on low-quality studies or, when diagnostic performance was assessed among high-quality studies, demonstrated poor performance in helping to identify patients at high vs low risk. Conclusions and Relevance:While a history of substance use disorder, certain mental health diagnoses, and concomitant prescription of certain psychiatric medications appeared useful for identifying patients at higher risk, few quality studies were available and no symptoms, signs, or screening tools were particularly useful for identifying those at lower risk.
| S-EPMC6503484 | biostudies-other