Project description:ObjectiveThe US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain management clinics. We aimed to provide practical design recommendations to improve PDMP workflow integration, as well as controlled substance history retrieval, interpretation, and decision support.MethodsWe conducted 16 in-depth semi-structured interviews with practicing emergency and pain physicians regarding their procedures, problems, and proposed solutions surrounding their use of CURES, California's PDMP. We investigated design problems in CURES by combining users' feedback with our usability inspection, drawing upon an extensive body of design literature. Then, we generated alternatives using design methods.ResultsWe found CURES's design did not accommodate the unique information needs of different medical domains. Further, clinicians had trouble accessing CURES and retrieving patients' controlled substance histories, mainly due to usability problems that could be addressed with little technical adjustment. Additionally, CURES rendered patient histories in large, cluttered tables, devoid of overview or context, making interpretation difficult and precarious. Lastly, our interviewees had rarely noticed or used advanced features, such as decision support.Discussion and conclusionUsability barriers inhibited adoption and effective use. We provide practical recommendations for improving opioid control by way of improving PDMP design, based on interviewees' suggestions and research-based design principles. Our findings have implications for other disciplines, including surgery and primary care.

Project description:ImportanceAlthough manufacturer-sponsored coupons are commonly used, little is known about how patients use them within a treatment episode.ObjectivesTo examine when and how frequently patients use manufacturer coupons during a treatment episode for a chronic condition, and to characterize factors associated with more frequent use.Design, setting, and participantsThis is a retrospective cohort study of a 5% nationally representative sample of anonymized longitudinal retail pharmacy claims data from October 1, 2017, to September 30, 2019, obtained from IQVIA's Formulary Impact Analyzer. The data were analyzed from September to December 2022. Patients with new treatment episodes using at least 1 manufacturer coupon over a 12-month period were identified. This study focused on patients with 3 or more fills for a given drug and characterized the association of the outcomes of interest with patient, drug, and drug class characteristics.Main outcomes and measuresThe primary outcomes were (1) the frequency of coupon use, measured as the proportion of prescription fills accompanied by manufacturer coupon within the treatment episode, and (2) the timing of first coupon use relative to the first prescription fill within the treatment episode.ResultsA total of 36 951 treatment episodes accounted for 238 474 drug claims and 35 352 unique patients (mean [SD] age, 48.1 [18.2] years; 17 676 women [50.0%]). Among these episodes, nearly all instances (35 103 episodes [95.0%]) of first coupon use occurred within the first 4 prescription fills. Approximately two-thirds of treatment episodes (24 351 episodes [65.9%]) used a coupon for the incident fill. Coupons were used for a median (IQR) of 3 (2-6) fills. The median (IQR) proportion of fills with a coupon was 70.0% (33.3%-100.0%), and many patients discontinued the drug after the last coupon. After adjustment for covariates, there was no significant association between an individual's out-of-pocket costs or neighborhood-level income and the frequency of coupon use. The estimated proportion of fills with a coupon was greater for products in competitive (19.5% increase; 95% CI, 2.1%-36.9%) or oligopolistic (14.5% increase; 95% CI, 3.5%-25.6%) markets than monopoly markets when there is only 1 drug in the therapeutic class.Conclusions and relevanceIn this retrospective cohort analysis of individuals receiving pharmaceutical treatment for chronic diseases, the frequency of manufacturer-sponsored drug coupon use was associated with the degree of market competition, rather than patients' out-of-pocket costs.

Project description:ImportanceDrug companies offer coupons to lower the out-of-pocket costs for prescription drugs, yet little is known about why they do so for some drugs but not for others.ObjectiveTo examine whether the following factors are associated with manufacturer drug coupon use: (1) patient-cost characteristics (mean per-patient cost per drug, mean patient copay); (2) drug characteristics (generics availability or "later-in-class-entrant" drugs); (3) drug-class characteristics (in-class coupon use among competitors; in-class generic competition; in-class mean cost and copay).Design setting and participantsThis was a retrospective cohort analysis of anonymized transactional pharmacy claims sourced from retail US pharmacies from October 2017 to September 2019, supplemented with information derived from Medi-Span, Red Book, and FDA.gov. Data were analyzed from September 2020 to February 2021.Main outcomes and measuresThe primary outcome was availability of a manufacturer's coupon. The secondary outcome was the mean proportion of transactions in which a coupon was used for each product.ResultsThe sample of 2501 unique brand-name prescription drugs accounted for a total of 8 995 141 claims. Manufacturers offered a coupon for 1267 (50.7%) of these drugs. When the manufacturer offered a coupon, it was used in a mean (SD) 16.3% (20.3%) of the transactions. Within a drug class, higher mean total cost per patient was positively associated with the likelihood of coupon use (odds ratio [OR], 1.03 per 10% increase; 95% CI, 1.01-1.04), but higher mean patient copay was inversely associated (OR, 0.98; 95% CI, 0.97-0.99). For drug characteristics, single-source later-in-class-entrant products were associated with a greater likelihood of coupon use compared with first entrants and multisource brands (OR, 1.44; 95% CI, 1.09-1.89). The intensity of coupon use was associated with later-in-class-entrant products and the class mean per-patient cost (4.16-percentage-point increase; 95% CI, 1.20-7.13; 0.27 per 10% increase; 95% CI, 0.09-0.44). Drugs with a new in-class brand-name competitor had greater mean coupon use compared with drugs without a new competitor (10.2% of claims with a coupon vs 5.9%).Conclusions and relevanceIn this cohort study of transactional pharmacy claims, higher mean per-patient total cost within a class was significantly associated with the likelihood of coupon use, but not patient out-of-pocket cost. Manufacturers' coupons were more likely to be used for expensive later-in-class-entrant products facing within-class competition where coupon use was prevalent.

Project description:ImportanceMedicaid enrolls a disproportionate share of US adults with hepatitis C virus (HCV), and most receive Medicaid benefits through managed care organizations (MCOs). Medicaid MCOs often impose stricter requirements to access HCV medications than traditional fee-for-service Medicaid, which may inhibit use. Though Medicaid MCOs generally cover prescription drugs, several states have carved out direct-acting antiviral HCV medications from MCO coverage and opted to cover them under fee-for-service. Whether these carve outs were associated with changes in medication use is unknown.ObjectiveTo examine the association between Medicaid-covered HCV medication fills and carve outs of these medications from MCO coverage.Design setting and participantsThis cross-sectional study examined changes in fills of Medicaid-covered direct-acting antiviral HCV medications in 4 states (Indiana, Michigan, New Hampshire, and West Virginia) that carved out these drugs from Medicaid MCOs between 2015 and 2017. A synthetic control approach was used to compare changes in HCV prescription fills between states that did and did not carve out these medications from MCO prescription drug coverage. Data of direct-acting antiviral HCV prescription fills were obtained from the Medicaid State Drug Utilization Data files, January 2015 to June 2020. Data analysis was conducted from November 2020 to June 2021.ExposuresCarve outs of direct-acting antiviral HCV medications from Medicaid MCO prescription drug coverage.Main outcomes and measuresDirect-acting antiviral HCV prescriptions filled per 100 000 Medicaid enrollees.ResultsIn this cross-sectional study, carve outs were associated with a mean quarterly increase of 22.1 (95% CI, 12.7-34.1) HCV prescriptions per 100 000 Medicaid enrollees, a relative increase of 86.3% compared with synthetic control states. Compared with each state's respective synthetic control, HCV prescription fills were associated with an increase of 11.5 (95% CI, 5.1-19.0) HCV prescription fills per 100 000 Medicaid enrollees per quarter in Indiana, 36.6 (95% CI, 23.5-53.9) in Michigan, 20.7 (95% CI, 11.1-32.8) in West Virginia, and 43.6 (95% CI, 25.9-68.4) in New Hampshire.Conclusions and relevanceIn this cross-sectional study of data from 39 states and the District of Columbia, carve outs of direct-acting antiviral HCV medications from Medicaid MCO prescription drug coverage were associated with significant increases in HCV medication use. Given their clinical benefits, greater uptake of HCV medication may help improve the health of Medicaid enrollees with HCV and reduce the economic burden of untreated HCV on the US health care system.

Project description:ImportanceBetween 1997 and 2017, the United States saw increases in nonmedical prescription opioid use and its consequences, as well as changes in marijuana policies. Ecological-level research hypothesized that medical marijuana legalization may reduce prescription opioid use by allowing medical marijuana as an alternative.ObjectivesTo investigate the association of state-level medical marijuana law enactment with individual-level nonmedical prescription opioid use and prescription opioid use disorder among prescription opioid users and to determine whether these outcomes varied by age and racial/ethnic groups.Design, setting, and participantsThis cross-sectional study used restricted data on 627 000 individuals aged 12 years and older from the 2004 to 2014 National Survey on Drug Use and Health, a population-based survey representative of the civilian population of the United States. Analyses were completed from March 2018 to May 2018.ExposuresTime-varying indicator of state-level medical marijuana law enactment (0 = never law enactment, 1 = before law enactment, and 2 = after law enactment).Main outcomes and measuresPast-year nonmedical prescription opioid use and prescription opioid use disorder among prescription opioid users. Odds ratios of nonmedical prescription opioid use and prescription opioid use disorder comparing the period before and after law enactment were presented overall, by age and racial/ethnic group, and adjusted for individual- and state-level confounders.ResultsThe study sample included 627 000 participants (51.51% female; 9.88% aged 12-17 years, 13.30% aged 18-25 years, 14.30% aged 26-34 years, 25.02% aged 35-49 years, and 37.50% aged ≥50 years; the racial/ethnic distribution was 66.97% non-Hispanic white, 11.83% non-Hispanic black, 14.47% Hispanic, and 6.73% other). Screening and interview response rates were 82% to 91% and 71% to 77%, respectively. Overall, there were small changes in nonmedical prescription opioid use prevalence after medical marijuana law enactment (4.32% to 4.86%; adjusted odds ratio, 1.13; 95% CI, 1.06-1.20). Prescription opioid use disorder prevalence among prescription opioid users decreased slightly after law enactment, but the change was not statistically significant (15.41% to 14.76%; adjusted odds ratio, 0.95; 95% CI, 0.81-1.11). Outcomes were similar when stratified by age and race/ethnicity.Conclusions and relevanceThis study found little evidence of an association between medical marijuana law enactment and nonmedical prescription opioid use or prescription opioid use disorder among prescription opioid users. Further research should disentangle the potential mechanisms through which medical marijuana laws may reduce opioid-related harm.

Project description:ImportancePatients who have a fragility fracture are at high risk for subsequent fractures. Prescription drugs represent 1 factor that could be modified to reduce the risk of subsequent fracture.ObjectiveTo describe the use of prescription drugs associated with fracture risk before and after fragility fracture.Design, setting, and participantsRetrospective cohort study conducted between February 2015 and March 2016 using a 40% random sample of Medicare beneficiaries from 2007 through 2011 in general communities throughout the United States. A total of 168 133 community-dwelling Medicare beneficiaries who survived a fracture of the hip, shoulder, or wrist were included. Cohort members were required to be enrolled in fee-for-service Medicare with drug coverage (Parts A, B, and D) and to be community dwelling for at least 30 days in the immediate 4-month postfracture period.ExposuresPrescription drug use during the 4-month period before and after a fragility fracture.Main outcomes and measuresPrescription fills for drug classes associated with increased fracture risk were measured using Part D retail pharmacy claims. These were divided into 3 categories: drugs that increase fall risk; drugs that decrease bone density; and drugs with unclear fracture risk mechanism. Drugs that increase bone density were also tracked.ResultsA total of 168 133 patients with a fragility fracture (141 569 women; 84.2%) met the inclusion criteria for this study; 91.8% were white. Across all fracture types, the mean (SD) age was 80.0 (7.7) years, and 53.2% of the fracture cohort was hospitalized at the time of the index fracture, although this varied significantly depending on fracture type (100% of hip fractures, 8.2% of wrist fractures, and 15.0% of shoulder fractures). The frequency of discharge to an institution for rehabilitation following hospitalization also varied by fracture type, but the mean (SD) duration of acute rehabilitation did not: 28.1 (19.8) days. Most patients were exposed to at least 1 nonopiate drug associated with increased fracture risk in the 4 months before fracture (77.1% of hip, 74.1% of wrist, and 75.9% of shoulder fractures). Approximately 7% of these patients discontinued this drug exposure after the fracture, but this was offset by new users after fracture. Consequently, the proportion of the cohort exposed following fracture was unchanged (80.5%, 74.3%, and 76.9% for hip, wrist, and shoulder, respectively). There was no change in the average number of fracture-associated drugs used. This same pattern of use before and after fracture was observed across all 3 drug mechanism categories. Use of drugs to strengthen bone density was uncommon (≤25%) both before and after fracture.Conclusions and relevanceExposure to prescription drugs associated with fracture risk is infrequently reduced following fragility fracture occurrence. While some patients eliminate their exposure to drugs associated with fracture, an equal number initiate new high-risk drugs. This pattern suggests there is a missed opportunity to modify at least one factor contributing to secondary fractures.

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Association of California's Prescription Drug Coupon Ban With Generic Drug Use.

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