Characteristics of Prescription Drug Fills Using Pharmacy-Pharmacy Benefit Manager Discount Programs: The "GoodRx" Model.

OBJECTIVES: This study aimed to characterize products using pharmacy-pharmacy benefit manager (PBM) discounts and to estimate the association among such discounts, prescription utilization, and out-of-pocket costs. METHODS: This is a retrospective cohort study using IQVIA's Formulary Impact Analyzer, which contains anonymized, individual-level pharmacy claims representing US retail pharmacy transactions. We focused on 20 products with the greatest number of transactions using a pharmacy-PBM discount. Our unit of analysis was a treatment episode, defined as the length of time from an incident fill to no continuous use for 60 consecutive days after allowing for indefinite stockpiling. Outcome measures included products with greatest pharmacy-PBM discount use, characteristics of treatment episodes, and out-of-pocket costs with and without pharmacy-PBM discount. RESULTS: Across all products, 3.82% of transactions and 7.69% of treatment episodes were accompanied by a pharmacy-PBM discount. Commonly discounted products included generic treatments for chronic disease (lisinopril, levothyroxine, metformin) and neuropsychiatric conditions (alprazolam, amphetamine, buprenorphine, hydrocodone). The median postdiscount out-of-pocket cost was >2.5-fold higher during treatment episodes with a discount than those without ($15.15, interquartile range [IQR] $8.53-32.00, vs $5.88, IQR $1.40-15.00). Median treatment episode duration was 249 days (IQR 132-418) with discount use compared with 236 days (IQR 121-396) without discount use, although treatment episodes that began with a discount had fewer transactions per treatment episode and were shorter (median 212 days, IQR 114-360) than those that did not (313 days, IQR 178-500). CONCLUSIONS: Pharmacy-PBM discounts may foster market competition and improve access for under- and uninsured individuals; however, these programs may not generate savings for many insured individuals.

Real-World Effectiveness of Remdesivir in Adults Hospitalized With Coronavirus Disease 2019 (COVID-19): A Retrospective, Multicenter Comparative Effectiveness Study.

BACKGROUND: There is an urgent need to understand the real-world effectiveness of remdesivir in the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: This was a retrospective comparative effectiveness study. Individuals hospitalized in a large private healthcare network in the United States from 23 February 2020 through 11 February 2021 with a positive test for SARS-CoV-2 and ICD-10 diagnosis codes consistent with symptomatic coronavirus disease 2019 (COVID-19) were included. Remdesivir recipients were matched to controls using time-dependent propensity scores. The primary outcome was time to improvement with a secondary outcome of time to death. RESULTS: Of 96 859 COVID-19 patients, 42 473 (43.9%) received at least 1 remdesivir dose. The median age of remdesivir recipients was 65 years, 23 701 (55.8%) were male, and 22 819 (53.7%) were non-White. Matches were found for 18 328 patients (43.2%). Remdesivir recipients were significantly more likely to achieve clinical improvement by 28 days (adjusted hazard ratio [aHR] 1.19, 95% confidence interval [CI], 1.16-1.22). Remdesivir patients on no oxygen (aHR 1.30, 95% CI, 1.22-1.38) or low-flow oxygen (aHR 1.23, 95% CI, 1.19-1.27) were significantly more likely to achieve clinical improvement by 28 days. There was no significant impact on the likelihood of mortality overall (aHR 1.02, 95% CI, .97-1.08). Remdesivir recipients on low-flow oxygen were significantly less likely to die than controls (aHR 0.85, 95% CI, .77-.92; 28-day mortality 8.4% [865 deaths] for remdesivir patients, 12.5% [1334 deaths] for controls). CONCLUSIONS: These results support the use of remdesivir for hospitalized COVID-19 patients on no or low-flow oxygen. Routine initiation of remdesivir in more severely ill patients is unlikely to be beneficial.

Perceived Unintended Consequences of Prescription Drug Monitoring Programs.

BACKGROUND: Opioid-related injuries and deaths continue to present challenges for public health practitioners. Prescription Drug Monitoring Programs (PDMPs) are a prevalent policy option intended to address problematic opioid pain reliever (OPR) prescribing, but previous research has not thoroughly characterized their unintended consequences. OBJECTIVES: To examine state actors' perceptions of the unintended consequences of PDMPs. METHODS: We conducted 37 interviews with PDMP staff, law enforcement officials, and administrative agency employees in Florida, Kentucky, New Jersey, and Ohio from May 2015 to June 2016. RESULTS: We identified six themes from the interviews. Perceived negative unintended consequences included: access barriers for those with medical needs, heroin use as OPR substitute and related deaths, and need for adequate PDMP security infrastructure and management. Perceived positive unintended consequences were: community formation and problem awareness, proactive population-level OPR monitoring, and increased knowledge about population-level drug diversion. Conclusions/Importance: State actors perceive a range of both negative and positive unintended consequences of PDMPs. Our findings suggest that there may be unintended risks of PDMPs that states should address, but also opportunities to maximize certain benefits.

Opioid Prescriptions After Total Joint Arthroplasty.

Prescription opioids are commonly prescribed for pain relief after total joint arthroplasty (TJA), yet little is known about the quantity of opioids prescribed after surgery. This study retrospectively reviewed a consecutive series of 1000 TJAs from April 2014 through September 2015. Postoperative opioid prescriptions were quantified using standardized morphine milligram equivalents (MME). Eighty-four percent of total knee arthroplasty (TKA) and 77% of total hip arthroplasty (THA) patients were opioid naïve. The median opioid volume of the first prescription for those undergoing TKA was greater than for those undergoing THA (600 vs. 450 MME), as was the proportion of individuals requiring one or more refills (48% vs. 32%). The total volume of opioids after TKA was also higher than for total hip replacement (870 vs. 525 MME). Patients who were not opioid naïve were prescribed substantially more opioids than their counterparts after TKA (mean 1593 vs. 1064 MME, p < .001) and THA (mean 1031 vs. 663 MME, p < .001). Decreasing opioid use before surgery may decrease total volume of opioid prescriptions after TJA. (Journal of Surgical Orthopaedic Advances 27(3):231-236, 2018).

Patterns of Buprenorphine-Naloxone Treatment for Opioid Use Disorder in a Multistate Population.

BACKGROUND: Buprenorphine-naloxone treatment for opioid use disorder has rapidly expanded, yet little is known about treatment outcomes among patients in the general population. OBJECTIVE: To examine predictors of treatment duration, dosage, and continuity in a diverse community setting. RESEARCH DESIGN: We examined QuintilesIMS Real World Data, an all-payer, pharmacy claims database, to conduct an analysis of individuals age 18 years and above initiating buprenorphine-naloxone treatment between January 2010 and July 2012 in 11 states. We used logistic regression to assess treatment duration longer than 6 months. We used accelerated failure time models to assess risk of treatment discontinuation. We used ordinary least squares regression to assess mean daily dosage. For patients with ≥3 fills, we also used logistic regression to assess whether ;an individual had a medication possession ratio of <80% and/or gaps in treatment >14 days. Models adjusted for individual demographics, prescribing physician specialty, state, and county-level variables. RESULTS: Overall, 41% of individuals were retained in treatment for at least 6 months and the mean treatment length was 266 days. Compared with individuals who paid primarily for treatment with cash, adjusted odds of 6 month retention were significantly lower for individuals with primary payment from Medicaid fee-for-service, Medicare part D, and third-party commercial. There were substantial differences in 6-month retention across states with the lowest in Arizona and highest in New York. Low-possession ratios occurred for 30% of individuals and 26% experienced treatment episodes with gaps >14 days. Odds of low-possession and treatment gaps were largely similar across demographic groups and geographic areas. CONCLUSIONS: Current initiatives to improve access and quality of buprenorphine-naloxone treatment should examine geographic barriers as well as the potential role of insurance benefit design in restricting treatment length.

The Opioid Industry Documents Archive: Advancing Public Health Through Industry Document Disclosure.

More than twenty-five years after the first signs of potential harm, the US remains locked in the grip of an opioid epidemic, with more Americans dying from overdoses than ever before.1 Diversion of prescription opioids plays an important role in opioid-related harms. Much of the scientific and public health focus on diversion has been on end-users, given how commonly non-medical prescription opioid use occurs, as well as the proportion of individuals who report that their source of non-medical opioids was friends or family. However, diversion of opioids, as well as their rampant oversupply, can be discerned higher up the supply chain, including among wholesalers, pharmacies and rogue prescribers whose behavior may trigger well-described "flags" warranting further evaluation and action.

Protocol: mixed-methods study to evaluate implementation, enforcement, and outcomes of U.S. state laws intended to curb high-risk opioid prescribing.

BACKGROUND: The U.S. opioid epidemic has been driven by the high volume of opioids prescribed by healthcare providers. U.S. states have recently enacted four types of laws designed to curb high-risk prescribing practices, such as high-dose and long-term opioid prescribing, associated with opioid-related mortality: (1) mandatory Prescription Drug Monitoring Program (PDMP) enrollment laws, which require prescribers to enroll in their state's PDMP, an electronic database of patients' controlled substance prescriptions, (2) mandatory PDMP query laws, which require prescribers to query the PDMP prior to prescribing an opioid, (3) opioid prescribing cap laws, which limit the dose and/or duration of opioid prescriptions, and (4) pill mill laws, which strictly regulate pain clinics to prevent nonmedical opioid prescribing. Some pain experts have expressed concern that these laws could negatively affect pain management among patients with chronic non-cancer pain. This paper describes the protocol for a mixed-methods study analyzing the independent effects of these four types of laws on opioid prescribing patterns and chronic non-cancer pain treatment, accounting for variation in implementation and enforcement of laws across states. METHODS: Many states have enacted multiple opioid prescribing laws at or around the same time. To overcome this issue, our study focuses on 18 treatment states that each enacted a single law of interest, and no other potentially confounding laws, over a 4-year period (2 years pre-/post-law). Qualitative interviews with key leaders in each of the 18 treatment states will characterize the timing, scope, and strength of each state law's implementation and enforcement. This information will inform the design and interpretation of synthetic control models analyzing the effects of each of the two types of laws on two sets of outcomes: measures of (1) high-risk opioid prescribing and (2) non-opioid treatments for chronic non-cancer pain. DISCUSSION: Study of mandatory PDMP enrollment, mandatory PDMP query, opioid prescribing cap, and pill mill laws is timely given a dynamic policy environment in which numerous states pass, revise, implement, and enforce varied laws to address opioid prescribing each year. Findings will inform enactment, implementation, and enforcement of these laws in additional states.

A conceptually based approach to understanding chronically ill patients' responses to medication cost pressures.

Prescription medications enhance the well-being of most chronically ill patients. Many individuals, however, struggle with how to pay for their treatments and as a result experience problems with self-care and health maintenance. Although studies have documented that high out-of-pocket costs are associated with medication non-adherence, little research on prescription cost sharing has been theoretically grounded in knowledge of the more general determinants of patients' self-management behaviors and chronic disease outcomes. We present a conceptual framework for understanding the influence of patient, medication, clinician, and health system factors on individuals' responses to medication costs. We review what is known about how these factors influence medication adherence, identify possible strategies through which clinicians, health systems, and policy-makers may assist patients burdened by their medication costs, and highlight areas in need of further research. Although medication costs represent a burden to chronically ill patients worldwide, most patients report using their medication as prescribed despite the costs, and others report cost-related underuse despite an apparent ability to afford those treatments. The cost-adherence relationship is modified by contextual factors, including patients' characteristics (e.g., age, ethnicity, and attitudes toward medications), the type of medications they are using (e.g., the complexity of dosing and the drug's clinical target), clinician factors (e.g., choice of first-line agent and communication about medication costs), and health system factors (e.g., efforts to influence clinicians' prescribing and to help patients apply for financial assistance programs). Understanding these relationships will enable clinicians and policy-makers to better design pharmacy benefits and assist patients in taking their medication as prescribed. The next generation of studies examining the consequences of prescription drug costs should expand our knowledge of the ways in which these co-factors influence patients' responses to medication cost pressures.