Extent of a valsartan drug shortage and its effect on antihypertensive drug use in the Canadian population: a national cross-sectional study.

BACKGROUND: Drug shortages represent a growing global problem, with potentially serious consequences to patients and the health care system. Our study investigates the impacts of a major recall and shortage of valsartan, an angiotensin receptor blocker (ARB), in July 2018 in Canada. METHODS: We conducted a time-series analysis of antihypertensive drugs dispensed in Canada between 2015 and 2019 using commercially available retail prescription data. Using autoregressive integrated moving average (ARIMA) modelling, we evaluated the change in valsartan use after the recall. We also measured the overall use of ARBs, angiotensin-converting-enzyme (ACE) inhibitors and other antihypertensive drug classes for the same period. RESULTS: After the recall in July 2018, valsartan use decreased 57.8%, from 362 231 prescriptions dispensed in June 2018 to 152 892 in September 2018 (difference = 209 339, p < 0.0001). Overall use of the ARB drug class decreased 2.0%, from 1 577 509 prescriptions dispensed in June 2018 to 1 545 591 in September 2018 (difference = 31 918, p = 0.0003), but use of non-valsartan ARBs increased 14.6%, from 1 215 278 to 1 392 699 prescriptions dispensed (difference = 177 421, p < 0.0001) in the same time frame. Although use of ACE inhibitors initially declined, this reduction was not sustained. The valsartan recall was not associated with a significant impact on use of other antihypertensive drug classes. INTERPRETATION: Our findings illustrate the impact of a major drug shortage, with the immediate and substantial reduction of valsartan dispensed and cascading effects on other ARBs, though future research is warranted to understand the consequences of such extensive shortages on clinical outcomes and health system costs. Improved policy strategies are needed to address the underlying causes of drug shortages and to mitigate their effects.

Comparison of claims from high-drug cost beneficiaries in Ontario, Canada, and Australia: a cross-sectional analysis.

BACKGROUND: Globally, payers are struggling with rising drug costs, driven primarily by the increasing number of high-cost medications used by their beneficiaries. We aimed to compare the annual drug spending on claims from high-drug cost beneficiaries in the province of Ontario, Canada, and Australia. METHODS: We conducted a cross-sectional analysis of public drug claims in Ontario and Australia from fiscal years 2006 to 2017. We identified the total government costs for prescribed medications per beneficiary. During the study period, public drug coverage in Ontario was provided to all residents 65 years of age and older, those with financial needs, and those living in long-term care or in need of home care. Australia maintains a publicly funded, universal system covering all citizens. Based on annual spending, we divided beneficiaries into 4 cost groups, representing the top 1%, top 5%, top 10% and the remaining 90%. We reported the following for each cost group: medication cost and proportion of total government spending, number of unique drugs dispensed per person and the top 10 most costly drug classes. RESULTS: In Ontario and Australia, the top 1% of beneficiaries accounted for a large and increasing proportion of all government drug costs, growing from 12% ($405 946 197) to 24% ($1 345 977 248) in Ontario, and from 14% ($86 565 586) to 34% ($416 097 984) in Australia between 2006 and 2017. The most costly drug classes among high-drug cost beneficiaries in both jurisdictions were biologics and hepatitis C treatments. INTERPRETATION: In both Ontario and Australia, a small number of beneficiaries accounted for a large proportion of public drug spending, driven largely by the use of expensive medications. The current development of potential national pharmacare strategies in Canada must optimize the use of high-cost drugs to ensure the sustainability of the program.

Pharmacological Predictors of Morbidity and Mortality in COVID-19.

The interaction of coronavirus disease (COVID-19) with the majority of common prescriptions is broadly unknown. The purpose of this study is to identify medications associated with altered disease outcomes in COVID-19. A retrospective cohort composed of all adult inpatient admissions to our center with COVID-19 was analyzed. Data concerning all antecedent prescriptions were collected and agents brought forward for analysis if prescribed to at least 20 patients in our cohort. Forty-two medications and 22 classes of medication were examined. Groups were propensity score matched and analyzed by logistic and linear regression. The majority of medications did not show a statistically significant relationship with altered disease outcomes. Lower mortality was associated with use of pregabalin (hazard ratio [HR], 0.10; 95% confidence interval [CI], 0.01-0.92; P = .049) and inhalers of any type (HR, 0.33; 95%CI, 0.14-0.80; P = .015), specifically beclomethasone (HR, 0.10; 95%CI, 0.01-0.82; P = .032), tiotropium (HR, 0.07; 95%CI, 0.01-0.83; P = .035), and steroid-containing inhalers (HR, 0.35; 95%CI, 0.15-0.79; P = .013). Gliclazide (HR, 4.37; 95%CI, 1.26-15.18; P = .020) and proton pump inhibitor (HR, 1.72; 95%CI, 1.06-2.79; P = .028) use was associated with greater mortality. Diuretic (HR, 0.07; 95%CI, 0.01-0.37; P = .002) and statin (HR, 0.35; 95%CI, 0.17-0.73; P = .006) use was associated with lower rates of critical care admission. Our data lends confidence to observing usual practice in patients with COVID-19 by continuing antecedent prescriptions in the absence of an alternative acute contraindication. We highlight potential benefits in investigation of diuretics, inhalers, pregabalin, and statins as therapeutic agents for COVID-19 and support further assessment of the safety of gliclazide and proton pump inhibitors in the acute illness.

Medications and risk of motor vehicle collision responsibility in British Columbia, Canada: a population-based case-control study.

BACKGROUND: Many medications impair driving skills yet their influence on collision risk remains uncertain. We aimed to systematically investigate the risk of collision responsibility associated with common classes of prescription medications. METHODS: In this population-based case-control study we analysed linked driving and health records in British Columbia, Canada from Jan 1, 1997, to Dec 31, 2016. The study cohort included all drivers involved in an incident collision (defined as first collision after 3 collision-free years) that resulted in a police report. We scored police collision reports and classified drivers as responsible for the collision (cases) or not responsible (controls); drivers with indeterminate scores were excluded. We used logistic regression to determine odds of collision responsibility in drivers with current prescriptions for medications of interest versus drivers without prescriptions. To explore whether risk of collision responsibility was related to medication effect or driver factors, we compared risk in current medication users versus past users. To study whether drivers developed tolerance to medication effects, we compared risk in new (first 30 days of a prescription) versus established users. FINDINGS: During the study period, 4 906 925 drivers had their driving licence linked to health records; of these drivers, 747 662 unique drivers were involved in 837 919 incident collisions between Jan 1, 2000, and Dec 31, 2016. 382 685 drivers responsible for the collision (cases) and 332 259 drivers not responsible (controls) were included in the final analysis; 122 975 drivers with indeterminate responsibility were excluded. We found increased risk of collision responsibility in drivers prescribed sedating antipsychotics (adjusted odds ratio [aOR] 1·35 [98·75% CI 1·25-1·46]), long-acting benzodiazepines (aOR 1·30 [1·22-1·38]), short-acting benzodiazepines (aOR 1·25 [1·20-1·31]), and high-potency opioids (aOR 1·24 [1·17-1·30]). Among medications used for medical indications, the highest risk was seen in drivers prescribed neurological medications: cholinergic drugs (aOR 1·83 [1·39-2·40]), anticholinergic agents for Parkinson's disease (aOR 1·45 [1·08-1·96]), dopaminergic agents (aOR 1·20 [1·04-1·38]), and anticonvulsants (aOR 1·20 [1·14-1·26]). People currently taking benzodiazepines, non-sedating antidepressants, high-potency opioids, and anticonvulsants had increased risk compared with past users, and we did not find increased risk in new compared with established users of these drugs. INTERPRETATION: Drivers prescribed benzodiazepines or high-potency opioids are at increased risk of being responsible for collisions and this risk does not decrease over time. Several other classes of medications are associated with increased risk, but this association might be independent of medication effect. These findings can guide medication warnings and prescription choices and inform public education campaigns targeting impaired driving. FUNDING: Canadian Institutes of Health Research.

High-content, targeted RNA-seq screening in organoids for drug discovery in colorectal cancer.

Organoids allow the recapitulation of intestinal homeostasis and cancerogenesis in vitro; however, RNA sequencing (RNA-seq)-based methods for drug screens are missing. We develop targeted organoid sequencing (TORNADO-seq), a high-throughput, high-content drug discovery platform that uses targeted RNA-seq to monitor the expression of large gene signatures for the detailed evaluation of cellular phenotypes in organoids. TORNADO-seq is a fast, highly reproducible time- and cost-effective ($5 per sample) method that can probe cell mixtures and their differentiation state in the intestinal system. We apply this method to isolate drugs that enrich for differentiated cell phenotypes and show that these drugs are highly efficacious against cancer compared to wild-type organoids. Furthermore, TORNADO-seq facilitates in-depth insight into the mode of action of these drugs. Our technology can easily be adapted to many other systems and will allow for more systematic, large-scale, and quantitative approaches to study the biology of complex cellular systems.

ConjuPepDB: a database of peptide-drug conjugates.

Peptide-drug conjugates are organic molecules composed of (i) a small drug molecule, (ii) a peptide and (iii) a linker. The drug molecule is mandatory for the biological action, however, its efficacy can be enhanced by targeted delivery, which often also reduces unwanted side effects. For site-specificity the peptide part is mainly responsible. The linker attaches chemically the drug to the peptide, but it could also be biodegradable which ensures controlled liberation of the small drug. Despite the importance of the field, there is no public comprehensive database on these species. Herein we describe ConjuPepBD, a freely available, fully annotated and manually curated database of peptide drug conjugates. ConjuPepDB contains basic information about the entries, e.g. CAS number. Furthermore, it also implies their biomedical application and the type of chemical conjugation employed. It covers more than 1600 conjugates from ∼230 publications. The web-interface is user-friendly, intuitive, and useable on several devices, e.g. phones, tablets, PCs. The webpage allows the user to search for content using numerous criteria, chemical structure and a help page is also provided. Besides giving quick insight for newcomers, ConjuPepDB is hoped to be also helpful for researchers from various related fields. The database is accessible at: https://conjupepdb.ttk.hu/.

CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors.

Inhibitors that form covalent bonds with their targets have traditionally been considered highly adventurous due to their potential off-target effects and toxicity concerns. However, with the clinical validation and approval of many covalent inhibitors during the past decade, design and discovery of novel covalent inhibitors have attracted increasing attention. A large amount of scattered experimental data for covalent inhibitors have been reported, but a resource by integrating the experimental information for covalent inhibitor discovery is still lacking. In this study, we presented Covalent Inhibitor Database (CovalentInDB), the largest online database that provides the structural information and experimental data for covalent inhibitors. CovalentInDB contains 4511 covalent inhibitors (including 68 approved drugs) with 57 different reactive warheads for 280 protein targets. The crystal structures of some of the proteins bound with a covalent inhibitor are provided to visualize the protein-ligand interactions around the binding site. Each covalent inhibitor is annotated with the structure, warhead, experimental bioactivity, physicochemical properties, etc. Moreover, CovalentInDB provides the covalent reaction mechanism and the corresponding experimental verification methods for each inhibitor towards its target. High-quality datasets are downloadable for users to evaluate and develop computational methods for covalent drug design. CovalentInDB is freely accessible at http://cadd.zju.edu.cn/cidb/.

Docking Paradigm in Drug Design.

Docking is in demand for the rational computer aided structure based drug design. A review of docking methods and programs is presented. Different types of docking programs are described. They include docking of non-covalent small ligands, protein-protein docking, supercomputer docking, quantum docking, the new generation of docking programs and the application of docking for covalent inhibitors discovery. Taking into account the threat of COVID-19, we present here a short review of docking applications to the discovery of inhibitors of SARS-CoV and SARS-CoV-2 target proteins, including our own result of the search for inhibitors of SARS-CoV-2 main protease using docking and quantum chemical post-processing. The conclusion is made that docking is extremely important in the fight against COVID-19 during the process of development of antivirus drugs having a direct action on SARS-CoV-2 target proteins.

Global Substance Registration System: consistent scientific descriptions for substances related to health.

The US Food and Drug Administration (FDA) and the National Center for Advancing Translational Sciences (NCATS) have collaborated to publish rigorous scientific descriptions of substances relevant to regulated products. The FDA has adopted the global ISO 11238 data standard for the identification of substances in medicinal products and has populated a database to organize the agency's regulatory submissions and marketed products data. NCATS has worked with FDA to develop the Global Substance Registration System (GSRS) and produce a non-proprietary version of the database for public benefit. In 2019, more than half of all new drugs in clinical development were proteins, nucleic acid therapeutics, polymer products, structurally diverse natural products or cellular therapies. While multiple databases of small molecule chemical structures are available, this resource is unique in its application of regulatory standards for the identification of medicinal substances and its robust support for other substances in addition to small molecules. This public, manually curated dataset provides unique ingredient identifiers (UNIIs) and detailed descriptions for over 100 000 substances that are particularly relevant to medicine and translational research. The dataset can be accessed and queried at https://gsrs.ncats.nih.gov/app/substances.

Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients.

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, Setting, and Participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures: Prescription of 38 level A medications based on electronic health records. Main Outcomes and Measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and Relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Changes in Drug List Prices and Amounts Paid by Patients and Insurers.

Importance: High out-of-pocket drug costs can cause patients to skip treatment and worsen outcomes, and high insurer drug payments could increase premiums. Drug wholesale list prices have doubled in recent years. However, because of manufacturer discounts and rebates, the extent to which increases in wholesale list prices are associated with amounts paid by patients and insurers is poorly characterized. Objective: To determine whether increases in wholesale list prices are associated with increases in amounts paid by patients and insurers for branded medications. Design, Setting, and Participants: Cross-sectional retrospective study analyzing pharmacy claims for patients younger than 65 years in the IBM MarketScan Commercial Database and pricing data from SSR Health, LLC, between January 1, 2010, and December 31, 2016. Pharmacy claims analyzed represent claims of employees and dependents participating in employer health benefit programs belonging to large employers. Rebate data were estimated from sales data from publicly traded companies. Analysis focused on the top 5 patent-protected specialty and 9 traditional brand-name medications with the highest total drug expenditures by commercial insurers nationwide in 2014. Data were analyzed from July 2017 to July 2020. Exposures: Calendar year. Main Outcomes and Measures: Changes in inflation-adjusted amounts paid by patients and insurers for branded medications. Results: In this analysis of 14.4 million pharmacy claims made by 1.8 million patients from 2010-2016, median drug wholesale list price increased by 129% (interquartile range [IQR], 78%-133%), while median insurance payments increased by 64% (IQR, 28%-120%) and out-of-pocket costs increased by 53% (IQR, 42%-82%). The mean percentage of wholesale list price accounted for by discounts increased from 17% in 2010 to 21% in 2016, and the mean percentage of wholesale list price accounted for by rebates increased from 22% in 2010 to 24% in 2016. For specialty medications, median patient out-of-pocket costs increased by 85% (IQR, 73%-88%) from 2010 to 2016 after adjustment for inflation and 42% (IQR, 25%-53%) for nonspecialty medications. During that same period, insurer payments increased by 116% for specialty medications (IQR, 100%-127%) and 28% for nonspecialty medications (IQR, 5%-34%). Conclusions and Relevance: This study's findings suggest that drug list prices more than doubled over a 7-year study period. Despite rising manufacturer discounts and rebates, these price increases were associated with large increases in patient out-of-pocket costs and insurer payments.

Prescribers aware: a cross-sectional study from New Zealand emergency departments on the substances used in intentional self-poisoning and their sources.

INTRODUCTION Intentional self-poisoning or self-harm through poisoning, is a common cause of presentations to emergency departments (EDs). National datasets do not allow identification of the substances most commonly used in hospital-treated intentional self-poisoning in New Zealand, nor do they capture sources of these substances. AIM To investigate the specific substances used in intentional self-poisoning and the sources from which they are obtained. METHODS In this cross-sectional study, information about the demographics and presentation particulars of intentional self-poisoning patients aged ≥16 years, presenting to three public EDs, as well as the substances they used in the self-poisoning event and the sources of these agents, were collected prospectively. RESULTS A total of 102 patients were recruited from the potentially eligible 1137 intentional self-poisoning patients presenting to the three EDs during the study period. Seventy per cent used their own prescription medications and 24% used medicines they purchased themselves. Paracetamol and ethanol were most commonly encountered substances. Patients presented a median of 1.9h after exposure (interquartile range 1.0-3.3h), 62% self-referred, 60% presented to the ED in the evening or at night and 66% were triaged into Australasian Triage Scale 3 (to be seen within 30min). Two-thirds were referred to emergency psychiatric services. DISCUSSION Collecting specific substance information, such as from this study, can assist in planning specific activities to prevent intentional self-poisoning. As most people used their prescribed medicines, the findings can inform and assist doctors in their prescribing practices when they manage patients at risk of self-poisoning.

Should the Same Safety Scrutiny of Antiobesity Medications be Applied to Other Chronic Usage Drugs?

Obesity treatment is highly stigmatized, mainly because of the stigma of obesity itself. The frequent withdrawal of medications, lorcaserin being the last example, contributes to this stigma, but it is also probably a reflection of it, as data suggest that the threshold for a withdrawal is lower than with other classes of drugs. Safety should always be an absolute priority for every new medication, especially when used on a chronic basis; however, the safety scrutiny given to antiobesity medications is not given for other medications, such as postmenopausal hormone therapy and central nervous system drugs for psychiatric use. The withdrawal of medications for obesity can also impact future research in the area, so we need transparency and equality. Transparency in knowing exactly what reason led to a drug being discontinued and equality in long-term safety should be a concern with any medication prescribed for chronic diseases.

Prescribed Drug Spending in Canada, 2019: A Focus on Public Drug Programs.

Public drug program spending accounts for 43.1% of prescribed drug spending in Canada. This report provides an in-depth look at public drug program spending in Canada, using the Canadian Institute for Health Information's (CIHI) National Prescription Drug Utilization Information System. Public drug program spending does not include spending on drugs dispensed in hospitals or on those funded through cancer agencies and other special programs.

The French reporting system for drug shortages: description and trends from 2012 to 2018: an observational retrospective study.

OBJECTIVES: The aim was to provide figures for drug shortages in France and describe their characteristics, causes and trends between 2012 and 2018. METHODS: Data from the national reporting system from the Agency of Medicine and Health Product Safety (ANSM) was analysed. This database contains information regarding effective and predicted shortages of major therapeutic of interest drugs (ie, drugs whose shortage would be life-threatening or representing a loss of treatment opportunity for patients with a severe disease) which are mandatory reported by marketing authorisation holders to the ANSM. Data are presented as numbers or percentages of pharmaceutical products (ie, the product name and its formulation) reported on shortage between 2012 and 2018. RESULTS: There were 3530 pharmaceutical products reported on shortage during the period, including 1833 different active substances. Drugs on shortage were mostly old products (63.4%) with national marketing authorisation procedures (62.8%), as well as injectable and oral forms (47.5% and 43.3%, respectively). Anti-infectives for systemic use ranked first (18%), followed by nervous and cardiovascular system drugs and by antineoplastic and immunomodulating agents (17.4%, 12.5% and 10.4%, respectively). The number of reported shortages presented a fourfold increase between 2012 and 2018 and a sharp rise in 2017 and 2018, along with a rise in the number of active substances on shortage. The therapeutic classes concerned remained similar over time. Manufacturing and material supply issues were the main reported reasons for the shortage each year (30%) and there was an overall rise of pharmaceutical market reasons. CONCLUSION: Drug shortages were increasingly reported in France. Preventive measures should specifically target the products most on shortage, in particular old drugs, injectable, anti-infective, nervous system and cardiovascular system drugs as well as antineoplastic and immunomodulating agents.

Patient-reported outcomes in light of supportive medications in treatment-naïve lung cancer patients.

PURPOSE: The impact of supportive medications on patient-reported outcomes (PROs) has not been systematically evaluated. We describe the supportive medications used by treatment-naïve lung cancer patients and assess their association with PROs from MD Anderson Symptom Inventory (MDASI). METHODS: Treatment-naïve lung cancer patients who completed PROs from MDASI at the initial visit to MD Anderson Cancer Center were included. Medications from the initial visit were abstracted from the electronic medical records system and categorized into therapeutic classes based on U.S. Pharmacopeia v7.0. A chi-square or Mann-Whitney U test was conducted as appropriate. RESULTS: Among 459 patients, ~ 50% took any analgesics and 25% were on opioids. One-third of patients with moderate-severe pain were not on any analgesics. Patients taking opioids had significantly worse median pain scores (6 vs. 0) compared with those not taking any analgesics (p < 0.0001). Higher proportion of patients with moderate-severe pain took opioids compared with those with mild pain (52% vs. 16%, p < 0.0001). Patients on opioids also reported significantly worse scores for five other cancer-specific core symptoms and all six symptoms rating interference with daily life. Only 15% of patients with higher composite score for depression-related symptoms were on antidepressants. However, patients taking antidepressants did not significantly differ in any individual MDASI symptom scores compared with those not on antidepressants (p = 0.4858). CONCLUSIONS: Our results suggest a need for better screening for pain and depression and optimization of pain management in treatment-naïve lung cancer patients since their poor functional status may result in suboptimal cancer therapy.

Can income-based co-payment rates improve disparity? The case of the choice between brand-name and generic drugs.

BACKGROUND: Higher income population tend to prefer brand-name to generic drugs, which may cause disparity in access to brand-name drugs among income groups. A potential policy that can resolve such disparity is imposing a greater co-payment rate on high-income enrollees. However, the effects of such policy are unknown. We examined how patients' choice between brand-name and generic drugs are affected by the unique income-based co-payment rates in Japan; 10% for general enrollees and 30% for those with high income among the elderly aged 75 and over. METHODS: We drew on cross-sectional price variation among commonly prescribed 311 drugs using health insurance claims data from a large prefecture in Japan between October 2013 and September 2014 to identify between-income-group differences in responses to differentiated payments. RESULTS: Running 311 multivariate logistic regression models controlling individual demographics, the median estimate indicated that high-income group was 3% (odds ratio = 0.97) less likely to choose a generic drug than the general-income group and the interquartile estimates ranged 0.92-1.02. The multivariate feasible generalized least squares model indicated high-income group's higher likelihood to choose brand-name drugs than the general-income group without co-payment rate differentiation (p < 0.001). Such gap in the likelihood was attenuated by 0.4% (p = 0.027) with an US$1 increase in the difference in additional payment/month for brand-name drugs between income groups - no gap with US$10 additional payment/month. This attenuation was observed in drugs for chronic diseases only, not for acute diseases. CONCLUSIONS: Income-based co-payment rates appeared to reduce disparity in access to brand-name drugs across income groups, in addition to reducing total medical expenditure among high-income group who shifted from brand-name drugs to generic ones due to larger drug price differences.

Policy Recommendations for Pharmacy Benefit Managers to Stem the Escalating Costs of Prescription Drugs: A Position Paper From the American College of Physicians.

Recent discussions about the increasing prices of prescription drugs have focused on pharmacy benefit managers (PBMs), third-party intermediaries for various types of employers and government purchasers who negotiate drug prices in health plans and thus play a crucial role in determining the amount millions of Americans pay for medications. In this position paper, the American College of Physicians expands on its position paper from 2016 by offering additional recommendations to improve transparency in the PBM industry and highlighting the need for reliable, timely, and relevant information on prescription drug pricing for physicians and patients.

Policy Recommendations for Public Health Plans to Stem the Escalating Costs of Prescription Drugs: A Position Paper From the American College of Physicians.

The increasing price of prescription drugs is an ongoing concern for Medicare and Medicaid, particularly for patients with chronic health conditions who are using multiple medications and patients in these programs taking high-priced brand-name specialty drugs. Shifts in benefit design, including higher deductibles and a movement away from copayments to coinsurance, have increased patient out-of-pocket costs and put pressure on program budgets. In this paper, the American College of Physicians expands on its position paper from 2016 and offers additional recommendations to decrease out-of-pocket costs for patients, enhance the government's purchasing power, and address existing policies that add costs to the health care system.