INTRODUCTION: Several small studies have reported inconsistent findings about the safety of selective serotonin reuptake inhibitors (SSRIs) among patients undergoing coronary artery bypass grafting (CABG). We sought to investigate post-CABG bleeding and mortality outcomes related to antidepressant exposure. METHODS: We identified patients who underwent CABG between 2004 and 2008 in the Premier Perspective Comparative Database. We determined whether they received SSRIs, other antidepressants, or no antidepressants on any pre-CABG hospital day and used Cox proportional hazards models to compare bleeding and mortality rates among the exposure groups while adjusting for potential confounders based on administrative data, pre-CABG charge codes, and discharge diagnosis codes. RESULTS: We identified 132,686 eligible patients: 7112 exposed to SSRIs, 1905 exposed to other antidepressants, and 123,668 unexposed. As compared with no exposure, neither SSRIs (hazard ratio [HR] 0.98; 95 % confidence interval [CI] 0.90-1.07) nor other antidepressants (HR 1.11; 95 % CI 0.96-1.28) increased major bleeds, and neither SSRIs (HR 0.93; 95 % CI 0.80-1.07) nor other antidepressants (HR 0.84; 95 % CI 0.62-1.14) increased mortality. Both SSRIs (HR 1.14; 95 % CI 1.10-1.18) and other antidepressants (HR 1.11; 95 % CI 1.03-1.19) were associated with a slight increase in receipt of one or more packed red blood cell (pRBC) units, but neither were associated with substantial increases in receipt of three or more pRBC units (HR 1.06; 95 % CI 0.96-1.17 for SSRIs; HR 1.09; 95 % CI 0.91-1.31 for other antidepressants). CONCLUSION: In this large cohort study, neither SSRIs nor other antidepressants were associated with elevated rates of major bleed, or in-hospital mortality.
BACKGROUND: Patients, physicians, and other decision makers make implicit but inevitable trade-offs among risks and benefits of treatments. Many methods have been proposed to promote transparent and rigorous benefit-risk analysis (BRA). OBJECTIVE: To propose a framework for classifying BRA methods on the basis of key factors that matter most for patients by using a common mathematical notation and compare their results using a hypothetical example. METHODS: We classified the available BRA methods into three categories: 1) unweighted metrics, which use only probabilities of benefits and risks; 2) metrics that incorporate preference weights and that account for the impact and duration of benefits and risks; and 3) metrics that incorporate weights based on decision makers' opinions. We used two hypothetical antiplatelet drugs (a and b) to compare the BRA methods within our proposed framework. RESULTS: Unweighted metrics include the number needed to treat and the number needed to harm. Metrics that incorporate preference weights include those that use maximum acceptable risk, those that use relative-value-adjusted life-years, and those that use quality-adjusted life-years. Metrics that use decision makers' weights include the multicriteria decision analysis, the benefit-less-risk analysis, Boers' 3 by 3 table, the Gail/NCI method, and the transparent uniform risk benefit overview. Most BRA methods can be derived as a special case of a generalized formula in which some are mathematically identical. Numerical comparison of methods highlights potential differences in BRA results and their interpretation. CONCLUSIONS: The proposed framework provides a unified, patient-centered approach to BRA methods classification based on the types of weights that are used across existing methods, a key differentiating feature.
AbstractBackground Long-term adherence to prescription medications for the treatment of chronic disease remains low. While there are many contributors to suboptimal medication use, simple forgetfulness is widely believed to be central. Relatively simple devices may be a particularly cost-efficient and scalable way to promote adherence, however limited data exists about their ability to improve adherence in real-world settings. Methods/design The REMIND trial is a prospective, intent-to-treat randomized control trial to evaluate the impact on medication adherence of three simple, low-cost devices (Take-N-Slide™, the RxTimerCap™, and a standard pillbox). In March 2014, we enrolled 53,480 individuals 18 to 64 years old taking one to three medications to treat chronic disease whose prescription drug benefits were administered by CVS Caremark. The study's primary outcome is optimal adherence over the 12-month period after randomization. Using a randomization ratio of 1:2 between control and each intervention arm, the study has more than 80% power with an alpha of 5% to detect a 1% difference in the rate of optimal adherence between intervention and control groups and across intervention arms. Discussion The REMIND trial is the first randomized study to rigorously evaluate the impact of simple, low-cost reminder devices on medication adherence. The results will inform comparative cost effectiveness studies of reminder systems in improving medication adherence and clinical outcomes.
BACKGROUND: Solid clinical evidence supports the effectiveness and safety of multiple drugs in treating diabetes, dyslipidemia, and hypertension, and numerous fixed-dose combination products (FDCs) containing such drugs have been developed for patients with more severe forms of these diseases. We sought to evaluate the extent to which utilization of treatment combinations for these conditions corresponded to the availability of FDCs. METHODS: Using claims data from a large national commercial insurer, we identified 2 cohorts of patients: those who filled multiple single-agent drugs to treat diabetes, dyslipidemia, and hypertension in 2012, and those who used FDCs containing these products during the same period. We determined the fill rate of single-agent pairs and FDCs, availability of FDCs for the most frequently filled single-agent and drug class pairs, and the number of conditions treated by frequently filled single-agent pairs and FDCs. RESULTS: During our study period, 848,082 patients filled prescriptions for 3,248 unique single-agent pairs (mean 4.7 per patient, standard deviation [SD] 5.0); and 568,923 patients received prescriptions for 43 unique FDCs (mean 1.1 per patient, SD 0.3). Three (15%) of the 20 most frequently filled single-agent pairs were available as FDCs, whereas 9 (45%) of the 20 most frequently filled drug class pairs were available as FDCs. Nearly all of the frequently filled FDCs had lower fill rates than the most frequently filled single-agent pairs. CONCLUSIONS: Utilization of drug combinations to treat cardiovascular conditions does not correspond well with availability of FDCs containing these agents. A concerted set of strategies should be implemented to streamline the development of useful combination products, including expedited approval pathways and increased investment in formulation studies.
BACKGROUND: New regimens for hepatitis C virus (HCV) have shorter treatment durations and increased rates of sustained virologic response compared with existing therapies but are extremely expensive. OBJECTIVE: To evaluate the cost-effectiveness of these treatments under different assumptions about their price and efficacy. DESIGN: Discrete-event simulation. DATA SOURCES: Published literature. TARGET POPULATION: Treatment-naive patients infected with chronic HCV genotype 1, 2, or 3. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. INTERVENTION: Usual care (boceprevir-ribavirin-pegylated interferon [PEG]) was compared with sofosbuvir-ribavirin-PEG and 3 PEG-free regimens: sofosbuvir-simeprevir, sofosbuvir-daclatasvir, and sofosbuvir-ledipasvir. For genotypes 2 and 3, usual care (ribavirin-PEG) was compared with sofosbuvir-ribavirin, sofosbuvir-daclatasvir, and sofosbuvir-ledipasvir-ribavirin (genotype 3 only). OUTCOME MEASURES: Discounted costs (in 2014 U.S. dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. RESULTS OF BASE-CASE ANALYSIS: Assuming sofosbuvir, simeprevir, daclatasvir, and ledipasvir cost $7000, $5500, $5500, and $875 per week, respectively, sofosbuvir-ledipasvir was cost-effective for genotype 1 and cost $12 825 more per QALY than usual care. For genotype 2, sofosbuvir-ribavirin and sofosbuvir-daclatasvir cost $110 000 and $691 000 per QALY, respectively. For genotype 3, sofosbuvir-ledipasvir-ribavirin cost $73 000 per QALY, sofosbuvir-ribavirin was more costly and less effective than usual care, and sofosbuvir-daclatasvir cost more than $396 000 per QALY at assumed prices. RESULTS OF SENSITIVITY ANALYSIS: Sofosbuvir-ledipasvir was the optimal strategy in most simulations for genotype 1 and would be cost-saving if sofosbuvir cost less than $5500. For genotype 2, sofosbuvir-ribavirin-PEG would be cost-saving if sofosbuvir cost less than $2250 per week. For genotype 3, sofosbuvir-ledipasvir-ribavirin would be cost-saving if sofosbuvir cost less than $1500 per week. LIMITATION: Data are lacking on real-world effectiveness of new treatments and some prices. CONCLUSION: From a societal perspective, novel treatments for HCV are cost-effective compared with usual care for genotype 1 and probably genotype 3 but not for genotype 2. PRIMARY FUNDING SOURCE: CVS Health.
PURPOSE: Type 2 diabetes mellitus has reached epidemic proportions worldwide. Many patients with type 2 diabetes mellitus will require insulin, and the evidence-based use of insulin is described in the prescription drug label. Product labels in different countries may provide inconsistent information. We evaluated the variability in drug label content for one brand of basal insulin across diverse settings. METHODS: We examined the drug label content pertinent to effective and safe use of insulin glargine across 17 countries: Abu Dhabi (United Arab Emirates), Argentina, Brazil, Canada, China, Germany, Israel, Italy, Japan, Mexico, Russia, Saudi Arabia, South Korea, Spain, Turkey, UK, and the USA. We compared label characteristics in settings where drug labels were governed by a local regulatory authority versus countries where labels were administered by a regional body or adopted from another locale. RESULTS: All 17 labels cautioned that providers should consider age, illness, diet, and exercise when prescribing. Only two (12%) described care of the fasting patient. Caution was urged for patients with renal or hepatic impairment in 16 (94%) labels. Four (24%) did not describe responses to missed doses, and five (29%) failed to recommend patient counseling about the risk of hypoglycemia. Labels emerging from regional or adopted regulatory bodies reported fewer patients in efficacy studies than did labels from settings with their own drug regulatory agencies (365 +/- 0 patients vs. 3560 +/- 2938, p = 0.04). CONCLUSIONS: There is substantial variation in the content of drug labels for glargine, which may lead to international inconsistency in quality of care for diabetic patients.
Previous reviews have shown that changes in prescription drug insurance benefits can affect medication use and adherence. We conducted a systematic review of the literature to identify studies addressing the association between prescription drug coverage and health outcomes. Studies were included if they collected empirical data on expansions or restrictions of prescription drug coverage and if they reported clinical outcomes. We found 23 studies demonstrating that broader prescription drug insurance reduces use of other health care services and has a positive impact on patient outcomes. Coverage gaps or caps on drug insurance generally led to worse outcomes. States should consider implementing the Affordable Care Act expansions in drug coverage to improve the health of low-income patients receiving state-based health insurance.
BACKGROUND: Primary medication nonadherence (PMN) occurs when patients do not fill new prescriptions. Interventions to reduce PMN have not been well described. OBJECTIVES: To determine whether 2 pharmacy-based interventions could decrease PMN. DESIGN: Two sequential interventions with a control group were evaluated after completion. The automated intervention began in 2007 and consisted of phone calls to patients on the third and seventh days after a prescription was processed but remained unpurchased. The live intervention began in 2009 and used calls from a pharmacist or technician to patients who still had not picked up their prescriptions after 8 days. SUBJECTS: Patients with newly prescribed cardiovascular medications received at CVS community pharmacies. Patients with randomly selected birthdays served as the control population. MEASURES: Patient abandonment of new prescription, defined as not picking up medications within 30 days of initial processing at the pharmacy. RESULTS: The automated intervention included 852,612 patients and 1.2 million prescriptions, with a control group of 9282 patients and 13,178 prescriptions. The live intervention included 121,155 patients and 139,502 prescriptions with a control group of 2976 patients and 3407 prescriptions. The groups were balanced by age, sex, and patterns of prior prescription use. For the automated intervention, 4.2% of prescriptions were abandoned in the intervention group and 4.5% in the control group (P>0.1), with no significant differences for any individual classes of medications. The live intervention was used in a group that had not purchased prescriptions after 8 days and thus had much higher PMN. In this setting 36.9% of prescriptions were abandoned in the intervention group and 41.7% in the control group, a difference of 4.8% (P<0.0001). The difference in abandoned prescriptions for antihypertensives was 6.9% (P<0.0001) but for antihyperlipidemics was only 1.4% (P>0.1). CONCLUSIONS: Automated reminder calls had no effect on PMN. Live calls from pharmacists decreased antihypertensive PMN significantly, although many patients still abandoned their prescriptions.
Background—With proliferating treatment options for anticoagulant therapy, physicians and patients must choose among them based on their benefits and risks. Using a Discrete Choice Experiment, we elicited patients’ relative preferences for specific benefits and risks of anticoagulant therapy.Methods and Results—We selected a sample of US patients with cardiovascular disease from an online panel and elicited their preferences for benefits and risks of anticoagulant therapy: nonfatal stroke, nonfatal myocardial infarction, cardiovascular death, minor bleeding, major bleeding, bleeding death, and need for monitoring. These attributes were used to design scenarios describing hypothetical treatments that were labeled as new drug, old drug, or no drug. Latent class analysis was used to identify groups of patients with similar preferences. A total of 341 patients completed all Discrete Choice Experiment questions. On average, patients valued a 1% increased risk of a fatal bleeding event the same as a 2% increase in nonfatal myocardial infarction, a 3% increase in nonfatal stroke, a 3% increase in cardiovascular death, a 6% increase in major bleeding, and a 16% increase in minor bleeding. The odds of choosing no drug or old drug versus new drug were 0.72 (95% confidence interval, 0.61–0.84) and 0.86 (95% confidence interval, 0.81–0.93), respectively. Previous stroke or myocardial infarction was associated with membership in the class with larger negative preferences for these outcomes.Conclusions—Patients’ preferences for various outcomes of anticoagulant therapy vary and depend on their previous experiences with myocardial infarction or stroke. Incorporating these preferences into benefit risk calculation and treatment decisions can enhance patient-centered care.
Objectives Evaluation of quality of care across retail clinics in a geographically diverse population has not been undertaken to date. We sought to evaluate and compare the quality of care for otitis media, pharyngitis, and urinary tract infection received in retail medical clinics in CVS pharmacies ("MinuteClinics" [MCs]), ambulatory care facilities (ACFs), and emergency departments (EDs). Methods We used 14 measures constructed from RAND Corporation's Quality Assurance Tools and guidelines from the American Academy of Pediatrics, the American Academy of Family Physicians, and the Infectious Diseases Society of America. Our cohort was drawn from Aetna medical and prescription claims, 2009-2012. Members were matched on visit date, condition, and propensity score. Generalized estimating equations were used to compare quality across clinic type, overall, and by index condition. Results We matched 75,886 episodes of care, of which 20,153 were eligible for at least 1 quality measure. MCs performed better than EDs and ACFs in 7 measures. In a multivariable model, MCs performed better than ACFs and EDs across all quality measures ([OR 0.42; 95% CI, 0.40-0.45; P < .0001; ACF vs MC] [OR 0.29; 95% CI, 0.27-0.31; P < .0001; ED vs MC]). Results for each condition were significant at P < .0001. Conclusions Quality of care for these conditions based on widely accepted objective measures was superior in MinuteClinics compared with ACFs and EDs.
Referring patients to other physicians is one of the most fundamental and frequently performed tasks in clinical practice. In 2009, referrals to other physicians were made during almost 1 in 10 ambulatory visits in the United States for a total of more than 100 million referrals.1 Despite the routine nature of referrals, there is significant variation in how and when physicians choose to ask for specialist involvement. Rates of referral appear to vary up to 5-fold, with both overreferral and underreferral being common.2 Decisions about whether to refer appear to be influenced by both patient factors, such as illness severity and expectations, as well as physician training and expertise.2 As a consequence, standardizing and optimizing the referral process may affect the cost and quality of care.3
Importance: Although many classes of oral glucose-lowering medications have been approved for use, little comparative effectiveness evidence exists to guide initial selection of therapy for diabetes mellitus. Objective: To determine the effect of initial oral glucose-lowering agent class on subsequent need for treatment intensification and 4 short-term adverse clinical events. Design, Setting, and Participants: This study was a retrospective cohort study of patients who were fully insured members of Aetna (a large national health insurer) who had been prescribed an oral glucose-lowering medication from July 1, 2009, through June 30, 2013. Individuals newly prescribed an oral glucose-lowering agent who filled a second prescription for a medication in the same class and with a dosage at or above the World Health Organization's defined daily dose within 90 days of the end-of-day's supply of the first prescription were studied. Individuals with interim prescriptions for other oral glucose-lowering medications were excluded. Exposures: Initiation of treatment with metformin, a sulfonylurea, a thiazolidinedione, or a dipeptidyl peptidase 4 inhibitor. Main Outcomes and Measures: Time to addition of a second oral agent or insulin, each component separately, hypoglycemia, other diabetes-related emergency department visits, and cardiovascular events. Results: A total of 15 516 patients met the inclusion criteria, of whom 8964 (57.8%) started therapy with metformin. In unadjusted analyses, use of medications other than metformin was significantly associated with an increased risk of adding a second oral agent only, insulin only, and a second agent or insulin (P < .001 for all). In propensity score and multivariable-adjusted Cox proportional hazards models, initiation of therapy with sulfonylureas (hazard ratio [HR], 1.68; 95% CI, 1.57-1.79), thiazolidinediones (HR, 1.61; 95% CI, 1.43-1.80), and dipeptidyl peptidase 4 inhibitors (HR, 1.62; 95% CI, 1.47-1.79) was associated with an increased hazard of intensification. Alternatives to metformin were not associated with a reduced risk of hypoglycemia, emergency department visits, or cardiovascular events. Conclusions and Relevance: Despite guidelines, only 57.8% of individuals began diabetes treatment with metformin. Beginning treatment with metformin was associated with reduced subsequent treatment intensification, without differences in rates of hypoglycemia or other adverse clinical events. These findings have significant implications for quality of life and medication costs.
Cigarette smoking can make managing chronic diseases more difficult. For instance, in patients with certain respiratory conditions, smoking increases the risk of acute exacerbation, can worsen disease control, and may limit the effectiveness of inhaled corticosteroids.1 Similarly, by raising blood pressure, smoking can make it challenging to effectively control hypertension and may increase the risk of atherosclerosis and coronary heart disease.2 Smoking can also increase the risk of serious adverse drug events. Oral contraceptive (OC) users older than 35 years who smoke have a 9-fold higher risk of myocardial infarction and venous thromboembolism compared with nonsmokers.3,4
Importance Genetic biomarkers that predict a drug’s efficacy or likelihood of toxicity are assuming increasingly important roles in the personalization of pharmacotherapy, but concern exists that evidence that links use of some biomarkers to clinical benefit is insufficient. Nevertheless, information about the use of biomarkers appears in the labels of many prescription drugs, which may add confusion to the clinical decision-making process.Objective To evaluate the evidence that supports pharmacogenomic biomarker testing in drug labels and how frequently testing is recommended.Data Sources Publicly available US Food and Drug Administration databases.Main Outcomes and Measures We identified drug labels that described the use of a biomarker and evaluated whether the label contained or referenced convincing evidence of its clinical validity (ie, the ability to predict phenotype) and clinical utility (ie, the ability to improve clinical outcomes) using guidelines published by the Evaluation of Genomic Applications in Practice and Prevention Working Group. We graded the completeness of the citation of supporting studies and determined whether the label recommended incorporation of biomarker test results in therapeutic decision making.Results Of the 119 drug-biomarker combinations, only 43 (36.1%) had labels that provided convincing clinical validity evidence, whereas 18 (15.1%) provided convincing evidence of clinical utility. Sixty-one labels (51.3%) made recommendations about how clinical decisions should be based on the results of a biomarker test; 36 (30.3%) of these contained convincing clinical utility data. A full description of supporting studies was included in 13 labels (10.9%).Conclusions and Relevance Fewer than one-sixth of drug labels contained or referenced convincing evidence of clinical utility of biomarker testing, whereas more than half made recommendations based on biomarker test results. It may be premature to include biomarker testing recommendations in drug labels when convincing data that link testing to patient outcomes do not exist.
OBJECTIVES:Poor adherence to mesalamine is common and driven by a combination of lifestyle and behavioral factors, as well as health beliefs. We sought to develop a valid tool to identify barriers to patient adherence and predict those at risk for future nonadherence.METHODS:A 10-item survey was developed from patient-reported barriers to adherence. The survey was administered to 106 patients with ulcerative colitis who were prescribed mesalamine, and correlated with prospectively collected 12-month pharmacy refills (medication possession ratio (MPR)), urine levels of salicylates, and self-reported adherence (Morisky Medication Adherence Scale (MMAS)-8).RESULTS:From the initial 10-item survey, 8 items correlated highly with the MMAS-8 score at enrollment. Computer-generated randomization produced a derivation cohort of 60 subjects and a validation cohort of 46 subjects to assess the survey items in their ability to predict future adherence. Two items from the patient survey correlated with objective measures of long-term adherence: their belief in the importance of maintenance mesalamine even when in remission and their concerns about side effects. The additive score based on these two items correlated with 12-month MPR in both the derivation and validation cohorts (P<0.05). Scores on these two items were associated with a higher risk of being nonadherent over the subsequent 12 months (relative risk (RR) =2.2, 95% confidence interval=1.5-3.5, P=0.04). The area under the curve for the performance of this 2-item tool was greater than that of the 10-item MMAS-8 score for predicting MPR scores over 12 months (area under the curve 0.7 vs. 0.5).CONCLUSIONS:Patients' beliefs about the need for maintenance mesalamine and their concerns about side effects influence their adherence to mesalamine over time. These concerns could easily be raised in practice to identify patients at risk of nonadherence (Clinical Trial number NCT01349504).Am J Gastroenterol advance online publication, 10 June 2014; doi:10.1038/ajg.2014.158.
BACKGROUND: Statins are effective in preventing cardiovascular events, but patients do not fully adhere to them. OBJECTIVE: To determine whether patients are more adherent to generic statins versus brand-name statins (lovastatin, pravastatin, or simvastatin) and whether greater adherence improves health outcomes. DESIGN: Observational, propensity score-matched, new-user cohort study. SETTING: Linked electronic data from medical and pharmacy claims. PARTICIPANTS: Medicare beneficiaries aged 65 years or older with prescription drug coverage between 2006 and 2008. INTERVENTION: Initiation of a generic or brand-name statin. MEASUREMENTS: Adherence to statin therapy (measured as the proportion of days covered [PDC] up to 1 year) and a composite outcome comprising hospitalization for an acute coronary syndrome or stroke and all-cause mortality. Hazard ratios (HRs) and absolute rate differences were estimated. RESULTS: A total of 90 111 patients who initiated a statin during the study was identified; 83 731 (93%) initiated a generic drug, and 6380 (7%) initiated a brand-name drug. The mean age of patients was 75.6 years, and most (61%) were female. The average PDC was 77% for patients in the generic group and 71% for those in the brand-name group (P < 0.001). An 8% reduction in the rate of the clinical outcome was observed among patients in the generic group versus those in the brand-name group (HR, 0.92 [95% CI, 0.86 to 0.99]). The absolute difference was -1.53 events per 100 person-years (CI, -2.69 to -0.19 events per 100 person-years). LIMITATION: Results may not be generalizable to other populations with different incomes or drug benefit structures. CONCLUSION: Compared with those initiating brand-name statins, patients initiating generic statins were more likely to adhere and had a lower rate of a composite clinical outcome. PRIMARY FUNDING SOURCE: Teva Pharmaceuticals.
Significant racial/ethnic disparities have been documented in cardiovascular care. Although health care quality is improving for many Americans, differences in clinical outcomes have persisted between racial/ethnic minority patients and non-minorities, even when income, education level, and site of care are taken into consideration. Potential causes of disparities are complex and are related to differences in risk factor prevalence and control, use of evidence-based procedures and medications, and social and environmental factors. Minority patients are more likely to receive care from lower-quality health care providers and institutions and experience more barriers to accessing care. Factors such as stereotyping and bias in medicine are hard to quantify, but likely contribute to differences in treatment. Recent trends suggest that some disparities are decreasing. Opportunities for change and improvement exist for patients, providers, and health care systems. Promising interventions, such as health policy changes, quality improvement programs, and culturally targeted community and clinic-based interventions offer hope that high-quality health care in the USA can be provided to all patients.
OBJECTIVES: We assessed the relationship between individual characteristics and receipt of oseltamivir (Tamiflu) in the United States during the H1N1 pandemic and other flu seasons. METHODS: In a cohort of individuals enrolled in pharmacy benefit plans, we used a multivariate logistic regression model to measure associations between subscriber characteristics and filling a prescription for oseltamivir during 3 flu seasons (October 2006-May 2007, October 2007-May 2008, and October 2008-May 2010). In 19 states with county-level influenza rates reported, we controlled for disease burden. RESULTS: Approximately 56 million subscribers throughout the United States were included in 1 or more study periods. During pandemic flu, beneficiaries in the highest income category had 97% greater odds of receiving oseltamivir than those in the lowest category (P < .001). After we controlled for disease burden, subscribers in the 2 highest income categories had 2.18 and 1.72 times the odds of receiving oseltamivir compared with those in the lowest category (P < .001 for both). CONCLUSIONS: Income was a stronger predictor of oseltamivir receipt than prevalence of influenza. These findings corroborate concerns about equity of treatment in pandemics, and they call for improved approaches to distributing potentially life-saving treatments.
BACKGROUND: Dabigatran, rivaroxaban, and apixaban have been approved for use in patients with atrial fibrillation based upon randomized trials demonstrating their comparable or superior efficacy and safety relative to warfarin. Little is known about their adoption into clinical practice, whether utilization is consistent with the controlled-trials on which their approval was based, and how their use has affected health spending for patients and insurers. STUDY DESIGN: We used medical and prescription claims data from a large insurer to identify patients with non-valvular atrial fibrillation who were prescribed an oral anticoagulant in 2010-2013. We plotted trends in medication initiation over time, assessed corresponding insurer and patient out-of-pocket spending, and evaluated the cumulative number and cost of anticoagulants. We identified predictors of novel anticoagulant initiation using multivariable logistic models. Finally, we estimated the difference in total drug expenditures over 6 months for patients initiating warfarin vs. a novel anticoagulant. RESULTS: 6,893 patients with atrial fibrillation initiated an oral anticoagulant during the study period. By the end of the study period, novel anticoagulants accounted for 62% of new prescriptions and 98% of anticoagulant-related drug costs. Female sex, lower household income and higher CHADS2, CHA2DS2-VASC, and HAS-BLED scores were significantly associated with lower odds of receiving a novel anticoagulant (p<0.001 for each). Average combined patient and insurer anticoagulant spending in the first 6 months after initiation was more than $900 greater for patients initiating a novel anticoagulant. CONCLUSIONS: This study demonstrates rapid adoption of novel anticoagulants into clinical practice, particularly among patients with lower CHADS2 and HAS-BLED scores, and high health care cost consequences. These findings provide important directions for future comparative and cost-effectiveness research.