BACKGROUND: With rising health spending, predicting costs is essential to identify patients for interventions. Many of the existing approaches have moderate predictive ability, which may result, in part, from not considering potentially meaningful changes in spending over time. Group-based trajectory modeling could be used to classify patients into dynamic long-term spending patterns. OBJECTIVES: To classify patients by their spending patterns over a 1-year period and to assess the ability of models to predict patients in the highest spending trajectory and the top 5% of annual spending using prior-year predictors. SUBJECTS: We identified all fully insured adult members enrolled in a large US nationwide insurer and used medical and prescription data from 2009 to 2011. RESEARCH DESIGN: Group-based trajectory modeling was used to classify patients by their spending patterns over a 1-year period. We assessed the predictive ability of models that categorized patients in the top fifth percentile of annual spending and in the highest spending trajectory, using logistic regression and split-sample validation. Models were estimated using investigator-specified variables and a proprietary risk-adjustment method. RESULTS: Among 998,651 patients, in the best-performing model, prediction was strong for patients in the highest trajectory group (C-statistic: 0.86; R: 0.47). The C-statistic of being in the top fifth percentile of spending in the best-performing model was 0.82 (R: 0.26). Approaches using nonproprietary investigator-specified methods performed almost as well as other risk-adjustment methods (C-statistic: 0.81 vs. 0.82). CONCLUSIONS: Trajectory modeling may be a useful way to predict costly patients that could be implementable by payers to improve cost-containment efforts.
DESCRIPTION: The discrepancy between health care spending and achieved outcomes in the United States has fueled efforts to identify and address situations where unnecessarily expensive therapies are used when less costly, equally effective options are available. The underuse of generic medications is an important example. METHODS: A literature review was conducted to answer 5 questions about generic medications: 1) How commonly are brand-name medications used when a generic version is available? 2) How does the use of generic medications influence adherence? 3) What is the evidence that brand-name and generic medications have similar clinical effects? 4) What are the barriers to increasing the use of generic medications? 5) What strategies can be used to promote cost savings through greater generic medication use? This article was reviewed and approved by the American College of Physicians Clinical Guidelines Committee. BEST PRACTICE ADVICE: Clinicians should prescribe generic medications, if possible, rather than more expensive brand-name medications.
The potential of short message system (SMS) text messaging and other mobile-phone based methods (collectively often called "mHealth") to engage patients in their own health care has been met with great enthusiasm because of the relatively low cost, transportability, and widespread use of these technologies - more than six billion people worldwide have access to mobile phones.1 By providing reminders and enhancing communication and interaction with healthcare professionals, there is compelling evidence for patients with HIV/AIDS that mHealth can improve adherence to medications and suppress viral loads.2-4.
BACKGROUND: Patient-physician communication often occurs outside the clinic setting; many institutions discourage electronic communication outside of established electronic health record systems. Little empirical data are available on patient interest in electronic communication and Web-based health tools that are technically feasible but not widely available. RESEARCH OBJECTIVE: To explore patient behavior and interest in using the Internet to contact physicians. DESIGN: National cross-sectional online survey. PARTICIPANTS: A sample of 4,510 CVS customers with at least one chronic condition in the household was used to target patients with chronic conditions and their caregivers. Subjects were identified from a national panel of over 100,000 retail pharmacy customers. Of those sampled, 2,252 responded (50.0 % response rate). MAIN MEASURES: Survey measures included demographic and health information, patient use of email and Facebook to contact physicians, and patient interest in and use of Web-based tools for health. KEY RESULTS: A total of 37 % of patients reported contacting their physicians via email within the last six months, and 18 % via Facebook. Older age was negatively associated with contacting physicians using email (OR 0.57 [95 % CI 0.41-0.78]) or Facebook (OR 0.28 [0.17-0.45]). Non-white race (OR 1.61 [1.18-2.18] and OR 1.82 [1.24-2.67]) and caregiver status (OR 1.58 [1.27-1.96] and OR 1.71 [1.31- 2.23]) were positively associated with using email and Facebook, respectively. Patients were interested in using Web-based tools to fill prescriptions, track their own health, and access health information (37-57 %), but few were currently doing so (4-8 %). CONCLUSIONS: In this population of retail pharmacy users, there is strong interest among patients in the use of email and Facebook to communicate with their physicians. The findings highlight the gap between patient interest for online communication and what physicians may currently provide. Improving and accelerating the adoption of secure Web messaging systems is a possible solution that addresses both institutional concerns and patient demand.
OBJECTIVE: Several trials suggest that triple therapy (methotrexate, sulfasalazine, and hydroxychloroquine) and biologic disease-modifying antirheumatic drugs (bDMARD) have similar efficacy in rheumatoid arthritis (RA). We investigated intensification to triple therapy after initial non-biologic (nbDMARD) prescription among patients with RA. METHODS: We used US insurance claims data to evaluate triple therapy use from 2009-2014. Patients with a visit for RA and initial nbDMARD prescription were included. Frequencies and rates to intensification to triple therapy or bDMARD were calculated. We evaluated whether sociodemographic, temporal, geographic, clinical, and healthcare utilization factors were associated with triple therapy intensification using Cox regression. Among those who intensified therapy, we investigated factors associated with triple therapy use by logistic regression. RESULTS: There were 24,576 patients initially with mean age of 50.3 (SD 12.3) years, and 78% were female. During the study period, 2,739 (11.1%) intensified treatment to bDMARD compared to 181 (0.7%) who intensified to triple therapy. There was no significant change in triple therapy use across calendar years. Patients who intensified to triple therapy were more likely to use glucocorticoids (HR 1.91, 95%CI 1.41-2.60) compared to no glucocorticoids and more likely to use nonsteroidal anti-inflammatory drugs (NSAID, HR 1.48, 95%CI 1.10-1.99) compared to no NSAID use within 180 days of initial nbDMARD prescription. Among those who intensified treatment to triple therapy or bDMARD, significant associations for triple therapy use included older age, US region (highest odds for triple therapy use in the West, lowest odds for triple therapy use in the Northeast), glucocorticoid use, and lower number of outpatient visits within 180 days of initial nbDMARD prescription. CONCLUSION: Despite reports published during the study period suggesting equivalent efficacy of triple therapy and bDMARDs for RA, the use of triple therapy was infrequent and did not increase over time in this large nationwide study. This article is protected by copyright. All rights reserved.
OBJECTIVE: Despite the proliferation of databases with increasingly rich patient data, prediction of medication adherence remains poor. We proposed and evaluated approaches for improved adherence prediction. DATA SOURCES: We identified Medicare beneficiaries who received prescription drug coverage through CVS Caremark and initiated a statin. STUDY DESIGN: A total of 643 variables were identified at baseline from prior claims and linked Census data. In addition, we identified three postbaseline predictors, indicators of adherence to statins during each of the first 3 months of follow-up. We estimated 10 models predicting subsequent adherence, using logistic regression and boosted logistic regression, a nonparametric data-mining technique. Models were also estimated within strata defined by the index days supply. RESULTS: In 77,703 statin initiators, prediction using baseline variables only was poor with maximum cross-validated C-statistics of 0.606 and 0.577 among patients with index supply 30 days, respectively. Using only indicators of initial statin adherence improved prediction accuracy substantially among patients with shorter initial dispensings (C = 0.827/0.518), and, when combined with investigator-specified variables, prediction accuracy was further improved (C = 0.842/0.596). CONCLUSIONS: Observed adherence immediately after initiation predicted future adherence for patients whose initial dispensings were relatively short.
OBJECTIVE: To explore the association between unexpected potentially disruptive life events in a patient or family member that may challenge an individual's ability to take medications as prescribed and the discontinuation of evidence-based medications for common, chronic conditions. Understanding the relationship between medication adherence and life stressors, especially those that can be identified using administrative data, may help identify patients at risk of non-adherence. DESIGN: Observational self-controlled case-crossover design. SETTING: Individuals in a nationally representative US commercial health insurance database. PARTICIPANTS: Adult individuals who initiated an oral hypoglycaemic, antihypertensive and/or statin and subsequently stopped the medication for >/=90 days. MAIN OUTCOME MEASURE: Potentially disruptive life events among patients and their family members measured in the 30 days just before the medication was discontinued ('hazard period') compared with the 30 days before this period ('control period'). These events included personal injury, hospitalisation, emergency room visits, changes in insurance coverage, acute stress or acute anxiety. RESULTS: Among the 326 519 patients meeting study criteria who discontinued their chronic disease medications, 88 896 (27.2%) experienced at least one potentially disruptive life event. Newly experiencing an injury (OR: 1.26, 95% CI 1.12 to 1.42), an emergency room visit (OR: 1.19, 95% CI 1.13 to 1.26) and acute stress (OR: 1.19, 95% CI 1.08 to 1.31) were associated with discontinuation. Life events among patients' family members did not appear to be associated with medication discontinuation or occurred less frequently just prior to discontinuation. CONCLUSIONS: Potentially disruptive life events among individuals identified using routinely collected claims data are associated with discontinuation of chronic disease medications. Awareness of these events may help providers or payers identify patients at risk of non-adherence to maximise patient outcomes.
Background Approximately half of patients with chronic cardiometabolic conditions are nonadherent with their prescribed medications. Interventions to improve adherence have been only modestly effective because they often address single barriers to adherence, intervene at single points in time, or are imprecisely targeted to patients who may not need adherence assistance. Objective To evaluate the effect of a multicomponent, behaviorally tailored pharmacist-based intervention to improve adherence to medications for diabetes, hypertension, and hyperlipidemia. Trial design The STIC2IT trial is a cluster-randomized pragmatic trial testing the impact of a pharmacist-led multicomponent intervention that uses behavioral interviewing, text messaging, mailed progress reports, and video visits. Targeted patients are those who are nonadherent to glucose-lowering, antihypertensive, or statin medications and who also have evidence of poor disease control. The intervention is tailored to patients' individual health barriers and their level of health activation.We cluster-randomized 14 practice sites of a large multispecialty group practice to receive either the pharmacist-based intervention or usual care. STIC2IT has enrolled 4,076 patients who will be followed up for 12 months after randomization. The trial's primary outcome is medication adherence, assessed using pharmacy claims data. Secondary outcomes are disease control and health care resource utilization. Conclusion This trial will determine whether a technologically enabled, behaviorally targeted pharmacist-based intervention results in improved adherence and disease control. If effective, this strategy could be a scalable method of offering tailored adherence support to those with the greatest clinical need.
Prescription opioid misuse is a major public health issue in the United States. Since the late 1990s, sales of prescription opioids have risen 4-fold, and the rates of admissions for substance use treatment and of death from opioid overdose have grown proportionately.1 In response, training programs about the appropriate prescribing of opioid therapy have been developed, prescription monitoring programs implemented, and access to naloxone facilitated to reduce deaths among people who overdose. In general, these strategies focus on detecting and preventing harm in those who are already dependent on or misusing opioids. Although the impact of many of these programs is uncertain, the opioid epidemic continues to grow.
OBJECTIVES: The burden of visiting pharmacies to fill medications is a central contributor to nonadherence to maintenance medications.Recently, pharmacies have begun offering services that align prescription fill dates to allow patients to pick up all medications on a single visit. We evaluated the prevalence and structure of synchronization programs and evidence of their impact on adherence and clinical outcomes.STUDY DESIGN: Mixed-methods approach consisting of semistructured interviews, data from surveillance activities, and a systematic literature review. METHODS: We conducted interviews with opinion leaders from nonprofit advocacy organizations and exemplary synchronization programs. Program prevalence was determined using data from regular surveillance efforts. A literature review included Medline,EMBASE, Google Scholar, and general Internet searches.RESULTS: Synchronization programs exist in approximately 10%of independent, 6% of stand-alone chain, and 11% of retail store pharmacies. The majority of programs include a monthly pharmacist appointment and reminder communication. Programs reported the importance of pharmacist buy-in, technology to track and recruit patients, links to other healthcare services, and flexible solutions for managing costs and communication preferences.Although existing peer-reviewed literature suggests that synchronization improves adherence, more evidence is needed to evaluate its impact on patient-centered outcomes.CONCLUSIONS: As medication synchronization programs shift directions and compete for patients and payer resources, it will be more important than ever to rigorously evaluate their ability to improve clinical outcomes while also providing the growing number of patients managing multiple chronic conditions with the highest level of patient engagement and consumer choice.
BACKGROUND: Medicaid programs face growing pressure to control spending. Despite evidence of clinical harms, states continue to impose policies limiting the number of reimbursable prescriptions (caps). We examined the recent use of prescription caps by Medicaid programs and the impact of policy implementation on prescription utilization. METHODS: We identified Medicaid cap policies from 2001-2010. We classified caps as applying to all prescriptions (overall caps) or only branded prescriptions (brand caps). Using state-level, aggregate prescription data, we developed interrupted time-series analyses to evaluate the impact of implementing overall caps and brand caps in a subset of states with data available before and after cap initiation. For overall caps, we examined the use of essential medications, which were classified as preventive or as providing symptomatic benefit. For brand caps, we examined the use of all branded drugs as well as branded and generic medications among classes with available generic replacements. RESULTS: The number of states with caps increased from 12 in 2001 to 20 in 2010. Overall cap implementation (n = 3) led to a 0.52 % (p < 0.001) annual decrease in the proportion of essential prescriptions but no change in cost. For preventive essential medications, overall caps led to a 1.12 % (p = 0.001) annual decrease in prescriptions (246,000 prescriptions annually) and a 1.20 % (p < 0.001) decrease in spending (-$12.2 million annually), but no decrease in symptomatic essential medication use. Brand cap implementation (n = 6) led to an immediate 2.29 % (p = 0.16) decrease in branded prescriptions and 1.26 % (p = 0.025) decrease in spending. For medication classes with generic replacements, the decrease in branded prescriptions (0.74 %, p = 0.003) approximately equaled the increase in generics (0.79 %, p = 0.009), with estimated savings of $17.4 million. CONCLUSIONS: An increasing number of states are using prescription caps, with mixed results. Overall caps decreased the use of preventive but not symptomatic essential medications, suggesting that patients assign higher priority to agents providing symptomatic benefit when faced with reimbursement limits. Among medications with generic replacements, brand caps shifted usage from branded drugs to generics, with considerable savings. Future research should analyze the patient-level impact of these policies to measure clinical outcomes associated with these changes.
OBJECTIVE: The objective of this study was to compare treatment persistence and rates of seizure-related events in patients who initiate antiepileptic drug (AED) therapy with a generic versus a brand-name product. METHODS: We used linked electronic medical and pharmacy claims data to identify Medicare beneficiaries who initiated one of five AEDs (clonazepam, gabapentin, oxcarbazepine, phenytoin, zonisamide). We matched initiators of generic versus brand-name versions of these drugs using a propensity score that accounted for demographic, clinical, and health service utilization variables. We used a Cox proportional hazards model to compare rates of seizure-related emergency room (ER) visit or hospitalization (primary outcome) and ER visit for bone fracture or head injury (secondary outcome) between the matched generic and brand-name initiators. We also compared treatment persistence, measured as time to first 14-day treatment gap, between generic and brand-name initiators. RESULTS: We identified 19,760 AED initiators who met study eligibility criteria; 18,306 (93%) initiated a generic AED. In the matched cohort, we observed 47 seizure-related hospitalizations and ER visits among brand-name initiators and 31 events among generic initiators, corresponding to a hazard ratio of 0.53 (95% confidence interval, 0.30 to 0.96). Similar results were observed for the secondary clinical endpoint and across sensitivity analyses. Mean time to first treatment gap was 124.2days (standard deviation [sd], 125.8) for brand-name initiators and 137.9 (sd, 148.6) for generic initiators. SIGNIFICANCE: Patients who initiated generic AEDs had fewer adverse seizure-related clinical outcomes and longer continuous treatment periods before experiencing a gap than those who initiated brand-name versions.
Cardiovascular disease (CVD) is the second leading cause of mortality worldwide, accounting for 17 million deaths in 2013. More than 80% of these cases were in low- and middle-income countries (LMICs). Although the risk factors for the development of CVD are similar throughout the world, the evolving change in lifestyle and health behaviours in LMICs-including tobacco use, decreased physical activity, and obesity-are contributing to the escalating presence of CVD and mortality. Although CVD mortality is falling in high-income settings because of more effective preventive and management programs, access to evidence-based interventions for combating CVD in resource-limited settings is variable. The existing pressures on both human and financial resources impact the efforts of controlling CVD. The implementation of emerging innovative interventions to improve medication adherence, introducing m-health programs, and decentralizing the management of chronic diseases are promising methods to reduce the burden of chronic disease management on such fragile health care systems.
Objectives: Minority patients have lower rates of cardiovascularmedication adherence, which may be amenable to co-payment reductions.Our objective was to evaluate the effect of race on adherencechanges following a statin co-payment reduction intervention.Study Design: Retrospective analysis.Methods: The intervention was implemented by a large selfinsuredemployer. Eligible individuals in the intervention cohort(n = 1961) were compared with a control group of employees ofother companies without such a policy (n = 37,320). As a proxy forrace, we categorized patients into tertiles based on the proportionof black residents living in their zip code of residence. Analyseswere performed using difference-in-differences design with generalizedestimating equations.Results: Prior to the new co-payment policy, adherence rateswere higher for individuals living in areas with fewer black residents.In multivariable models adjusting for demographic factors,clinical covariates and baseline trends, the co-payment reductionincreased adherence by 2.0% (P = .14), 2.1% (P = .15) and 6% (P<.0001) for intervention patients living in areas with the bottom,middle and top tertiles of the proportion of black residents. Theseresults persisted after adjusting for income.Conclusions: Co-payment reduction for statins preferentiallyimproved adherence among patients living in communities witha higher proportion of black residents. Further research is neededon the impact of value-based insurance design programs onreducing racial disparities in cardiovascular care.
PURPOSE: Trajectory models have been shown to (1) identify groups of patients with similar patterns of medication filling behavior and (2) summarize the trajectory, the average adherence in each group over time. However, the association between adherence trajectories and clinical outcomes remains unclear. This study investigated the association between 12-month statin trajectories and subsequent cardiovascular events. METHODS: We identified patients with insurance coverage from a large national insurer who initiated a statin during January 1, 2007 to December 31, 2010. We assessed medication adherence during the 360 days following initiation and grouped patients based on the proportion of days covered (PDC) and trajectory models. We then measured cardiovascular events during the year after adherence assessment. Cox proportional hazards models were used to evaluate the association between adherence measures and cardiovascular outcomes; strength of association was quantified by the hazard ratio, the increase in model C-statistic, and the net reclassification index (NRI). RESULTS: Among 519 842 statin initiators, 8777 (1.7%) had a cardiovascular event during follow-up. More consistent medication use was associated with a lower likelihood of clinical events, whether adherence was measured through trajectory groups or PDC. When evaluating the prediction of future cardiovascular events by including a measure of adherence in the model, the best model reclassification was observed when adherence was measured using three or four trajectory groups (NRI = 0.189; 95% confidence interval: [0.171, 0.210]). CONCLUSIONS: Statin adherence trajectory predicted future cardiovascular events better than measures categorizing PDC. Thus, adherence trajectories may be useful for targeting adherence interventions. Copyright (c) 2015 John Wiley & Sons, Ltd.
OBJECTIVES: Automatic prescription refill programs are a popular means of improving medication adherence. A concern is the potential for prescription drug wastage and unnecessary healthcare spending. We evaluated the impact of an automatic refill program on patterns of medication use. STUDY DESIGN: Retrospective propensity score matched cohort study with multivariable generalized linear modeling. METHODS: The setting of the study was a pharmacy benefit manager administering benefits for patients of retail pharmacies. Participants included patients on medication for chronic conditions; those receiving a 30-day supply (n = 153,964) and a 90-day supply (n = 100,394) were analyzed separately. The intervention was the automatic prescription refill program. Measures included medication possession ratio (MPR) and average days excess at the time of refill. The results are reported across 11 therapeutic classes. RESULTS: Overall, patients receiving 30-day supplies of medication in the automatic refill program had an MPR that was 3 points higher than those not in the refill program; among those receiving 90-day fills and in the refill program, the MPR was 1.4 points higher (P < .001 for both 30- and 90-day fills). The MPR was higher for members in the refill program across all therapeutic classes. Limiting our analysis to members receiving more than 365 days of medication, we found that patients who received 30-day fills and enrolled in the automatic refill program had 2.5 fewer days' oversupply than those in the control group, whereas automatic refill patients receiving 90-day supplies had 2.18 fewer days' oversupply than the controls (P < .001 for both 30- and 90-day fills). CONCLUSIONS: For this pharmacy provider, automatic refill programs result in improved adherence without adding to medication oversupply.
BACKGROUND: Adherence to drugs that are prescribed after myocardial infarction remains suboptimal. Although eliminating patient cost sharing for secondary prevention increases adherence and reduces rates of major cardiovascular events, the long-term clinical and economic implications of this approach have not been adequately evaluated. METHODS AND RESULTS: We developed a Markov model simulating a hypothetical cohort of commercially insured patients who were discharged from the hospital after myocardial infarction. Patients received beta-blockers, renin-angiotensin system antagonists, and statins without cost sharing (full coverage) or at the current level of insurance coverage (usual coverage). Model inputs were extracted from the Post Myocardial Infarction Free Rx Event and Economic Evaluation trial and other published literature. The main outcome was an incremental cost-effectiveness ratio as measured by cost per quality-adjusted life year gained. Patients receiving usual coverage lived an average of 9.46 quality-adjusted life years after their event and incurred costs of $171,412. Patients receiving full coverage lived an average of 9.60 quality-adjusted life years and incurred costs of $167,401. Compared with usual coverage, full coverage would result in greater quality-adjusted survival (0.14 quality-adjusted life years) and less resource use ($4011) per patient. Our results were sensitive to alterations in the risk reduction for post-myocardial infarction events from full coverage. CONCLUSIONS: Providing full prescription drug coverage for evidence-based pharmacotherapy to commercially insured post-myocardial infarction patients has the potential to improve health outcomes and save money from the societal perspective over the long-term. CLINICAL TRIAL REGISTRATION INFORMATION: https://www.clinicaltrials.gov. Unique identifier: NCT00566774.
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.
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.
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.