Variation in Estimated Medicare Prescription Drug Plan Costs and Affordability for Beneficiaries Living in Different States

BACKGROUND: Medicare Part D prescription drug plans (PDPs) implemented in January 2006 are designed to improve beneficiaries’ access to pharmaceuticals and use market competition to yield affordable drug costs. Variations in estimated PDP costs for beneficiaries living in different states have not previously been characterized. OBJECTIVE: To describe variations in the estimated costs of PDPs (plan premium, copays, and coinsurance) within and across states. DESIGN: To estimate PDP costs based on 4 actual patient cases that exemplify common conditions and prescription drug combinations for Medicare beneficiaries, we used the online tool provided by the Centers for Medicare and Medicaid Services. MEASUREMENTS: Principal study outcomes included (a) variation across states in the estimated annual cost of the lowest-cost PDP for each case and (b) variation in the estimated affordability of the lowest-cost PDPs across states, based on cost-of-living-adjusted median income for zero-earner households. RESULTS: For all 4 patient cases, we found substantive within-state and between-state differences in the estimated costs of Medicare PDPs incurred by beneficiaries. The estimated annual costs to beneficiaries of the lowest-cost PDPs varied across states by as much as $320 for medications in the least expensive scenario, and by as much as$13,000 for the most expensive scenario. On average across states, a beneficiary with cost-of-living-adjusted median income would expect to spend 3%–28% of annual income to pay for medications in the lowest-cost PDPs in the 4 patient cases. The affordability of the lowest-cost plans varied across states, and for 2 of the 4 cases the lowest-cost PDP estimates were negatively correlated with cost-of-living-adjusted median income. CONCLUSIONS: Substantive differences in estimated PDP costs are evident across states for patients with common Medicare conditions. Importantly, the lowest-cost plans were not proportionally affordable with respect to state-specific cost-of-living-adjusted median income. Refinement of the Medicare drug program may be needed to improve national balance in PDP affordability for beneficiaries living in different states. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available for this article at http://dx.doi.org/10.1007/s11606-006-0018-y and is accessible for authorized users

The fallacy of enrolling only high-risk subjects in cancer prevention trials: Is there a "free lunch"?

BACKGROUND: There is a common belief that most cancer prevention trials should be restricted to high-risk subjects in order to increase statistical power. This strategy is appropriate if the ultimate target population is subjects at the same high-risk. However if the target population is the general population, three assumptions may underlie the decision to enroll high-risk subject instead of average-risk subjects from the general population: higher statistical power for the same sample size, lower costs for the same power and type I error, and a correct ratio of benefits to harms. We critically investigate the plausibility of these assumptions. METHODS: We considered each assumption in the context of a simple example. We investigated statistical power for fixed sample size when the investigators assume that relative risk is invariant over risk group, but when, in reality, risk difference is invariant over risk groups. We investigated possible costs when a trial of high-risk subjects has the same power and type I error as a larger trial of average-risk subjects from the general population. We investigated the ratios of benefit to harms when extrapolating from high-risk to average-risk subjects. RESULTS: Appearances here are misleading. First, the increase in statistical power with a trial of high-risk subjects rather than the same number of average-risk subjects from the general population assumes that the relative risk is the same for high-risk and average-risk subjects. However, if the absolute risk difference rather than the relative risk were the same, the power can be less with the high-risk subjects. In the analysis of data from a cancer prevention trial, we found that invariance of absolute risk difference over risk groups was nearly as plausible as invariance of relative risk over risk groups. Therefore a priori assumptions of constant relative risk across risk groups are not robust, limiting extrapolation of estimates of benefit to the general population. Second, a trial of high-risk subjects may cost more than a larger trial of average risk subjects with the same power and type I error because of additional recruitment and diagnostic testing to identify high-risk subjects. Third, the ratio of benefits to harms may be more favorable in high-risk persons than in average-risk persons in the general population, which means that extrapolating this ratio to the general population would be misleading. Thus there is no free lunch when using a trial of high-risk subjects to extrapolate results to the general population. CONCLUSION: Unless the intervention is targeted to only high-risk subjects, cancer prevention trials should be implemented in the general population

Selecting patients for randomized trials: a systematic approach based on risk group

BACKGROUND: A key aspect of randomized trial design is the choice of risk group. Some trials include patients from the entire at-risk population, others accrue only patients deemed to be at increased risk. We present a simple statistical approach for choosing between these approaches. The method is easily adapted to determine which of several competing definitions of high risk is optimal. METHOD: We treat eligibility criteria for a trial, such as a smoking history, as a prediction rule associated with a certain sensitivity (the number of patients who have the event and who are classified as high risk divided by the total number patients who have an event) and specificity (the number of patients who do not have an event and who do not meet criteria for high risk divided by the total number of patients who do not have an event). We then derive simple formulae to determine the proportion of patients receiving intervention, and the proportion who experience an event, where either all patients or only those at high risk are treated. We assume that the relative risk associated with intervention is the same over all choices of risk group. The proportion of events and interventions are combined using a net benefit approach and net benefit compared between strategies. RESULTS: We applied our method to design a trial of adjuvant therapy after prostatectomy. We were able to demonstrate that treating a high risk group was superior to treating all patients; choose the optimal definition of high risk; test the robustness of our results by sensitivity analysis. Our results had a ready clinical interpretation that could immediately aid trial design. CONCLUSION: The choice of risk group in randomized trials is usually based on rather informal methods. Our simple method demonstrates that this decision can be informed by simple statistical analyses

Budget impact analysis of rituximab biosimilar in Italy from the hospital and payer perspectives

Introduction: This article aims at investigating the 5-year budget impact of rituximab biosimilars in Italy. Methods: A budget impact analysis model was developed in accordance with the International Society For Pharmacoeconomics and Outcomes Research recommendations. Drug acquisition and drug administration costs were considered since the risk/benefit profile of biosimilars and the originator was assumed to be overlapping. The perspectives of hospitals and payers were used. Input data were retrieved from the literature and validated/integrated by an expert panel of seven clinicians from various Italian regions. A dynamic incidence-based approach was used. Results: From the hospital perspective, adopting a rituximab biosimilar would produce savings of €79.2 and €153.6 million over 3 and 5 years, respectively. The results are very similar if the payer perspective is considered, with a cumulated savings of about €153.4 million in 5 years. Lymphoma and chronic lymphocytic leukaemia would account for the most significant savings. Discussion: Despite its limitations, this study provides the first Italian evaluation of the financial impact of rituximab biosimilars and also incorporates the effects of biosimilars on the pricing strategies of the originator (dynamic impact). This dynamic effect is more relevant than the impact of the treatment shift from the originator to biosimilars. Our hope is that these savings will be used to cover new cost-effective drugs and not just for cost-cutting policies

Improved care of acute exacerbation of chronic obstructive pulmonary disease in two academic emergency departments

Background: Although several chronic obstructive pulmonary disease (COPD) practice guidelines have been published, there is sparse data on the actual emergency department (ED) management of acute exacerbation of COPD (AECOPD). Aims: Our objectives were to examine concordance of ED care of AECOPD in older patients with guideline recommendations and to evaluate whether concordance has improved over time in two academic EDs. Methods: Data were obtained from two cohort studies on AECOPD performed in two academic EDs during two different time periods, 2000 and 2005–2006. Both studies included ED patients, aged 55 and older, who presented with AECOPD, and cases were confirmed by emergency physicians. Data on ED management and disposition were obtained from chart review for both cohorts. Results: The analysis included 272 patients: 72 in the 2000 database and 200 in the 2005–2006 database. The mean age of the patients was 72 years; 50% were women and 80% white. In 2005–2006, overall concordance with guideline recommendations was high (for chest radiography, pulse oximetry, bronchodilators, all ≥ 90%), except for arterial blood gas testing (7% among the admitted) and discharge medication with systemic corticosteroids (42%). Compared to the 2000 data, the use of systemic corticosteroids in the ED improved from 53 to 77% [absolute improvement: 24%, 95% confidence interval (CI): 11–37%], and the use of antibiotics among the patients with respiratory infection symptoms improved from 56 to 78% (absolute improvement: 22%, 95% CI: 6–38%). Conclusions: Overall concordance with guideline-recommended care for AECOPD was high in two academic EDs, and some emergency treatments have improved over time

Get screened: a pragmatic randomized controlled trial to increase mammography and colorectal cancer screening in a large, safety net practice

Abstract Background Most randomized controlled trials of interventions designed to promote cancer screening, particularly those targeting poor and minority patients, enroll selected patients. Relatively little is known about the benefits of these interventions among unselected patients. Methods/Design "Get Screened" is an American Cancer Society-sponsored randomized controlled trial designed to promote mammography and colorectal cancer screening in a primary care practice serving low-income patients. Eligible patients who are past due for mammography or colorectal cancer screening are entered into a tracking registry and randomly assigned to early or delayed intervention. This 6-month intervention is multimodal, involving patient prompts, clinician prompts, and outreach. At the time of the patient visit, eligible patients receive a low-literacy patient education tool. At the same time, clinicians receive a prompt to remind them to order the test and, when appropriate, a tool designed to simplify colorectal cancer screening decision-making. Patient outreach consists of personalized letters, automated telephone reminders, assistance with scheduling, and linkage of uninsured patients to the local National Breast and Cervical Cancer Early Detection program. Interventions are repeated for patients who fail to respond to early interventions. We will compare rates of screening between randomized groups, as well as planned secondary analyses of minority patients and uninsured patients. Data from the pilot phase show that this multimodal intervention triples rates of cancer screening (adjusted odds ratio 3.63; 95% CI 2.35 - 5.61). Discussion This study protocol is designed to assess a multimodal approach to promotion of breast and colorectal cancer screening among underserved patients. We hypothesize that a multimodal approach will significantly improve cancer screening rates. The trial was registered at Clinical Trials.gov NCT00818857http://deepblue.lib.umich.edu/bitstream/2027.42/78264/1/1472-6963-10-280.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78264/2/1472-6963-10-280.pdfPeer Reviewe

Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

<p>Abstract</p> <p>Background</p> <p>Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome.</p> <p>Methods</p> <p>Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data.</p> <p>Results</p> <p>Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET.</p> <p>Conclusions</p> <p>The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.</p

The effect on survival of continuing chemotherapy to near death

<p>Abstract</p> <p>Background</p> <p>Overuse of anti-cancer therapy is an important quality-of-care issue. An aggressive approach to treatment can have negative effects on quality of life and cost, but its effect on survival is not well-defined.</p> <p>Methods</p> <p>Using the Surveillance, Epidemiology, and End Results-Medicare database, we identified 7,879 Medicare-enrolled patients aged 65 or older who died after having survived at least 3 months after diagnosis of advanced non-small cell lung cancer (NSCLC) between 1991 and 1999. We used Cox proportional hazards regression analysis, propensity scores, and instrumental variable analysis (IVA) to compare survival among patients who never received chemotherapy (n = 4,345), those who received standard chemotherapy but not within two weeks prior to death (n = 3,235), and those who were still receiving chemotherapy within 14 days of death (n = 299). Geographic variation in the application of chemotherapy was used as the instrument for IVA.</p> <p>Results</p> <p>Receipt of chemotherapy was associated with a 2-month improvement in overall survival. However, based on three different statistical approaches, no additional survival benefit was evident from continuing chemotherapy within 14 days of death. Moreover, patients receiving chemotherapy near the end of life were much less likely to enter hospice (81% versus 51% with no chemotherapy and 52% with standard chemotherapy, P < 0.001), or were more likely to be admitted within only 3 days of death.</p> <p>Conclusions</p> <p>Continuing chemotherapy for advanced NSCLC until very near death is associated with a decreased likelihood of receiving hospice care but not prolonged survival. Oncologists should strive to discontinue chemotherapy as death approaches and encourage patients to enroll in hospice for better end-of-life palliative care.</p