Effects of the valsartan recall on heart failure patients: A nationwide analysis.

BACKGROUND: Valsartan is commonly used for cardiac conditions. In 2018, the Food and Drug Administration recalled generic valsartan due to the detection of impurities. Our objective was to determine if heart failure patients receiving valsartan at the recall date had a greater likelihood of unfavorable outcomes than patients using comparable antihypertensives. METHODS: We conducted a cohort study of Optum's de-identified Clinformatics® Datamart (July 2017-January 2019). Heart failure patients with commercial or Medicare Advantage insurance who received valsartan were compared to persons who received non-recalled angiotensin receptor blockers (ARBs) and angiotensin converting enzyme-inhibitors (ACE-Is) for 1 year prior and including the recall date. Outcomes included a composite for all-cause hospitalization, emergency department (ED), and urgent care (UC) use and a measure of cardiac events which included hospitalizations for acute myocardial infarction and hospitalizations/ED/UC visits for stroke/transient ischemic attack, heart failure or hypertension at 6-months post-recall. Cox proportional hazard models with propensity score weighting compared the risk of outcomes between groups. RESULTS: Of the 87 130 adherent patients, 15% were valsartan users and 85% were users of non-recalled ARBs/ACE-Is. Valsartan use was not associated with an increased risk of all-cause hospitalization/ED/UC use six-months post-recall (HR 1.00; 95% CI 0.96-1.03), compared with individuals taking non-recalled ARBs/ACE-Is. Similarly, cardiac events 6-months post-recall did not differ between individuals on valsartan and non-recalled ARBs/ACE-Is (HR 1.04; 95% CI 0.97-1.12). CONCLUSIONS: The valsartan recall did not affect short-term outcomes of heart failure patients. However, the recall potentially disrupted the medication regimens of patients, possibly straining the healthcare system.

Prevalence and patterns of catastrophic spending for antidiabetic medication in 2020.

BACKGROUND: Medication costs for antidiabetic drugs have risen significantly in the United States, causing concerns about the affordability of these essential treatments. OBJECTIVE: To examine out-of-pocket spending for antidiabetic medication and evaluate what proportion of Americans reach catastrophic spending levels during the year. METHODS: This retrospective cohort analysis of nationally representative data from the 2020 Medical Expenditure Panel Survey (MEPS) was analyzed for respondents that reported a diabetes diagnosis. Prescription drug costs were identified from the MEPS Prescribed Medicines File, which included both total prescription payment and out-of-pocket payment for each medication fill. Catastrophic spending thresholds were evaluated based on the World Health Organization's definition, which is spending greater than 40% of a household's nonsubsistence income on health care payments. Statistical analysis was performed with Stata 17 and sample weights were applied adjusting for the MEPS complex survey design to produce national estimates. Descriptive statistics were reported as weighted counts and percentages for categorical variables and as medians with interquartile range for continuous variables. Comparisons of reaching catastrophic spending thresholds across study variables were evaluated with Pearson chi-square tests. A P value less than 0.05 was considered statistically significant in this study. RESULTS: The study included data from a weighted US population of 29.5 million Americans with diabetes. Among this group, 23.8 million (81%) reported use of a prescription medication to treat diabetes. Total reported out-of-pocket payments paid by the patient for antidiabetic medication surpassed $5.2 billion with the largest portion attributable to the insulin subclass, which accounted for 42% or $2.2 billion. The data suggest an estimated 3 million Americans (10.3%) experienced out-of-pocket spending for antidiabetic drugs that reached catastrophic spending thresholds in 2020. CONCLUSIONS: Affordability of prescribed medication in community-dwelling persons with diabetes remains a significant challenge for many Americans.

Trends in prescription drug utilization and spending for the Department of Defense, 2002-2007.

OBJECTIVE: Examine trends in U.S. Department of Defense (DoD) outpatient drug spending and utilization between 2002 and 2007. METHODS: We analyzed pharmacy claims data from the U.S. Military Health System (MHS), using a cross-sectional analysis at the prescription and patient-year level and measuring utilization in 30-day equivalent prescriptions and expenditures in dollars. RESULTS: Pharmaceutical spending more than doubled in DoD, from $3 billion in FY02 to $6.5 billion in FY07. The largest increase occurred in the DoD community pharmacy network, where utilization grew from 6 million 30-day equivalent prescriptions in the first quarter of FY02 to more than 16 million in the last quarter of FY07. The smallest increase in annual spending occurred in FY07 (5.5%), down from a high of 27.5% in FY03. CONCLUSIONS: The MHS has experienced rapid growth in pharmaceutical spending since FY02. However, there are signs that growth in pharmaceutical spending may be slowing.

Follow-on biologics: competition in the biopharmaceutical marketplace.

OBJECTIVE: To describe the implications of a follow-on biologic approval process with focus on current stakeholders, implications of the status quo, and recommendations for future policy. DATA SOURCES: A search using Medline, International Pharmaceutical Abstracts, Med Ad News, F-D-C Reports/Pink Sheets, and Google index directories was conducted with terms such as biologic, biopharmaceutical, generic, and follow-on. STUDY SELECTION: Articles pertaining to the follow-on biologic debate. DATA EXTRACTION: By the authors. DATA SYNTHESIS: Over the past decade, the biopharmaceutical market has experienced substantial growth in the number of product approvals and sales. In contrast with prescription medications, biologic agents currently lack an abbreviated regulatory approval process. Evidence from the Drug Price Competition and Patent Term Restoration Act of 1984 suggests that reducing barriers to generic competition in the pharmaceutical market successfully increases generic market penetration and reduces overall prices to consumers. Although scientific and regulatory dissimilarities between biopharmaceuticals and other medications exist, a follow-on biologic approval process has the potential to play an important role in containing growth in pharmaceutical spending. In addition to biopharmaceutical and generic biopharmaceutical manufacturers, stakeholders with a vested interest in this debate include individual consumers who continue to bear the burden of spending increases in the pharmaceutical market. CONCLUSION: The debate over a follow-on process likely will be difficult as parties seek a balance between incentives for biopharmaceutical innovation, consumer safety, and affordability of existing biologic products.

A comparison of comorbidity measurements to predict healthcare expenditures.

OBJECTIVE: To compare the performance of the Elixhauser, Charlson, and RxRisk-V comorbidity indices and several simple count measurements, including counts of prescriptions, physician visits, hospital claims, unique prescription classes, and diagnosis clusters. STUDY DESIGN: Each measurement was calculated using claims data during a 1-year period before the initial filling of an antihypertensive medication among 20 378 members of a managed care organization. The primary outcome variable was the log-transformed sum of prescription, physician, and hospital expenditures in the year following the prescription encounter. METHODS: In addition to descriptive statistics and Spearman rank correlations between measurements, the predictive performance was determined using linear regression models and corresponding adjusted R(2) statistics. RESULTS: The Charlson index and the Elixhauser index performed similarly (adjusted R(2) = 0.1172 and 0.1148, respectively), while the prescription claims-based RxRisk-V (adjusted R(2) = 0.1573) outperformed both. An age- and gender-adjusted regression model that included a count of diagnosis clusters was the best individual predictor of payments (adjusted R(2) = 0.1814). This outperformed age- and gender-adjusted models of the number of unique prescriptions filled (adjusted R(2) = 0.1669), number of prescriptions filled (R(2) = 0.1573), number of physician visits (adjusted R(2) = 0.1546), logtransformed prior healthcare payments (adjusted R(2) = 0.1359), and number of hospital claims (adjusted R(2) = 0.1115). CONCLUSION: Simple count measurements appear to be better predictors of future expenditures than the comorbidity indices, with a count of diagnosis clusters being the single best predictor of future expenditures among the measurements examined.

Patterns and predictors of prescription medication use in the management of headache: findings from the 2000 Medical Expenditure Panel Survey.

OBJECTIVE: The primary objectives were to examine national trends of prescription medication use for headache and explore patterns of variation in the use of these medications across social and demographic levels. BACKGROUND: Despite widespread use of prescription medication for management of headache, little is known about utilization patterns or patient characteristics associated with receiving this type of treatment. METHODS: This study conducted a secondary analysis of data obtained during the 2000 Medical Expenditure Panel Survey, a representative survey of the U.S. noninstitutionalized population. Weighted descriptive statistics and logistic regression models were used to evaluate patterns and rates of overall prescription medication use in patients reporting headache as a household condition. RESULTS: An estimated 9.7 million people 18 years or older reported suffering from headache in 2000. Of these, 46% reported using at least one medication for the treatment of headache. Migraine-specific abortive medication (ie, selective serotonin receptor agonists and ergotamine derivatives) was the most frequently reported medication class, used by 36% of participants. Opiate analgesics and butalbital-containing products also experienced extensive prescribing reported by 22% and 17% of survey respondents, respectively. After adjustment for covariates, wide variation in the use of prescription medication was observed across sociodemographic characteristics including age, ethnicity, and insurance status. CONCLUSION: The observed variation in prescription medication use by drug class and sociodemographic characteristics suggests strategies are needed for improving current prescribing patterns in this patient population.