Background: Cost sharing is widely used to encourage therapeutic substitution. This study aimed to examine the impact of increases in patient cost-sharing differentials for brand name and generic drugs on statin utilization on entry into the Medicare Part D coverage gap.
Method And Results: Using 5% Medicare Chronic Condition Warehouse files from 2006, this quasi-experimental study examined patients with hyperlipidemia who filled prescriptions for atorvastatin or rosuvastatin between January and March 2006. Propensity score matching and difference-in-difference regressions were used to compare changes in statin utilization for the study group (patients who were not eligible for low-income subsidies [non-LIS] and had generic-only gap coverage) to those of a control group (LIS patients who faced the same cost sharing before and during the Part D coverage gap). In the final sample, 801 patients in the study group were matched to 801 patients in the control group. We found that, compared to the control group, the study group had a larger decline in any monthly brand-name statin use (-0.24 30-day fills, P<0.001). This was only partially offset by increased monthly generic statin use (+0.06 30-day fill, P<0.001), with an overall drop in any monthly statin use (-0.18 30-day fills, P<0.001). Overall adherence with statins declined (OR 0.81, P<0.001), and statin discontinuation increased (OR 1.62, P<0.001) in the study group as compared to the control group.
Conclusions: Increases in cost-sharing differentials for brand name and generic drugs on coverage gap entry were associated with discontinuation of statins in Medicare Part D patients with hyperlipidemia.
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http://dx.doi.org/10.1161/JAHA.116.003377 | DOI Listing |
Appl Clin Inform
January 2025
Divison of Quantitative and Clinical Sciences, Vanderbilt University Medical Center, Nashville, United States.
Background: The use of Electronic Health Records (EHRs) in research demands robust, interoperable systems. By linking biorepositories to EHR algorithms, researchers can efficiently identify cases and controls for large observational studies (e.g.
View Article and Find Full Text PDFPLOS Glob Public Health
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MSD LATAM, San José, Costa Rica.
Varicella presents a public health challenge in Guatemala, with limited evidence regarding its impact; vaccine is currently absent from the national immunization program. Generating local data on the economic and health burden can support immunization policies. This study describes the use of hospital resources, costs of care, clinical and demographic characteristics, and complications in children with varicella.
View Article and Find Full Text PDFDiabetologia
January 2025
MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Aims/hypothesis: UK standard care for type 2 diabetes is structured diabetes education, with no effects on HbA, small, short-term effects on weight and low uptake. We evaluated whether remotely delivered tailored diabetes education combined with commercial behavioural weight management is cost-effective compared with current standard care in helping people with type 2 diabetes to lower their blood glucose, lose weight, achieve remission and improve cardiovascular risk factors.
Methods: We conducted a pragmatic, randomised, parallel two-group trial.
BMC Health Serv Res
January 2025
Mayo Clinic Health System Northwest Wisconsin, Eau Claire, Wisconsin, USA.
Background: Interpreter service mode (in person, audio, or video) can impact patient experiences and engagement in the healthcare system, but clinics must balance quality with costs and volume to deliver services. Videoconferencing and telephone services provide lower cost options, effective where on site interpreters are scarce, or patients with limited English proficiency (LEP) and/or interpreters are unable to visit healthcare centers. The COVID 19 pandemic generated these conditions in Northwest Wisconsin (NWWI).
View Article and Find Full Text PDFMethods
January 2025
School of Computer Science and Engineering, Central South University, Changsha 410083, China; Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China.
Compound-protein interaction (CPI) prediction is critical in the early stages of drug discovery, narrowing the search space for CPIs and reducing the cost and time required for traditional high-throughput screening. However, CPI-related data are usually distributed across different institutions and their sharing is restricted because of data privacy and intellectual property rights. Constructing a scheme that enhances multi-institutional collaboration to improve prediction accuracy while protecting data privacy is essential.
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