Background: To reduce the burden of patients' medical care, the Xuzhou Municipal Government has initiated an exploratory study on the supply model and categorized management of nationally negotiated drugs. This study aims to understand the extent to which Xuzhou's 2021 reform of the National Drug Price Negotiation (NDPN) policy has had a positive impact on the healthcare costs of individuals with different types of health insurance.
Methods: The Interrupted Time Series Analysis method was adopted, and the changes in average medical expenses per patient, average medical insurance payment cost per patient and actual reimbursement ratio were investigated by using the data of single-drug payments in Xuzhou from October 2020 to October 2022.
Results: Following the implementation of the policy, there was a significant decrease in the average medical expenses per patient of national drug negotiation in Xuzhou, with a reduction of 62.42 yuan per month ( < 0.001). Additionally, the average medical insurance payment cost per patient decreased by 44.13 yuan per month ( = 0.01). Furthermore, the average medical expenses per patient of urban and rural medical insurance participants decreased by 63.45 yuan ( < 0.001), and the average monthly medical insurance payment cost per patient decreased by 57.56 yuan ( < 0.04). However, the mean total medical expenditures for individuals enrolled in employee medical insurance decreased by 63.41 yuan per month ( < 0.001), whereas the monthly decrease was 22.11 yuan per month ( = 0.21). On the other hand, there was no discernible change in the actual reimbursement ratio.
Conclusion: After the adoption of the NDPN policy, a noticeable decline has been observed in the average medical expenses per patient and the mean cost of the average medical insurance payment per patient, although to a limited extent. Notably, the reduction in employee medical insurance surpasses that of urban and rural medical insurance.
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http://dx.doi.org/10.3389/fpubh.2024.1381786 | DOI Listing |
J Cheminform
January 2025
School of Systems Biomedical Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, 06978, Seoul, Republic of Korea.
G protein-coupled receptors (GPCRs) play vital roles in various physiological processes, making them attractive drug discovery targets. Meanwhile, deep learning techniques have revolutionized drug discovery by facilitating efficient tools for expediting the identification and optimization of ligands. However, existing models for the GPCRs often focus on single-target or a small subset of GPCRs or employ binary classification, constraining their applicability for high throughput virtual screening.
View Article and Find Full Text PDFAddict Sci Clin Pract
January 2025
Department of Medicine, Division of General Internal Medicine, University of Washington/Harborview Medical Center, 325 9Th Avenue, Box 359780, Seattle, WA, 98104, USA.
Background: Initiation of buprenorphine for treatment of opioid use disorder (OUD) in acute care settings improves access and outcomes, however patients who use methamphetamine are less likely to link to ongoing treatment. We describe the intervention and design from a pilot randomized controlled trial of an intervention to increase linkage to and retention in outpatient buprenorphine services for patients with OUD and methamphetamine use who initiate buprenorphine in the hospital.
Methods: The study is a two-arm pilot randomized controlled trial (N = 40) comparing the mHealth Incentivized Adherence Plus Patient Navigation (MIAPP) intervention to treatment as usual.
Trials
January 2025
Université Côte d'Azur, CNRS, LP2M, Nice, France.
Background: /aims. Pseudoxanthoma Elasticum (PXE, OMIM 264800) is an autosomal, recessive, metabolic disorder characterized by progressive ectopic calcification in the skin, the vasculature and Bruch's membrane. Variants in the ABCC6 gene are associated with low plasma pyrophosphate (PPi) concentration.
View Article and Find Full Text PDFTrials
January 2025
Department of Electrical and Computer Engineering, Princeton University, Princeton, 08544, NJ, USA.
Background: Phase-3 clinical trials provide the highest level of evidence on drug safety and effectiveness needed for market approval by implementing large randomized controlled trials (RCTs). However, 30-40% of these trials fail mainly because such studies have inadequate sample sizes, stemming from the inability to obtain accurate initial estimates of average treatment effect parameters.
Methods: To remove this obstacle from the drug development cycle, we present a new algorithm called Trend-Adaptive Design with a Synthetic-Intervention-Based Estimator (TAD-SIE) that powers a parallel-group trial, a standard RCT design, by leveraging a state-of-the-art hypothesis testing strategy and a novel trend-adaptive design (TAD).
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