cost effectiveness analysis
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2022 ◽  
Vol 28 ◽  
pp. 90-97
Author(s):  
Bahia Namavar Jahromi ◽  
Mozhgan Fardid ◽  
Elahe Esmaili ◽  
Zahra Kavosi ◽  
Zahra Shiravani ◽  
...  

2022 ◽  
Vol 242 ◽  
pp. 106780
Author(s):  
Rosabianca Trevisi ◽  
Sara Antignani ◽  
Teresa Botti ◽  
Giuliana Buresti ◽  
Carmela Carpentieri ◽  
...  

Healthcare ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 160
Author(s):  
Daniel Fernández-Sanchis ◽  
Natalia Brandín-de la Cruz ◽  
Carolina Jiménez-Sánchez ◽  
Marina Gil-Calvo ◽  
Pablo Herrero ◽  
...  

Introduction: Dry needling is a non-pharmacological approach that has proven to be effective in different neurological conditions. Objective: The aim of this study was to evaluate the cost-effectiveness of a single dry needling session in patients with chronic stroke. Methods: A cost-effectiveness analysis was performed based on a randomized controlled clinical trial. The results obtained from the values of the EuroQol-5D questionnaire and the Modified Modified Ashworth Scale were processed in order to obtain the percentage of treatment responders and the quality-adjusted life years (QALYs) for each alternative. The cost analysis was that of the hospital, clinic, or health center, including the equipment and physiotherapist. The cost per respondent and the incremental cost-effectiveness ratio of each alternative were assessed. Results: Twenty-three patients with stroke were selected. The cost of DN treatment was EUR 14.96, and the data analysis showed a favorable cost-effectiveness ratio of both EUR/QALY and EUR/responder for IG, although the sensitivity analysis using limit values did not confirm the dominance (higher effectiveness with less cost) of the dry needling over the sham dry needling. Conclusions: Dry needling is an affordable alternative with good results in the cost-effectiveness analysis—both immediately, and after two weeks of treatment—compared to sham dry needling in persons with chronic stroke.


Author(s):  
Fatimah Baqer Alqubbanchi ◽  
Fadya Yaqoob Al-Hamadani

Abstract Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through evidence-based pricing decisions. Objective: compare the clinical outcome and the costs of two anticoagulants (heparin and (enoxaparin)) used to treat hospitalized patients with COVID-19 infection. Patients and method: The study was a retrospective review of medical records of adult, non-pregnant, COVID-19 infected hospitalized patients who had baseline and last outcome measurements at Alamal Epidemiology Center, Al-Najaf city from (Augast 2020 to June 2021). The outcome measures included D-dimer, length of stay (LOS), and mortality rate. Only the cost of the medical treatment was considered in the analysis. The pharmacoeconomics analysis was done in three different cost-effectiveness analysis methods. Microsoft Excel spreadsheet and Statistical Package for the Social Sciences software (SPSS), was used to conduct statistical analysis. Kaplan Meier test was used to compare the mortality rate. T-TEST was used to compare the outcomes of the two groups. Results and discussion: two groups were compared, the first group consists of 72 patients who received heparin, and the second group consists of 72 patients who received enoxaparin. COVID-19 infected patients had a higher abnormal average D-dimer (2534.675 ng/dl). No significant differences between both genders with regards to the basal average D-dimer (males= 2649.95 ng/dl, females= 2374.1mg/dl, P-value>0.05). There was a significant difference between patient's ages 60 years and patients <60. (3177.33 ng/dl, 1763.06 ng/dl, P-value <0.05). It seems that, higher D-dimer levels were associated with a higher mortality rate (died=3166.263 ng/dl, survived= 1729.94 ng/dl, P-value <0.05). Heparin was more effective in decreasing D-dimer levels than enoxaparin which inversely increased the D-dimer levels (-24.4 ng/dl/day, +154.701 ng/dl/day, P-value <0.05). Additionally, heparin was more effective in increasing the survival rate compared to enoxaparin (55% vs, 35%, P-value<0.05). Heparin was associated with a longer duration of stay in hospital than enoxaparin but with no significant difference (13.7 days, 12.3 days, P-value >0.05). Concerning the cost, treatment with heparin cost less than enoxaparin (2.08 U.S $, 9.44 U.S $)/per patient/per day. Conclusion: Originator heparin was a more cost-effective anticoagulant therapy compared to originator enoxaparin, it was associated with a lower cost and better effect, treatment with Heparin resulted in positive INB= 11.3, where a positive result means that heparin is more cost-effective than Enoxaparin. All three methods of pharmacoeconomic analysis decide that heparin was more cost-effective than enoxaparin in treating COVID-19 infected patients.


Neurology ◽  
2022 ◽  
pp. 10.1212/WNL.0000000000013313
Author(s):  
Jonathan D Campbell ◽  
Melanie D. Whittington ◽  
Steven D Pearson

The purpose of this paper is to describe the process and the methods of cost-effectiveness analysis for clinicians interested in joining or leading aspects of this branch of evidence-based research. Cost-effectiveness is a useful tool for policymakers and is considered a starting point for discussions of fair pricing. Clinicians are important members of teams conducting cost-effectiveness analyses, particularly as it relates to integrating their clinical expertise into the decisions around the design and conduct of the analysis. Their input is essential in assuring that models adequately reflect clinical practice and are informed by expert judgments of how existing data can best be interpreted to build a comprehensive analysis of the clinical and economic outcomes of different treatment options. We illustrate specific contributions that clinicians are well positioned to make in these teams using a recent cost-effectiveness analysis of aducanumab that was conducted to support fair drug pricing. While discussing these contributions, we explain key components of a cost-effectiveness analysis, such as time horizon, health states, and perspective, to support the understanding of the methods of cost-effectiveness by the clinical researchers and to promote a common dialogue among these multidisciplinary teams.


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