Научно-практический журнал Медицинские технологии. Оценка и выбор
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Issue № 24 | 2016 (2)

Abstract

We have developed an instrument to assess the methodological quality of network meta-analyzes and indirect comparisons based on International Society for Pharmacoeconomics and Outcomes Research (ISPOR) tool. This instrument includes 15 questions on five aspects (domains): the evidence base, analysis, presentation of results, interpretation, conflict of interests. For each domain the estimate is given informally then the general credibility (methodological quality) of the research is assessed.

Keywords

network meta-analysis, indirect comparison, mixed treatment comparison, credibility, methodological quality, questionnaire, assessment, ISPOR.

For citations

Rebrova O. Yu., Fedyaeva V. K. The Questionnaire for Evaluating the Credibility of the Network Meta-Analysis (Including Mixed and Indirect Comparisons). Medical Technologies. Assessment and Choice. 2016; 2(24): 9–15.

Issue № 23 | 2016 (1)

Abstract

Meta-analysis is often considered as the highest level evidence on the effectiveness and safety of drugs and other medical technologies; however, the methodological quality of meta-analyses and systematic reviews varies considerably, which leads to the differences of effect values and the levels of evidence of the results. In 2007, validated tool to assess the methodological quality of systematic reviews AMSTAR has been developed. It is based on the combination of many elements of the previous evaluation systems. We have translated AMSTAR into Russian and made some extra explanation. The current publication presents the Russian-language version of the questionnaire. We believe that the Russian version of AMSTAR questionnaire can be used for a more objective assessment of the evidence of medical technology.

Keywords

systematic review, meta-analysis, questionnaire, AMSTAR, Russian version.

For citations

Rebrova O. Yu., Fedyaeva V. K. Meta-analyses and Assessment of Their Methodological Quality. Russian Version of AMSTAR Questionnaire. Medical Technologies. Assessment and Choice. 2016; 1(23): 10–16.

Issue № 22 | 2015 (4)

Abstract

Restrictive drug lists can be considered to be one of the signs of reimbursement formation in Russia. According to the new rules developed in 2014, the basic principle for the Vital and Essential Drugs (VED) List compilation is a structured formalized expert opinion. The aim of this study was to construct a decision making model using mathematical tools for the VED List compilation. The paper describes a mathematical formalization of the problem, as well as mathematical modeling techniques used. Based on the constructed models, the conclusion data received from the expert organizations (EO), the main external specialist of the Ministry of Health (MES), and the data on the final decision made by interdisciplinary committee of the Ministry of Health (IC) were analyzed. The study showed that the linear regression models can be partly applied to solve the problems mentioned above. The VED List analysis with help of linear models showed that the constructed rules for an expert organization gave an error of 12.4%. The model for the analysis of the EO opinion influence on the MES conclusion gave an error of 10%. The model for the final decision gave an error of about 35%, i. e. it was impossible to determine the final Committee decision based on the scoring made by the previous agents. Recommendations on optimizing the formalized approach are presented.

Keywords

restrictive lists, formalized approach, mathematical modeling, scores.

For citations

Prasolov A.V., Kolbin A.S., Maksimkina E.A., Golant Z.M., Polushin Y.S., Kurylev A.A., Viilyum I.A., Balykina Y.E. Analysis of the 2014 Vital and Essential Drugs (VED) List Using Mathematical Modelling. Medical Technologies. Assessment and Choice. 2015; 4(22): 13–19.

Issue № 3 | 2015 (21)

Abstract

The best practice of new biomed technologies development assessment is based on rigorous and transparent management system and applied criteria. The paper is focused on innovative projects assessment management in the context of the Skolkovo Foundation expert panel. Results of its implementation are demonstrated, considering advantages and disadvantages as well as its future development.

Keywords

expertise, innovation, Skolkovo Foundation, project assessment.

For citations

Khodova К.А., Grechikhin P.V., Kutsakov V.N., Nikolsky Y.V., Bulatov K.A., Kaem K.V. Management of Innovative Projects Assessment: Skolkovo Foundation Perspective. Medical Technologies. Assessment and Choice. 2015; 3(21): 15–20.

Issue № 3 | 2015 (21)

Abstract

To assess the relative cost-effectiveness of the two medical technologies (cost-effectiveness analysis, CEA), the incremental cost-effectiveness ratio (ICER), net (monetary) health benefit (NHB) and the cost-effectiveness acceptability curve (CEAC) are used. The criterion «willingness to pay» is utilized in the above approaches. In this study, we simulated data of two medical interventions (effects and costs) and computed cost-effectiveness using the above three methods, and then compared the results. We revealed the proximity of the 95% CI for the ICER, calculated using different approaches (nonparametric percentile bootstrap, parametric Fieller, based on the NHB and CEAC). This allows to make reliable statistical conclusion about two compared medical technology and support decision making.

Keywords

cost-effectiveness analysis, confidence interval, incremental cost-effectiveness ratio, net (monetary) health benefit, cost-effectiveness acceptability curve.

For citations

Simonov A.N., Rebrova O.Yu. Statistical Estimates of Cost-Effectiveness of Medical Technologies. Medical Technologies. Assessment and Choice. 2015; 3(21): 8–14.

Issue № 2 | 2015 (20)

Abstract

The article touches upon assessment methodology of treatment compliance, describes existing assessment criteria and gives their sample calculations. Attempt was made to analyze the use of Russian terms for designation of criteria in question.

Keywords

treatment compliance, compliance, treatment adherence duration, continuity of treatment, health technology assessment, period of distribution, acceptable gap.

For citations

Dombrovskiy V.S., Omelyanovskiy V.V. Study Questions of Treatment Compliance: Assessment Criteria and Terminology. Medical Technologies. Assessment and Choice. 2015; 2(20): 16–23.

Issue № 2 | 2015 (20)

Abstract

One of the main goals of a state health care system is improving population health status. It is essential to inform public health policymakers about real problems of citizen health. The authors of Global Burden of Disease study have developed a new approach to compare the effects of different diseases and injuries that lead to premature death and impaired health, and to assess the burden of disease caused by the infl uence of various risk factors. They used Disability-Adjusted Life Years (DALY) indicator to quantify the comparative magnitude of health loss due to different factors. To analyze the major causes of morbidity and premature mortality for the working population in terms of DALYs for Russia in 2013 we used the data, calculations and methodology of GBD study. Also we assessed leading risk factors for illnesses of Russian citizens.

Keywords

GBD research, YLD indicator, YLL indicator, DALY indicator, GDP losses due to disability, risk factors, death and disability causes.

For citations

Skornyakova Е.S. How to Assess Health? Medical Technologies. Assessment and Choice. 2015; 2(20): 9–15.

Issue № 1 | 2015 (19)

Abstract

This paper presents the main elements of the Markov process, including health states, the transition probabilities, cycle tree, and the advantages and disadvantages of both cohort and microsimulation models. Markov models are most often used for the modeling of time-dependent clinical events. The Markov process assumes that patients are always in one of a number of exclusive health states. All events in these models are transitions from one of these states to another. Health technology assessment involves simulating the outcomes of either a cohort or individual patients.

Keywords

Markov process, transition probability, health state, cycle tree, cohort and micro simulations.

For citations

Djalalov S.Ch., Djalalova D.K., Hoch J.S. State-Transition Modeling: Markov Process. Medical Technologies. Assessment and Choice. 2015; 1(19): 18–28.

Issue № 1 | 2015 (19)

Abstract

The questionnaire of the Cochrane Collaboration developed to assess risks of the main bias in randomized controlled trials (RCT) was translated into Russian. It was also adapted and validated. We proposed to consider the risk of the conflict of interests as a mandatory part of the questionnaire. Also we slightly modified the rule to determine the total risk of bias in RCTs. Validation of the questionnaire accomplished by two experts on 20 RCTs demonstrated good agreement: Kappa = 0.785, 95% CI (0.503; 1.000).

Keywords

randomized controlled trials, bias, questionnaire, Cochrane collaboration, validation, adaptation.

For citations

Rebrova O.Yu., Fedyaeva V.K., Khachatryan G.R. Adaptation and Validation of the Cochrane Questionnarie to Assess Risks of Bias in Randomized Controlled Trials. Medical Technologies. Assessment and Choice. 2015; 1(19): 9–17.

Issue № 4 | 2014 (18)

Abstract

This article describes two basic principles of the methodological quality assessment of the original medical research: 1) evaluation of relevance of study design to its objectives, 2) assessment of the methodological quality of studies in aspects of risks of systematic bias and incorrect statistical analysis. This article opens a series of publications that will describe the methods of formalized assessment of methodological quality for each of the most common designs of the original medical research.

Keywords

health technology assessment, evidence, expertise, methodological quality, systematic bias, statistical analysis.

For citations

Rebrova O.Yu. On Principles of Assessment of Medical Research Methodological Quality. Medical Technologies. Assessment and Choice. 2014; 4(18): 15–18.