Научно-практический журнал Медицинские технологии. Оценка и выбор
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Issue № 32 | 2018 (2)

DOI: https://doi.org/10.31556/2219-0678.2018.32.2.024-033 meta

Abstract

The classification algorithm is one of the key elements of the provider-payment system based on diagnostic related groups (DRG). Current version of the algorithm in Russian DRG system is described in a manual approved by the Federal Fund of Compulsory Medical Insurance. The algorithm determines the steps of computerized assignment of each hospital case to the DRG. Each region of Russia creates its own information system for classification of cases based on the approved algorithm. The article provides a brief analysis of the case-mix classification criteria and the classification algorithms in the Russian DRG model. The problems of the current algorithm are underlined and illustrated by the examples. Finally, the authors propose the ways for improving the algorithm.

Keywords

provider-payment methods in healthcare, diagnostic related groups (DRG), classification algorithm.

For citations

Fedyaev D. V., Akimov O. V., Zuev A. V. Algorithm of Hospital Cases Classification in the Russian Model of Diagnostic Related Groups: Need for Improvement. Medical Technologies. Assessment and Choice. 2018; 2(32): 24–33.

Issue № 31 | 2018 (1)

Abstract

In the last decade, the interest of the Russian and international scientific and medical communities and pharmaceutical companies in the research of routine clinical practice has increased significantly. In addition to the already usual term «non-intervention study», «real world data» and «real world evidence» came; role of health technology assessment is being emphasized more often and more actively, more attention is being paid to patient-oriented approach. The objectives of this article are: updating information in the field of routine clinical practice, discussing new terms for the Russian-language scientific literature and the role of real world data in health technology assessment.

Keywords

non-interventional study, real-world data study, health technology assessment.

For citations

Goldina T. A., Suvorov N. I. Real-World Data Studies: from Data to Health Technology Assessment and Decision-Making in Healthcare. Medical Technologies. Assessment and Choice. 2018; 1(31): 21–29.

Issue № 31 | 2018 (1)

Abstract

An approach is proposed to find reference values of incremental cost-effectiveness ratio (ICER) for the assessment of pharmacoeconomic effectiveness of drugs for lists of vital and essential drugs. The essence is to use a unified simple method of calculation of ICER for drugs within the therapeutic groups already included into the list. The criteria of effectiveness should be separately defined for each area. The method was developed on the example of antineoplastic drugs. The numerator in the formula of ICER is the difference in costs between compared drugs, and the denominator is the difference in saved life years or life years without tumor progression obtained from the overall survival rate or progression-free survival in randomized clinical trials (RCT). RCT that form the basis for ICER calculation should demonstrate statistically significant advantages of the proposed drug compared to the drug already included into the list. The calculation considers the cost of drugs only.

Keywords

incremental cost-effectiveness ratio (ICER), list of vital and essential drugs, antineoplastic drugs.

For citations

Omelyanovsky V. V., Avxentyeva M. V., M. V. Sura M. V., Khachatryan G. R., Savilova A. G. Approaches to the Creation of a Unified Method of Calculation of Incremental Cost-Effectiveness Ratio for the Re-Consideration of Lists of Medical Drugs; an Example of Antineoplastic Drugs. Medical Technologies. Assessment and Choice. 2018; 1(31): 10–20.

Issue № 30 | 2017 (4)

Abstract

The aim of the study was to identify the main directions of improvement of planning and organization of medical care based on the analysis of age and gender composition of the population of the Moscow region, and its special features compared to the national level. The analysis was based on the materials of the Russian Federal State Statistics Service (Rosstat). The dynamics of the number of population was assessed for the period between 2012 and 2016. According to the analysis, the Moscow region was typical in respect of age and gender composition. There was a trend towards the increase of the share of older population and persons under active working age. The decrease of working population increases demographic load and decreases GDP. We found demographic depression under 19 years of age that should lead to the decrease in marriages and in the formation of family structures in the nearest future. The assessment of the trends in demographic factors enables to predict the transformation of demand for medical services and to plan reorganization of health care in Russian regions.

Keywords

age and gender composition, organization of medical care, Moscow region.

For citations

Voynov M. A., Yelchuyeva Z. G. Identification of the Main Directions for the Improvement in Planning and Organization of Medical Care Based on the Analysis of Population Structure by Age and Sex (on the Example of Moscow Region). Medical Technologies. Assessment and Choice. 2017; 4(30): 21–29.

Issue № 30 | 2017 (4)

Abstract

Since 2012, a unified model of payment for hospital care based on diagnosis related groups (DRGs) is being implemented in the Russian system of mandatory health insurance. Today, two mechanisms of the regional adaptation of this model are defined on the federal level. The first one is adjustment coefficients (coefficient for the level of medical care in health care organization, coefficient for the complexity of treatment, management coefficient), and the second one is distinguishing subgroups within standard DRGs. The analysis of tariff agreements in regions revealed significant transregional differences in interpretation and application of the established rules. They vary from strict compliance with the approved algorithms to arbitrary and often distorted interpretation of federal recommendations. The obtained data suggest that tighter restrictions are needed on the federal level in respect of regional adjustment coefficients, including those for day hospitals. The experience of some regions in distinguishing subgroups in standard DRGs including drug treatment schedules may be useful for further subdivision of DRGs on the federal level.

Keywords

diagnosis-related groups (DRG), coefficient for the level of medical care in health care institution (CLC), coefficient for the complexity of treatment of patient (CCT), management coefficient (MC), subgroups of DRG.

For citations

Sura M. V. DRG-based Payment for Medical Care in Mandatory Health Insurance: Regional Adaptation. Medical Technologies. Medical Technologies. Assessment and Choice. 2017; 4(30): 11–20.

Issue № 29 | 2017 (3)

Abstract

Original research data in MEDLINE database allows one to find the most comprehensive answer to clinical query. This entails the problem of large amounts of material that needs to be analyzed. The main study objective was to develop an algorithm for search results ranking of medical studies based on the levels of evidence. Developed search engine is based on a combination of classifiers that determine the level of evidence and subtype of medical intervention for a study abstract. As the main classification algorithms linear classifiers, as well as AdaBoost with Random Forest and SVM with RBF kernel were considered. Evaluation of the quality of classification by medical intervention subtypes was obtained using 5-folds cross validation method. Generative probabilistic LDA model was used for solving the problem of training set imbalance. The developed algorithm allows one with 92% precision to determine the study level of evidence, and to rank query results in relevance descending order.

Keywords

evidence-based medicine, algorithm, MEDLINE, searching.

For citations

Kamalov M. V., Dobrynin V. Yu., Balykina Yu. E., Kolbin A. S., Verbitskaya E. V. Ranking Algorithm for Medical Research Results Based on the Levels of Evidence at the Stage of Getting Answers to Search Queries. Medical Technologies. Assessment and Choice. 2017; 3(29): 11–21.

Issue № 28 | 2017 (2)

Abstract

Best practice recommendations for HTA system design which do not pay sufficient attention to local institutional environments may prove to be suboptimal or dysfunctional in countries newly implementing HTA. This study presents how HTA system design can be supported by taking an institutional perspective and adopting basic findings from contingency theory. A four-step rational process to HTA system is described and nine practical recommendations are formulated for Russia and the Eurasian Economic Union.

Keywords

contingency theory, HTA system design, HTA institutions, Russia, Eurasian Economic Union.

For citations

Danko D., Khachatryan G. R. Development of Health Technology Assessment Systems in the Countries at the Initial Stage of their Introduction – Recommendations for Russia and the Countries of the Eurasian Economic Union. Medical Technologies. Assessment and Choice. 2017; 2(28): 10–19.

Issue № 27 | 2017 (1)

Abstract

The article presents the Russian-language version of the questionnaire to assess the risk of systematic bias in cross-sectional studies of diagnostic tests. This version is the adapted translation of the international consensus questionnaire QUADAS. The risk of systematic bias in the original scale is not stratified, however, we propose to evaluate the overall risk of systematic bias as low, medium or high, depending on the score sum according to the criteria of the questionnaire. To assess the overall methodological quality not only the risk of systematic bias should be assessed, but also the risk of incorrect statistical analysis.

Keywords

cross-sectional study, diagnostic test, diagnostic accuracy, reference test, systematic bias, assessment, QUADAS.

For citations

Rebrova O. Yu., Fediaeva V. K. Assessment of Risk of Bias in the Cross-Sectional Studies of Diagnostic Tests: the Russian-Language Version of the Questionnaire QUADAS. Medical Technologies. Assessment and Choice. 2017; 1(27): 11–14.

Issue № 25 | 2016 (3)

Abstract

The article presents the Russian-language version of the questionnaire to assess the risk of systematic bias in case-control studies and cohort studies. These questionnaires are translations of the Newcastle-Ottawa Scale to assess the methodological quality of non-randomized studies. The risk of systematic bias in the original scale is not stratified, but in practice the Cochrane Collaboration considered trials with 5 or fewer points (of 9) to have a low methodological quality. We propose to assess the methodological quality not only by the assessing risk of systematic errors, but also the risk of incorrectness of statistical analysis.

Keywords

non-randomized trial, case-control, cohort, questionnaire, systematic bias, systematic error, assessment, methodological quality, Newcastle-Ottawa Scale.

For citations

Rebrova O. Yu., Fedyaeva V. K. The Questionnaire to Assess the Risk of Systematic Bias in Non-Randomized Comparative Studies: the Russian-Language Version of the Newcastle-Ottawa Scale. Medical Technologies. Assessment and Choice. 2016; 3(25): 14–19.

Issue № 25 | 2016 (3)

Abstract

Multicriteria decision analysis (MCDA) is the mathematical approach that allows to take into account several factors when making difficult decisions. The article presents the results of a pilot application of MCDA for rare diseases and orphan drugs. Comparison of two methods (direct weighting and swing weighting) for assessing the importance of the criteria was conducted. The advantage of the second approach was shown.

Keywords

multi-criteria decision analysis, MCDA, decision-making, rare diseases, weighting coefficients, direct weighting, swing weighting.

For citations

Fedyaeva V. K., Rebrova O. Yu., Omelyanovskiy V. V. Comparison of Methods for Assessing the Importance of the Criteria in Multi-Criteria Decision Analysis in Financing the Treatment of Rare Diseases. Medical Technologies. Assessment and Choice. 2016; 3(25): 8–13.