Anna Korotkova - Academia.edu (original) (raw)

Papers by Anna Korotkova

Zeitschrift fü Arztliche Fortbildung und Qualitatssicherung

All rights in this document are reserved by the WHO Regional Office for Europe. The document may ... more All rights in this document are reserved by the WHO Regional Office for Europe. The document may nevertheless be freely reviewed, abstracted, reproduced or translated into any other language, but not for sale or for use in conjunction with commercial purposes. Any views expressed by named authors are solely the responsibility of those authors. The Regional Office would appreciate receiving three copies of any translation. TARGET 34 MANAGING HEALTH FOR ALL DEVELOPMENT By the year 2000, management structures and processes should exist in all Member States to inspire, guide and coordinate health development, in line with health for all principles.

The Lancet, 2020

Background Achieving universal health coverage (UHC) involves all people receiving the health ser... more Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0-100 based on the 2•5th and 97•5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target-1 billion more people benefiting from UHC by 2023-we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45•8 (95% uncertainty interval 44•2-47•5) in 1990 to 60•3 (58•7-61•9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2•6% [1•9-3•3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite noncommunicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0•79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US1398pooledhealthspendingpercapita(US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388•9 million (358•6-421•3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3•1 billion (3•0-3•2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968•1 million [903•5-1040•3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to

Health, 2016

Background: Potential years of life lost (PYLL) rate describes the number of years lost due to pr... more Background: Potential years of life lost (PYLL) rate describes the number of years lost due to preventable premature death in a population. This is equal to the loss of human capital. Cause-specific PYLL-rates provide information for public health policy. Methods: PYLL-rate is calculated as an absolute difference between the age at death and the assumed length of life. Causes of preventable deaths are defined and classified according to International Classification of Diseases version 10 (ICD-10) as determined by World Health Organization. PYLL rate is age-standardized and expressed per 100,000 persons. Organization for Economic Cooperation and Development (OECD) standard of 70 years was applied as the expected length of life in Saint Petersburg (Russia), Edmonton (Canada), and Helsinki (Finland). Results: There were very big differences in PYLL rates of all causes of death between the countries compared. Total PYLL-rates were the lowest in Helsinki, slightly higher in Edmonton, and the highest in Saint Petersburg. The intercity differences in the total of PYLL-rates were considerably smaller among women than men. In each city, the three most prevalent causes of premature death were injuries, cancer and cardiovascular diseases. Magnitudes of these causes varied between the three cities. Conclusions: PYLL rate provides comparable and sensitive information about the health related well-being of a population concerning all preventable causes of death as well as cause-specific premature deaths. The study demonstrates that the reduction of cause-specific PYLL-rates is possible. It provides supplementary information for planning of health policies and evaluation of effectiveness of past interventions. Results demonstrate that these actions need to differ between countries and localities. I. Krasilnikov et al.

Zeitschrift fü Arztliche Fortbildung und Qualitatssicherung

All rights in this document are reserved by the WHO Regional Office for Europe. The document may ... more All rights in this document are reserved by the WHO Regional Office for Europe. The document may nevertheless be freely reviewed, abstracted, reproduced or translated into any other language, but not for sale or for use in conjunction with commercial purposes. Any views expressed by named authors are solely the responsibility of those authors. The Regional Office would appreciate receiving three copies of any translation. TARGET 34 MANAGING HEALTH FOR ALL DEVELOPMENT By the year 2000, management structures and processes should exist in all Member States to inspire, guide and coordinate health development, in line with health for all principles.

The Lancet, 2020

Background Achieving universal health coverage (UHC) involves all people receiving the health ser... more Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0-100 based on the 2•5th and 97•5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target-1 billion more people benefiting from UHC by 2023-we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45•8 (95% uncertainty interval 44•2-47•5) in 1990 to 60•3 (58•7-61•9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2•6% [1•9-3•3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite noncommunicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0•79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US1398pooledhealthspendingpercapita(US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388•9 million (358•6-421•3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3•1 billion (3•0-3•2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968•1 million [903•5-1040•3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to

Health, 2016

Background: Potential years of life lost (PYLL) rate describes the number of years lost due to pr... more Background: Potential years of life lost (PYLL) rate describes the number of years lost due to preventable premature death in a population. This is equal to the loss of human capital. Cause-specific PYLL-rates provide information for public health policy. Methods: PYLL-rate is calculated as an absolute difference between the age at death and the assumed length of life. Causes of preventable deaths are defined and classified according to International Classification of Diseases version 10 (ICD-10) as determined by World Health Organization. PYLL rate is age-standardized and expressed per 100,000 persons. Organization for Economic Cooperation and Development (OECD) standard of 70 years was applied as the expected length of life in Saint Petersburg (Russia), Edmonton (Canada), and Helsinki (Finland). Results: There were very big differences in PYLL rates of all causes of death between the countries compared. Total PYLL-rates were the lowest in Helsinki, slightly higher in Edmonton, and the highest in Saint Petersburg. The intercity differences in the total of PYLL-rates were considerably smaller among women than men. In each city, the three most prevalent causes of premature death were injuries, cancer and cardiovascular diseases. Magnitudes of these causes varied between the three cities. Conclusions: PYLL rate provides comparable and sensitive information about the health related well-being of a population concerning all preventable causes of death as well as cause-specific premature deaths. The study demonstrates that the reduction of cause-specific PYLL-rates is possible. It provides supplementary information for planning of health policies and evaluation of effectiveness of past interventions. Results demonstrate that these actions need to differ between countries and localities. I. Krasilnikov et al.