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Showing papers by "Christopher J L Murray published in 2000"


01 Jan 2000
TL;DR: The World Health Organization (WHO) adopted a standard based on the average age-structure of those populations to be compared (the world) over the likely period of time that a new standard will be used (some 25-30 years), using the latest UN assessment for 1998 (UN Population Division, 1998) from these estimates, an average world population agestructure was constructed for the period 2000-2025 as discussed by the authors.
Abstract: Summary A recent WHO analysis has revealed the need for a new world standard population (see attached table). This has become particularly pertinent given the rapid and continued declines in age-specific mortality rates among the oldest old, and the increasing availability of epidemiological data for higher age groups. There is clearly no conceptual justification for choosing one standard over another, hence the choice is arbitrary. However, choosing a standard population with higher proportions in the younger age groups tends to weight events at these ages disproportionately. Similarly, choosing an older standard does the opposite. Hence, rather than selecting a standard to match the current age-structure of some population(s), the WHO adopted a standard based on the average age-structure of those populations to be compared (the world) over the likely period of time that a new standard will be used (some 25-30 years), using the latest UN assessment for 1998 (UN Population Division, 1998). From these estimates, an average world population age-structure was constructed for the period 2000-2025. The use of an average world population, as well as a time series of observations, removes the effects of historical events such as wars and famine on population age composition. The terminal age group in the new WHO standard population has been extended out to 100 years and over, rather than the 85 and over as is the current practice. The WHO World Standard population has fewer children and notably more adults aged 70 and above than the world standard. It is also notably younger than the European standard. It is important to note, however, that the age standardized death rates based on the new standard are not comparable to previous estimates that are based on some earlier standard(s). However, to facilitate comparative analyses, WHO will disseminate trend analyses of the “complete” historical mortality data using on the new WHO World Standard Population in future editions of the World Health Statistics Annual.

2,065 citations


Journal ArticleDOI
TL;DR: By investigating four key functions of the health system and how they combine, it is possible not only to understand the proximate determinants of health system performance, but also to contemplate major policy challenges.
Abstract: Health systems vary widely in performance, and countries with similar levels of income, education and health expenditure differ in their ability to attain key health goals. This paper proposes a framework to advance the understanding of health system performance. A first step is to define the boundaries of the health system, based on the concept of health action. Health action is defined as any set of activities whose primary intent is to improve or maintain health. Within these boundaries, the concept of performance is centred around three fundamental goals: improving health, enhancing responsiveness to the expectations of the population, and assuring fairness of financial contribution. Improving health means both increasing the average health status and reducing health inequalities. Responsiveness includes two major components: (a) respect for persons (including dignity, confidentiality and autonomy of individuals and families to decide about their own health); and (b) client orientation (including prompt attention, access to social support networks during care, quality of basic amenities and choice of provider). Fairness of financial contribution means that every household pays a fair share of the total health bill for a country (which may mean that very poor households pay nothing at all). This implies that everyone is protected from financial risks due to health care. The measurement of performance relates goal attainment to the resources available. Variation in performance is a function of the way in which the health system organizes four key functions: stewardship (a broader concept than regulation); financing (including revenue collection, fund pooling and purchasing); service provision (for personal and non-personal health services); and resource generation (including personnel, facilities and knowledge). By investigating these four functions and how they combine, it is possible not only to understand the proximate determinants of health system performance, but also to contemplate major policy challenges.

870 citations


Journal Article
TL;DR: It is proposed that health is an intrinsic component of well-being and thus it should be concerned with inequality in health, whether or not it is correlated withequality in other dimensions ofWell-being.
Abstract: This paper proposes an approach to conceptualizing and operationalizing the measurement of health inequality, defined as differences in health across individuals in the population. We propose that health is an intrinsic component of well-being and thus we should be concerned with inequality in health, whether or not it is correlated with inequality in other dimensions of well-being. In the measurement of health inequality, the complete range of fatal and non-fatal health outcomes should be incorporated. This notion is operationalized through the concept of healthy lifespan. Individual health expectancy is preferable, as a measurement, to individual healthy lifespan, since health expectancy excludes those differences in healthy lifespan that are simply due to chance. In other words, the quantity of interest for studying health inequality is the distribution of health expectancy across individuals in the population. The inequality of the distribution of health expectancy can be summarized by measures of individual/mean differences (differences between the individual and the mean of the population) or inter-individual differences. The exact form of the measure to summarize inequality depends on three normative choices. A firmer understanding of people's views on these normative choices will provide a basis for deliberating on a standard WHO measure of health inequality.

305 citations


Journal ArticleDOI
TL;DR: The issues and challenges in the design and application of summary measures are reviewed, a framework for evaluating different alternatives is presented and a set of basic criteria and desirable properties that may lead to rejection of certain summary measures and the development of new ones are considered.
Abstract: In the past decade, interest has been rising in the development, calculation and use of summary measures of population health, which combine information on mortality and non-fatal health outcomes. This paper reviews the issues and challenges in the design and application of summary measures and presents a framework for evaluating different alternatives. Summary measures have a variety of uses, including comparisons of health in different populations and assessments of the relative contributions of different diseases, injuries and risk factors to the total disease burden in a population. Summary measures may be divided into two broad families: health expectancies and health gaps. Within each family, there are many different possible measures, but they share a number of inputs, including information on mortality, non-fatal health outcomes, and health state valuations. Other critical points include calculation methods and a range of conceptual and methodological issues regarding the definition, measurement and valuation of health states. This paper considers a set of basic criteria and desirable properties that may lead to rejection of certain summary measures and the development of new ones. Despite the extensive developmental agenda that remains, applications of summary measures cannot await the final resolution of all methodological issues, so they should focus on those measures that satisfy as many basic criteria and desirable properties as possible.

304 citations



Posted Content
TL;DR: The approach separates financing from utilisation, so that fairness in financial contribution is determined independently of the health status of the individual or household or the use of health services.
Abstract: One of the challenges common to all social systems is to achieve fairness in the distribution of the financing burden, and protection from the risk of financial loss. For health systems, this goal is of particular importance and especially difficult to achieve due to the catastrophic and unpredictable nature of some expenditures. Societies have long demonstrated a special concern about how health systems are financed.(Behrman 1995;Londono & Frenk 1997;World Health Organization 2000) Much of the public discourse in countries undertaking health sector reform is focused on the design of health system financing and its fairness. (Londono & Frenk 1997; Wagstaff A & Van Doorslaer E 1998) The purpose of this paper is to present a definition, a measure and an index of fairness in financial contribution to the health system. Our notion of fairness is not a concern about the extent to which contributions to the cost of the health system across households redistribute income. Starting from a society’s efforts to redistribute income, there are, nevertheless, important considerations of fairness that we try to define and quantify. Three issues are critical to this concept of fairness: avoiding catastrophic payments by households, horizontal equity and (to some extent) progressivity of contribution. Further, our approach separates financing from utilisation, so that fairness in financial contribution is determined independently of the health status of the individual or household or the use of health services.

72 citations


01 Jan 2000
TL;DR: Inequality estimates should be routinely reported alongside average levels of health, as they reveal important information about the distribution of health in populations, and measuring inequality with individual level data enables meaningful comparisons of inequality across countries and analyses of the determinants of inequality.
Abstract: a A file with all data and information necessary to replicate the results in this article is available from the authors. Abstract Background: Reducing health inequalities is an important part of the agenda of health policymakers globally. Studies of health inequalities have revealed large variations in average health status across social, economic, and other groups. However, no studies have been conducted on the distribution of the risk of ill-health across individuals. Methods: We use an extended beta-binomial model to estimate the distribution the risk of death in children under the age of two in the 50 developing countries where data from a Demographic and Health Survey are available. Inequality in these distributions is measured by the WHO health inequality index. Findings: At the same level of average child mortality, inequality in the risk of death across children can vary considerably across countries. Representing the entire distribution of risk with an inequality measure involves normative choices that we delineate and formalise with quantitative measures. The results are not very sensitive to the choice of measure. Liberia, Mozambique and the Central African Republic have the largest inequalities in child survival, while Colombia, the Philippines and Kazakhstan have the lowest among the 50 countries measured. Interpretation: Inequality estimates should be routinely reported alongside average levels of health, as they reveal important information about the distribution of health in populations. Measuring inequality with individual level data, rather than quantifying differences in average levels of health across social groups, enables meaningful comparisons of inequality across countries and analyses of the determinants of inequality. This approach should be extended to the measurement of inequalities in healthy life expectancy.

29 citations


Journal ArticleDOI
TL;DR: The approach is attacked for taking health inequalities across individuals as the starting point for efforts to standardize and promote the comparable measurement of inequality in health across populations, and for maintaining that social research is introduced as part of the theoretical framework from which social variables are derived in order to explain the distribution of health.
Abstract: In the above commentary, Braveman et al. criticize our papers (1, 2) for taking health inequalities across individuals as the starting point for efforts to standardize and promote the comparable measurement of inequality in health across populations. They interpret our approach as an attempt to "discredit research on social inequalities in health" and a "rejection of research on social inequalities". It is neither. Nor is it "univariate", as Braveman et al. suggest. What we have attempted is to construct a better dependent variable than the literature has provided so far: the distribution of health expectancy. With this dependent variable one can then analyse in a more rigorous fashion its social determinants. Far from "discrediting" or "rejecting" the scientific quality of research on social inequalities in health, our approach aims at improving it. Braveman et al. seem to imply that the only valid way of carrying out social analysis is by constructing an a priori categorization of the population through a social attribute such as occupation or education. In contrast, we maintain that social research is introduced as part of the theoretical framework from which social variables are derived in order to explain the distribution of health. Using the distribution of health expectancy across individuals as the dependent variable is perfectly compatible with a theoretical framework where social variables such as income, education and occupation are used to explain that distribution. Furthermore, we explicitly recognize the usefulness of the study of social group differences in health in developing estimates of the underlying distribution of health expectancy across individuals in a population (1). Below we respond to some of the more specific concerns raised by Braveman et al. 1. Geographical groups are social groups Braveman et al. argue that "geographical comparisons are similar to social group comparisons in that both involve a priori selection of a categorizing variable based on knowledge indicating its likely relevance". We agree with this statement, and have pointed out that "small area analyses may hold out the greatest promise for studying the extent to which social group health differences vary across countries"(2) and that "one particular approach to defining social groups, namely community location, has been much underutilized" (2). We also proposed that despite the limitations that small area analyses face, they do "hold out the promise of being one of the most refined methods for revealing the underlying distribution of health expectancy in a population" (1). 2. Health inequalities in the policy agenda Braveman et al. argue that promoting the measurement of health inequality across individuals rather than the "social group" approach, "could be used ... to prevent social inequalities in health from occupying an important place on the global research and policy agenda". This claim is very hard to understand. We believe that our efforts will place the critical problem of health inequalities prominently on the global agenda. The absence of comparable measures of health inequality across countries, such as those our approach is designed to achieve, is a major obstacle to placing health inequality more prominently on the global agenda. …

16 citations


01 Jan 2000
TL;DR: The authors define desigualdades en salud as "diferencias of salud entre los individuos of la población" and define a marco general for definir and medir these differences.
Abstract: Este articulo propone un marco general para definir y medir las desigualdades en salud, definidas como las diferencias de salud entre los individuos de la poblacion. Consideramos que la salud es un componente intrinseco del bienestar y que, por tanto, las desigualdades en salud tienen importancia en si mismas, esten o no correlacionadas con desigualdades en otras dimensiones del bienestar. En la medicion de las desigualdades en salud deben incorporarse todos los resultados relacionados con la salud, es decir, tanto la mortalidad como la morbilidad. Esa nocion se concreta en el concepto de (periodo de) vida sana. Como medida, la esperanza de salud individual es preferible al periodo de vida sana individual, ya que la esperanza de salud excluye las diferencias de vida sana simplemente debidas al azar. En otras palabras, la cantidad que interesa estudiar al abordar las desigualdades en salud es la distribucion de la esperanza de salud entre los individuos que componen el conjunto de la poblacion. La desigualdad de la distribucion de la esperanza de salud puede cuantificarse mediante las desviaciones individuales respecto de la media o mediante las desviaciones interindividuales. La forma exacta de la medida que resuma la desigualdad dependera de tres decisiones normativas. Las deliberaciones sobre esa medida normalizada de la OMS destinada a cuantificar la desigualdad en salud se verian beneficiadas por un mejor conocimiento de las opiniones de la gente respecto a esas tres decisiones normativas.

6 citations


01 Jan 2000
TL;DR: In this article, the authors present an ensemble of actions sanitaire to evaluate the performance of a sante system, i.e., ameliorer the sante, mieux repondre aux attentes de la population (reactivite) and assurer l’equite de la participation financiere.
Abstract: La performance des systemes de sante est extremement variable et des pays ayant un niveau equivalent de revenu, d’education et de depenses de sante n’ont pas la meme aptitude a atteindre leurs objectifs principaux en matiere de sante. Cet article presente un cadre pour mieux comprendre la performance des systemes de sante. La premiere etape consiste a tracer les limites du systeme de sante en se fondant sur le concept d’action sanitaire. On entend par action sanitaire un ensemble d’activites dont l’intention premiere est d’ameliorer ou de maintenir la sante. A l’interieur de ces limites, le concept de performance s’articule autour de trois objectifs fondamentaux : ameliorer la sante, mieux repondre aux attentes de la population (reactivite) et assurer l’equite de la participation financiere. Ameliorer la sante signifie a la fois ameliorer l’etat de sante moyen et reduire les inegalites de sante. La reactivite comprend deux elements majeurs : a) le respect des personnes (dignite, confidentialite et droit des personnes et des familles a disposer de leur propre leur sante) ; b) l’orientation client (prise en charge immediate, acces aux reseaux d’aide sociale pendant les soins, qualite de l’environnement et choix du prestateur). La participation financiere est equitable si chaque menage paie une juste part des depenses de sante totales d’un pays (il se peut donc que les menages tres pauvres ne paient rien du tout), ce qui suppose une protection universelle contre les risques financiers que presentent les soins de sante. Pour mesurer la performance, on etablit une relation entre la realisation des objectifs et les ressources disponibles. Les ecarts de performance dependent de la facon dont le systeme de sante exerce quatre grandes fonctions : l’administration generale (concept plus large que celui de regulation), le financement (perception des recettes, mise en commun des fonds et achats), la prestation de services (services de sante individuels et collectifs) et la creation de ressources (personnel, equipements et savoir). L’examen de ces quatre fonctions et de la facon dont elles se conjuguent permet non seulement de connaitre les determinants directs de la performance du systeme de sante, mais aussi de prevoir des reformes majeures.

4 citations