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Christopher JL Murray

Publications and source records attributed to Christopher JL Murray.

6 recordsLinked to original sources

Introduction of article-processing charges for Population Health Metrics.

Population Health Metrics is an open-access online electronic journal published by BioMed Central - it is universally and freely available online to everyone, its authors retain copyright, and it is archived in at least one internationally recognised free repository. To fund this, from November 1 2003, authors of articles accepted for publication will be asked to pay an article-processing charge of US$500. This editorial outlines the reasons for the introduction of article-processing charges and the way in which this policy will work.Waiver requests will be considered on a case-by-case basis, by the Editor-in-Chief. Article-processing charges will not apply to authors whose institutions are 'members' of BioMed Central. Current members include NHS England, the World Health Organization, the US National Institutes of Health, Harvard, Princeton and Yale universities, and all UK universities. No charge is made for articles that are rejected after peer review. Many funding agencies have also realized the importance of open access publishing and have specified that their grants may be used directly to pay APCs.

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Comparative quantification of health risks conceptual framework and methodological issues.

Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability.In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty.

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A generic model for the assessment of disease epidemiology: the computational basis of DisMod II.

Epidemiology as an empirical science has developed sophisticated methods to measure the causes and patterns of disease in populations. Nevertheless, for many diseases in many countries only partial data are available. When the partial data are insufficient, but data collection is not an option, it is possible to supplement the data by exploiting the causal relations between the various variables that describe a disease process. We present a simple generic disease model with incidence, one prevalent state, and case fatality and remission. We derive a set of equations that describes this disease process and allows calculation of the complete epidemiology of a disease given a minimum of three input variables. We give the example of asthma with age-specific prevalence, remission, and mortality as inputs. Outputs are incidence and case fatality, among others. The set of equations is embedded in a software package called 'DisMod II', which is made available to the public domain by the World Health Organization.

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Population health metrics: crucial inputs to the development of evidence for health policy.

Valid, reliable and comparable measures of the health states of individuals and of the health status of populations are critical components of the evidence base for health policy. We need to develop population health measurement strategies that coherently address the relationships between epidemiological measures (such as risk exposures, incidence, and mortality rates) and multi-domain measures of population health status, while ensuring validity and cross-population comparability.Studies reporting on descriptive epidemiology of major diseases, injuries and risk factors, and on the measurement of health at the population level - either for monitoring trends in health levels or inequalities or for measuring broad outcomes of health systems and social interventions - are not well-represented in traditional epidemiology journals, which tend to concentrate on causal studies and on quasi-experimental design. In particular, key methodological issues relating to the clear conceptualisation of, and the validity and comparability of measures of population health are currently not addressed coherently by any discipline, and cross-disciplinary debate is fragmented and often conducted in mutually incomprehensible language or paradigms. Population health measurement potentially bridges a range of currently disjoint fields of inquiry relating to health: biology, demography, epidemiology, health economics, and broader social science disciplines relevant to assessment of health determinants, health state valuations and health inequalities.This new journal will focus on the importance of a population based approach to measurement as a way to characterize the complexity of people's health, the diseases and risks that affect it, its distribution, and its valuation, and will attempt to provide a forum for innovative work and debate that bridge the many fields of inquiry relevant to population health in order to contribute to the development of valid and comparable methods for the measurement of population health and its determinants.

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Econometric estimation of country-specific hospital costs.

Information on the unit cost of inpatient and outpatient care is an essential element for costing, budgeting and economic-evaluation exercises. Many countries lack reliable estimates, however. WHO has recently undertaken an extensive effort to collect and collate data on the unit cost of hospitals and health centres from as many countries as possible; so far, data have been assembled from 49 countries, for various years during the period 1973-2000. The database covers a total of 2173 country-years of observations. Large gaps remain, however, particularly for developing countries. Although the long-term solution is that all countries perform their own costing studies, the question arises whether it is possible to predict unit costs for different countries in a standardized way for short-term use. The purpose of the work described in this paper, a modelling exercise, was to use the data collected across countries to predict unit costs in countries for which data are not yet available, with the appropriate uncertainty intervals.The model presented here forms part of a series of models used to estimate unit costs for the WHO-CHOICE project. The methods and the results of the model, however, may be used to predict a number of different types of country-specific unit costs, depending on the purpose of the exercise. They may be used, for instance, to estimate the costs per bed-day at different capacity levels; the "hotel" component of cost per bed-day; or unit costs net of particular components such as drugs.In addition to reporting estimates for selected countries, the paper shows that unit costs of hospitals vary within countries, sometimes by an order of magnitude. Basing cost-effectiveness studies or budgeting exercises on the results of a study of a single facility, or even a small group of facilities, is likely to be misleading.

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PopMod: a longitudinal population model with two interacting disease states.

This article provides a description of the population model PopMod, which is designed to simulate the health and mortality experience of an arbitrary population subjected to two interacting disease conditions as well as all other "background" causes of death and disability. Among population models with a longitudinal dimension, PopMod is unique in modelling two interacting disease conditions; among the life-table family of population models, PopMod is unique in not assuming statistical independence of the diseases of interest, as well as in modelling age and time independently. Like other multi-state models, however, PopMod takes account of "competing risk" among diseases and causes of death.PopMod represents a new level of complexity among both generic population models and the family of multi-state life tables. While one of its intended uses is to describe the time evolution of population health for standard demographic purposes (e.g. estimates of healthy life expectancy), another prominent aim is to provide a standard measure of effectiveness for intervention and cost-effectiveness analysis. PopMod, and a set of related standard approaches to disease modelling and cost-effectiveness analysis, will facilitate disease modelling and cost-effectiveness analysis in diverse settings and help make results more comparable.

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