Research Article: What Is the Future for Global Case Management Guidelines for Common Childhood Diseases?

Date Published: December 9, 2008

Publisher: Public Library of Science

Author(s): Mike English, J. Anthony G Scott

Abstract: Mike English and J. Anthony G. Scott propose a framework for national surveillance, monitoring, and research that could help inform guideline development in low-income settings.

Partial Text: Others have made the point convincingly that Millennium Development Goal 4, a reinvigorated commitment to reduce child mortality by two-thirds before 2015, could be achieved if existing interventions were implemented on a massive scale [1,2]. Widespread access to simple therapeutic interventions, in accordance with World Heath Organization (WHO) case management guidelines, is a substantial part of this package. Assuming that the coverage of existing interventions can be improved, what will be the next major challenge? We believe it will be enabling groups of countries, individual countries, or even large states to take increasing responsibility for the future of their case management strategies. Here we bring together insights from a wide range of disciplines to propose a framework for national surveillance, monitoring, and research that could help inform guideline development in low-income settings. Although our focus is on childhood illness, the principles might be applied more widely.

WHO guidelines for common childhood illnesses were developed over several decades. A high burden of disease in settings with basic biomedical health systems demanded management strategies that were simple, safe, and inexpensive to achieve high coverage. Often the aim was high diagnostic sensitivity at the expense, to a degree, of specificity. However, much of the research underpinning the actual content of current guidelines was undertaken in the 1980s and early 1990s, and often considerable reliance was placed not on evidence but on expert opinion [3,4]. Three factors now undermine the relevance of this foundation.

The science of guidelines is a relatively new discipline [14] that seeks to combine clinical, behavioural, and implementation research. New institutions such as the National Institute for Health and Clinical Excellence (http://www.nice.org.uk/) and the Agency for Healthcare Research and Quality (http://www.ahrq.gov/) have arisen to evaluate the population benefits of novel therapies. WHO has adopted this new science. In a 2006 journal supplement, WHO commissioned 16 reports to enunciate best practices for each step and methodology underpinning guideline development (http://www.health-policy-systems.com/articles/browse.asp?volume=4). We now illustrate some consequences of these changes in developing new guidelines for sick children.

The development of WHO’s first generation of simple case management guidelines represented the culmination of considerable formative research, and their impact has been considerable. However, no comprehensive process for evaluation, revision, or refinement was established at introduction, despite the fact that they are applied globally to hundreds of millions of episodes of pneumonia, diarrhoea, and malaria every year [22–24]. As the epidemiological landscape diversifies we will need appropriate evidence to adapt treatment guidelines for these millions of children so that the guidelines are optimally effective at regional or country, not continental, level. Strengthening this process may foster, through increased ownership, a virtuous cycle that generates demand for better data and improves the value and specification of models. As a starting point, models should be used to identify quickly those decision points and data that are most critical to the determination of costs and outcomes.

We have heard many calls for, and seen considerable resources devoted to, improving data to inform often vertical global health monitoring exercises. In order to determine health policy, industrialised countries are investing in systems to acquire their own data on the burden of diseases and the costs of interventions. This is not an expression of nationalism but a recognition that diseases and health systems vary across and even within countries. As low-income countries develop, they will also desire local data for this purpose to use in conjunction with other data available from international collaboration or synthesis. The question that we have posed is: how do we anticipate this need and its consequences for the evolution of health systems in low-income countries? We have argued that two simple approaches will carry this forward: the development of population-based models of health systems and the acquisition of relatively simple local data on the burden of disease, the effectiveness of simple curative practices, their cost, and pattern of usage. The models proposed combine international and local data and could lead, in turn, to a greater demand by policy makers for more and better data. Given the economic constraints it will be necessary to share data across regions for some time, especially the findings of major research studies. Initial investment in local health data will be required to foster the evolution of guidelines and policy in low-income countries. This challenges us to strengthen our support for clinical health systems research at country level, within ministries of health, and in public service and academic institutions. Low-income countries will need better trained epidemiologists, health economists, clinical epidemiologists, and behavioural and laboratory scientists who are able to gather, utilise, and interpret data from their region. The responsibility for this lies with all involved in improving global health and also depends on the countries themselves who, by application of simple health system models, create the demand for better care through better data.

Source:

http://doi.org/10.1371/journal.pmed.0050241

 

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