This paper sought to investigate the feasibility, the ease of implementation, and the extent to which community health workers with little experience of data collection could be trained and successfully supervised to collect data using mobile phones in a large baseline survey. A web-based system was developed to allow electronic surveys or questionnaires to be designed (on a word processor), sent to, and conducted on standard entry level mobile phones. The web-based interface permitted comprehensive daily real-time supervision of CHW performance, with no data loss. The system permitted the early detection of data errors in combination with real-time quality control and data collector supervision. In conclusion, the benefits of mobile technology, combined with the improvement that mobile phones offer over personal digital assistants (PDAs) – or palmtop computers – in terms of data loss and uploading difficulties, make mobile phones a feasible method of data collection that needs to be further explored.
Monitoring equity and research policy
This paper studied policymaking processes in Mozambique, South Africa and Zimbabwe to understand the factors affecting the use of research evidence in national policy development, with a particular focus on the findings from randomised control trials. It used a qualitative case-study methodology to explore the policy-making process. It carried out key informants interviews with a range of research and policy stakeholders in each country, reviewed documents and developed timelines of key events. Prior experience of particular interventions, local champions, stakeholders and international networks, and the involvement of researchers in policy development were important in knowledge translation for both case studies. In contrast to treatment policies for eclampsia, a diverse group of stakeholders with varied interests, differing in their use and interpretation of evidence, was involved in malaria policy decisions in the three countries. The paper concluded that translating research knowledge into policy is a complex and context sensitive process. Researchers aiming to enhance knowledge translation need to be aware of factors influencing the demand for different types of research; interact and work closely with key policy stakeholders, networks and local champions; and acknowledge the roles of important interest groups.
This paper aims to assess current priority setting methods and the extent to which they adequately include health policy and systems research (HPSR) and to draw out lessons regarding how HPSR priority setting can be enhanced to promote relevant HPSR and to strengthen developing country leadership of research agendas. Priority setting processes can be distinguished by the level at which they occur, their degree of comprehensiveness in terms of the topic addressed, the balance between technical versus interpretive approaches and the stakeholders involved. When HPSR is considered through technical, disease-driven priority setting processes it is systematically under-valued. More successful approaches for considering HPSR are typically nationally driven, interpretive and engage a range of stakeholders. There is still a need however for better defined approaches to enable research funders to determine the relative weight to assign to disease specific research versus HPSR and other forms of cross-cutting health research. While country-level research priority setting is key, there is likely to be a continued need for the identification of global research priorities for HPSR. The paper argues that such global priorities can and should be driven by country level priorities.
Performance targets for global TB control were first formulated in 1991 at the 44th World Health Assembly. National TB control programmes were encouraged to achieve CDRs of at least 70% and cure rates in excess of 85%. However, even in situations where both targets were reached and achievements sustained, incidence rates failed to decline as predicted. The vast differences that exist between endemic and non-endemic areas (in other words, case density) and the impact this has on transmission dynamics within communities are rarely appreciated. Most source cases have fairly fixed circles of social interaction. This implies that once the majority of close contacts have been infected, the risk of infecting new people may decline even though the source case remains highly infectious. This phenomenon is referred to as transmission saturation. There is a need to reconsider the accuracy and applicability of current mathematical models and to identify pragmatic ways of quantifying additional factors that may be at play in endemic areas. The incorporation of case density and transmission saturation in future mathematical models may assist.
This article addresses considerations of equity. Policies or programmes that are effective can improve the overall health of a population. However, the impact of such policies and programmes on inequities may vary: they may have no impact on inequities, they may reduce inequities, or they may exacerbate them, regardless of their overall effects on population health. Four questions are proposed as useful to guide equity analysis: Which groups or settings are likely to be disadvantaged in relation to the option being considered? Are there plausible reasons for anticipating differences in the relative effectiveness of the option for disadvantaged groups or settings? Are there likely to be different baseline conditions across groups or settings such that that the absolute effectiveness of the option would be different, and the problem more or less important, for disadvantaged groups or settings? Are there important considerations that should be made when implementing the option in order to ensure that inequities are reduced, if possible, and that they are not increased?
This article addresses the use of evidence to inform judgements about the balance between the pros and cons of policy and programme options. It suggests five questions that can be considered when making these judgements: What are the options that are being compared? What are the most important potential outcomes of the options being compared? What is the best estimate of the impact of the options being compared for each important outcome? How confident can policymakers and others be in the estimated impacts? Is a formal economic model likely to facilitate decision making?
This article addresses the issue of decision making in situations in which there is insufficient evidence at hand. Policymakers often have insufficient evidence to know with certainty what the impacts of a health policy or programme option will be, but they must still make decisions. The article suggests four questions that can be considered when there may be insufficient evidence to be confident about the impacts of implementing an option: Is there a systematic review of the impacts of the option? Has inconclusive evidence been misinterpreted as evidence of no effect? Is it possible to be confident about a decision despite a lack of evidence? Is the option potentially harmful, ineffective or not worth the cost?
The term monitoring is commonly used to describe the process of systematically collecting data to inform policymakers, managers and other stakeholders whether a new policy or programme is being implemented in accordance with their expectations. Indicators are used for monitoring purposes to judge, for example, if objectives are being achieved, or if allocated funds are being spent appropriately. Sometimes the term evaluation is used interchangeably with the term monitoring, but the former usually suggests a stronger focus on the achievement of results. When the term impact evaluation is used, this usually implies that there is a specific attempt to try to determine whether the observed changes in outcomes can be attributed to a particular policy or programme. This article suggests four questions that can be used to guide the monitoring and evaluation of policy or programme options: Is monitoring necessary? What should be measured? Should an impact evaluation be conducted? How should the impact evaluation be done?
This article discusses three questions: What is evidence? What is the role of research evidence in informing health policy decisions? What is evidence-informed policymaking? Evidence-informed health policymaking is an approach to policy decisions that aims to ensure that decision making is well-informed by the best available research evidence. It is characterised by the systematic and transparent access to, and appraisal of, evidence as an input into the policymaking process. The overall process of policymaking is not assumed to be systematic and transparent. However, within the overall process of policymaking, systematic processes are used to ensure that relevant research is identified, appraised and used appropriately. These processes are transparent in order to ensure that others can examine what research evidence was used to inform policy decisions, as well as the judgements made about the evidence and its implications. Evidence-informed policymaking helps policymakers gain an understanding of these processes.
This article addresses ways of organising efforts to support evidence-informed health policymaking. Efforts to link research to action may include a range of activities related to the production of research that is both highly relevant to – and appropriately synthesised for – policymakers. Such activities may include a mix of efforts used to link research to action, as well as the evaluation of such efforts. The article suggests five questions that can help guide considerations of how to improve organisational arrangements to support the use of research evidence to inform health policy decision making: What is the capacity of your organisation to use research evidence to inform decision making? What strategies should be used to ensure collaboration between policymakers, researchers and stakeholders? What strategies should be used to ensure independence as well as the effective management of conflicts of interest? What strategies should be used to ensure the use of systematic and transparent methods for accessing, appraising and using research evidence? What strategies should be used to ensure adequate capacity to employ these methods?