1.1.1. Health information

Health information is a subset of evidence that encompasses data and indicators related to socioeconomic determinants of health; health status/mortality of individuals and populations; risk factors; service coverage; and health system inputs, outputs and outcomes (8,9). It is collected, processed, stored, reported and used with the aim of influencing policy- and decision-making, programme action and efficient resource allocation, ultimately for improving health outcomes (8). Health information systems provide the underpinnings for decision-making and have four key functions: data generation; data compilation; analysis and synthesis; and communication and use. The health information system collects data from the health sector and other relevant sectors, analyses the data and ensures their overall quality, relevance and timeliness, and finally converts the data into information for health-related decision-making (10). The health information system is heavily biased towards quantitative (longitudinal) data, which can be disaggregated by sex, age and socioeconomic characteristics (8). These data may be used by researchers, data analysts, public health managers or policy-makers to:

• describe the scope and magnitude of health conditions and their geographical and demographical distribution;
• explore the associations between health outcomes and risk or protective factors; and
• assess the effectiveness of public health interventions.

Some of the common sources of health information for policy are census data, birth and death records, public health and behavioural surveillance data, service-generated data from public health facilities, national health accounts and household surveys (8). A health observatory is an institutional mechanism that can help to incorporate health information into policy-making and can undertake public health monitoring by producing, assembling and analysing information on health outcomes and their determinants (11). Observatories can be governmental, nongovernmental or academic entities that monitor health trends, identify gaps in health information, provide guidance on the appropriate methods to be used and integrate population-based (e.g. vital statistics, censuses and sociodemographic surveys) and institution-based data from both within and outside the health sector. Emerging models show that decision-makers can also be active and contributing coproducers of new information for public health decision-making (12). Such collaboration in a functioning health information system can enhance the richness, relevance and real-world applicability of health information.

1.1.2. The use of health information in policy-making

Policy development is an extended, iterative process, and, therefore, health information can influence policy at multiple points in this process (13,14). Typically, policy-makers use health information to identify the need for policy action, to formulate a policy, to implement it in a feasible way (e.g. by using health information to create awareness and mobilize communities) and finally to determine how effective a policy is in terms of addressing the problem in question (14). Importantly, health information can be used at the early agenda-setting stage to frame the magnitude of the health problem and also at midterm and ex-post policy evaluation stages to assess various aspects of the implemented policy, such as change in burden or cost–effectiveness of the new intervention. The outcome of the evaluation, in turn, may lead to setting new policy agendas or adjusting the existing policy (14). A functioning health information system, therefore, involves policy-makers who request health information and who can evaluate its relevance, interpret it and use it for feedback into policy.

However, the availability of good-quality health information does not inherently lead to an increased uptake by policy-makers. In order for such uptake to occur, interventions in the technical, behavioural and organizational domains are necessary (15). The technical domain includes systems or processes to collect and review health information and to ensure the quality of such information (e.g. in terms of its interpretability, timeliness, completeness, accuracy, validity and relevance). The behavioural domain relates to the attitudes and capacity of information producers and end-users when using data to solve problems and improve programmes. Finally, the organizational domain concerns the structure and processes of the organizations that use the data.

1.1.3. Modalities

Mechanisms and tools to support evidence-informed policy-making may take different forms and may be driven by different stakeholder groups. Additionally, they may have different modalities. Tools may be used in response to push activities by producers of research data and health information or pull actions from data users to establish links between evidence and action (16). For example, an evidence brief may be created by information producers on their own initiative on topics of their choice (push efforts) or may be commissioned by policy-makers based on exact specifications (pull efforts) (17). The producer push modality may be passive, for example through posts on organizational websites, academic publications and conference presentations, or it may involve active promotion and communication through the preparation of policy briefs, targeted mail to policy-makers or sharing results on health information exchange platforms. Producers may facilitate user pull by providing access to health data and information (e.g. setting up rapid response units to meet users’ needs) and contribute to training of users to create capacity to acquire, assess and use evidence in decision-making (17).

Push and pull activities may also coexist in a modality termed exchange. In this case, producers and policy-makers work in real partnership, often facilitated by knowledge intermediaries or brokers, with division lines between stakeholders becoming fuzzy. They may co-design approaches to generate evidence and execute the necessary steps together, from agenda setting to implementation (16).

Finally, when knowledge translation platforms, incorporating elements of push, pull or exchange efforts, are institutionalized in an organization or in the broader health system, the modality is known as integrated efforts (17). Integrated efforts include setting up a transparent governance structure with key stakeholders represented, establishing a clear objective for action, regularly assessing priorities to ensure that efforts remain relevant, and facilitating both push and pull efforts.

1.1.4. The objective of this report

While there is extensive literature on how to translate knowledge of research-based evidence into policy, there is limited literature on how to incorporate health information into policy, particularly on suitable tools and mechanisms by which that integration can be accomplished. This report aims to fill this gap by undertaking a systematic literature review to describe the tools and mechanisms that can help to increase the use of health information in health systems and policies. In doing so, it is assumed that health information is of quality, available and accessible, and attention is focused on the tools and mechanisms that facilitate the uptake of health information by policy-makers.

Considering the complexity of health information, health information systems and stakeholder types (e.g. governments, health policy-makers, health professionals, knowledge brokers, nongovernmental organizations (NGOs), researchers, patients and the wider community), a broad typology has been devised to catalogue the tools and mechanisms and to describe these with their modalities and intended outcomes. The use of research and health information tools is illustrated with real-world examples to provide guidance to policy-makers for future applications.