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Background: The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment.Discussion: We present an architectural framework for LHSs that incorporates five dimensions-goals, scientific, social, technical, and ethical-commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making.Conclusion: In this paper, we outline a high-level architectural framework grounded in conceptual and empirical LHS literature. Applying this architectural framework can guide the development and implementation of new LHSs and the evolution of existing ones, as it allows for clear and critical understanding of the types of decisions that underlie LHS operations. Further research is required to assess and refine its generalizability and methods. [ABSTRACT FROM AUTHOR]

Background: The use of health policy and systems research (HPSR) to support decision making in health systems is limited in the Eastern Mediterranean Region (EMR). This is partly due to the lack of effective initiatives to strengthen regional HPSR capacities and promote its use in decision making. This paper offers a structured reflection on the establishment and core functioning of a HPSR Nodal Institute for the EMR with specific focus on the approach used to support the conduct and use of HPSR. It seeks to gain better understanding of the activities conducted by the Nodal Institute, the methods by which the Nodal Institute implemented these activities, and the outcomes of these activities.Methods: A multi-faceted approach was implemented by the Nodal Institute in collaboration with regional academic/research institutions, Sub-Nodes. The overall approach was a phased one that included the selection of Sub-Nodes, mapping of academic/research institutions in the EMR, stakeholders' meetings, and HPSR capacity building workshops, and culminated with a regional meeting.Results: The mapping of academic/research institutions in the EMR resulted in the identification of 50 institutions, of which only 32 were engaged in HPSR. These institutions have the highest HPSR involvement in information/evidence (84%) and the lowest in human resources for health (34%). Their main HPSR focus areas included quality of healthcare services, patient safety, management of non-communicable diseases, and human resources for health. Regional HPSR challenges among these institutions were identified. The validation and ranking questionnaires resulted in the identification of country-specific HPSR priorities according to stakeholders in three countries. From these results, cross-cutting HPSR priorities among the countries related to primary healthcare, non-communicable diseases, human resources for health, as well as cross-cutting HPSR priorities among stakeholders and according to stakeholders of the countries, were extracted.Conclusion: The Nodal Institute in the EMR is a promising initiative to support the conduct and use of HPSR in health policies. The approach and findings reported in this paper allow for the development of opportunities towards the building of capacity for HPSR in the region and other countries and provide a roadmap for academic/research institutions interested in HPSR in the region. [ABSTRACT FROM AUTHOR]

Background: While there have been efforts to develop frameworks to guide healthcare priority setting; there has been limited focus on evaluation frameworks. Moreover, while the few frameworks identify quality indicators for successful priority setting, they do not provide the users with strategies to verify these indicators. Kapiriri and Martin (Health Care Anal 18:129-147, 2010) developed a framework for evaluating priority setting in low and middle income countries. This framework provides BOTH parameters for successful priority setting and proposes means of their verification. Before its use in real life contexts, this paper presents results from a validation process of the framework.Methods: The framework validation involved 53 policy makers and priority setting researchers at the global, national and sub-national levels (in Uganda). They were requested to indicate the relative importance of the proposed parameters as well as the feasibility of obtaining the related information. We also pilot tested the proposed means of verification.Results: Almost all the respondents evaluated all the parameters, including the contextual factors, as 'very important'. However, some respondents at the global level thought 'presence of incentives to comply', 'reduced disagreements', 'increased public understanding,' 'improved institutional accountability' and 'meeting the ministry of health objectives', which could be a reflection of their levels of decision making. All the proposed means of verification were assessed as feasible with the exception of meeting observations which would require an insider. These findings results were consistent with those obtained from the pilot testing.Conclusions: These findings are relevant to policy makers and researchers involved in priority setting in low and middle income countries. To the best of our knowledge, this is one of the few initiatives that has involved potential users of a framework (at the global and in a Low Income Country) in its validation. The favorable validation of all the parameters at the national and sub-national levels implies that the framework has potential usefulness at those levels, as is. The parameters that were disputed at the global level necessitate further discussion when using the framework at that level. The next step is to use the validated framework in evaluating actual priority setting at the different levels. [ABSTRACT FROM AUTHOR]

Background: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim: The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods: This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). Results: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection. [ABSTRACT FROM AUTHOR]

Background: The reduction of health inequalities is a focus of many national and international health organisations. The need for pragmatic evidence-based approaches has led to the development of a number of evidence-based equity initiatives. This paper describes a new program that focuses upon evidencebased tools, which are useful for policy initiatives that reduce inequities. Methods: This paper is based on a presentation that was given at the "Regional Consultation on Policy Tools: Equity in Population Health Reports," held in Toronto, Canada in June 2002. Results: Five assessment tools were presented. 1. A database of systematic reviews on the effects of educational, legal, social, and health interventions to reduce unfair inequalities is being established through the Cochrane and Campbell Collaborations. 2 Decision aids and shared decision making can be facilitated in disadvantaged groups by 'health coaches' to help people become better decision makers, negotiators, and navigators of the health system; a pilot study in Chile has provided proof of this concept. 3. The CIET Cycle: Combining adapted cluster survey techniques with qualitative methods, CIET's population based applications support evidence-based decision making at local and national levels. The CIET map generates maps directly from survey or routine institutional data, to be used as evidence-based decisions aids. Complex data can be displayed attractively, providing an important tool for studying and comparing health indicators among and between different populations. 4. The Ottawa Equity Gauge is applying the Global Equity Gauge Alliance framework to an industrialised country setting. 5 The Needs-Based Health Assessment Toolkit, established to assemble information on which clinical and health policy decisions can be based, is being expanded to ensure a focus on distribution and average health indicators. Conclusion: Evidence-based planning tools have much to offer the goal of equitable health development. [ABSTRACT FROM AUTHOR]

Background: Building research capacity in health services has been recognised internationally as important in order to produce a sound evidence base for decision making in policy and practice. Activities to increase research capacity for, within, and by practice include initiatives to support individuals and teams, organisations and networks. Little has been discussed or concluded about how to measure the effectiveness of research capacity building (RCB) Discussion: This article attempts to develop the debate on measuring RCB. It highlights that traditional outcomes of publications in peer reviewed journals and successful grant applications may be important outcomes to measure, but they may not address all the relevant issues to highlight progress, especially amongst novice researchers. They do not capture factors that contribute to developing an environment to support capacity development, or on measuring the usefulness or the 'social impact' of research, or on professional outcomes. The paper suggests a framework for planning change and measuring progress, based on six principles of RCB, which have been generated through the analysis of the literature, policy documents, empirical studies, and the experience of one Research and Development Support Unit in the UK. These principles are that RCB should: develop skills and confidence, support linkages and partnerships, ensure the research is 'close to practice', develop appropriate dissemination, invest in infrastructure, and build elements of sustainability and continuity. It is suggested that each principle operates at individual, team, organisation and supra organisational levels. Some criteria for measuring progress are also given. Summary: This paper highlights the need to identify ways of measuring RCB. It points out the limitations of current measurements that exist in the literature, and proposes a framework for measuring progress, which may form the basis of comparison of RCB activities. In this way it could contribute to establishing the effectiveness of these interventions, and establishing a knowledge base to inform the science of RCB. [ABSTRACT FROM AUTHOR]

Background: Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process.Discussion: We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence.Summary: In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved. [ABSTRACT FROM AUTHOR]

Context: The Kenya Partnership for Health (KPH) program began in 1999, and is currently one of the 12 field projects participating in the WHO's 'Towards Unity for Health initiative' implemented to develop partnership synergies in support of the Primary Health Care (PHC) approach [1]. Content: This paper illustrates how Program-linked Information Management by Integrative-participatory Research Approach (PIMIRA) as practised under KPH has been implemented within Trans-Nzoia District, Kenya to enhance community-based health initiatives. It shows how this model is strategically being scaled-up from one community to another in the management of political, social, cultural and economic determinants (barriers and enhancers) of health. Objective: Target rural communities in the development of a community-based health information management and feedback initiatives that can provide insights on the social, cultural, political and economic determinants of health for utilization in informed health service management. Key Findings and Achievements: 1. Cues for health seeking and health service utilization are determined by the social, cultural, political and economic factors as seen by the individual and as defined by the community but not due to the pathological nature of the illness. 2. Establishment of community-based health surveillance and health action initiatives as the best practices in transferring health as a resource that can be 'owned and guarded' by the community. 3. Establishment of Healthy Villages Initiative (HVI) through which health service delivery and scale-up can be sustained at the community level. 4. Provision of actionable health information necessary for health planning and evaluation of preventive health programs thorough PIMIRA. Conclusion: It has been realized that for every one person who visits a health facility for medication, there are nine others who had the same condition but sought health care from other sources including self-medication and five others who never sought health care. Innovative means of involving the community in health information management and utilization such as PIMIRA are hence the best ways of guaranteeing equitable delivery of health services that are accessible and sustainable by the community. [ABSTRACT FROM AUTHOR]

Background: To increase the uptake of research evidence in practice, responsive research services have been developed within universities that broker access to academic expertise for practitioners and decision-makers. However, there has been little examination of the process of knowledge brokering within these services. This paper reflects on this process within the AskFuse service, which was launched in June 2013 by Fuse, the Centre for Translational Research in Public Health, in North East England. The paper outlines the challenges and opportunities faced by both academics and health practitioners collaborating through the service.Methods: The authors reflected on conversations between the AskFuse Research Manager and policy and practice partners accessing the service between June 2013 and March 2017. Summary notes of these conversations, including emails and documents relating to over 240 enquiries, have been analysed using an auto-ethnographic approach.Findings: We identified five challenges to knowledge brokering in an institutional service, namely length of brokerage time required, limits to collaboration, lack of resources, brokering research in a changing system, and multiple types of knowledge.Conclusions: To understand and overcome some of the identified challenges, we employ Goffman's dramaturgical perspective and argue for making better use of the distinction between front and back stages in the knowledge brokering process. We emphasise the importance of back stages for defusing destructive information that could discredit collaborative performances. [ABSTRACT FROM AUTHOR]