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      Improving the use of health data for health system strengthening

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          Abstract

          Background

          Good quality and timely data from health information systems are the foundation of all health systems. However, too often data sit in reports, on shelves or in databases and are not sufficiently utilised in policy and program development, improvement, strategic planning and advocacy. Without specific interventions aimed at improving the use of data produced by information systems, health systems will never fully be able to meet the needs of the populations they serve.

          Objective

          To employ a logic model to describe a pathway of how specific activities and interventions can strengthen the use of health data in decision making to ultimately strengthen the health system.

          Design

          A logic model was developed to provide a practical strategy for developing, monitoring and evaluating interventions to strengthen the use of data in decision making. The model draws on the collective strengths and similarities of previous work and adds to those previous works by making specific recommendations about interventions and activities that are most proximate to affect the use of data in decision making. The model provides an organizing framework for how interventions and activities work to strengthen the systematic demand, synthesis, review, and use of data.

          Results

          The logic model and guidance are presented to facilitate its widespread use and to enable improved data-informed decision making in program review and planning, advocacy, policy development. Real world examples from the literature support the feasible application of the activities outlined in the model.

          Conclusions

          The logic model provides specific and comprehensive guidance to improve data demand and use. It can be used to design, monitor and evaluate interventions, and to improve demand for, and use of, data in decision making. As more interventions are implemented to improve use of health data, those efforts need to be evaluated.

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          Most cited references48

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          The in-between world of knowledge brokering.

          J Lomas (2007)
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            Implementing information systems in health care organizations: myths and challenges.

            Marc Berg (2001)
            Successfully implementing patient care information systems (PCIS) in health care organizations appears to be a difficult task. After critically examining the very notions of 'success' and 'failure', and after discussing the problematic nature of lists of 'critical success- or failure factors', this paper discusses three myths that often hamper implementation processes. Alternative insights are presented, and illustrated with concrete examples. First of all, the implementation of a PCIS is a process of mutual transformation; the organization and the technology transform each other during the implementation process. When this is foreseen, PCIS implementations can be intended strategically to help transform the organization. Second, such a process can only get off the ground when properly supported by both central management and future users. A top down framework for the implementation is crucial to turn user-input into a coherent steering force, creating a solid basis for organizational transformation. Finally, the management of IS implementation processes is a careful balancing act between initiating organizational change, and drawing upon IS as a change agent, without attempting to pre-specify and control this process. Accepting, and even drawing upon, this inevitable uncertainty might be the hardest lesson to learn.
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              Assessing country-level efforts to link research to action.

              We developed a framework for assessing country-level efforts to link research to action. The framework has four elements. The first element assesses the general climate (how those who fund research, universities, researchers and users of research support or place value on efforts to link research to action). The second element addresses the production of research (how priority setting ensures that users' needs are identified and how scoping reviews, systematic reviews and single studies are undertaken to address these needs). The third element addresses the mix of four clusters of activities used to link research to action. These include push efforts (how strategies are used to support action based on the messages arising from research), efforts to facilitate "user pull" (how "one-stop shopping" is provided for optimally packaged high-quality reviews either alone or as part of a national electronic library for health, how these reviews are profiled during "teachable moments" such as intense media coverage, and how rapid-response units meet users' needs for the best research), "user pull" efforts undertaken by those who use research (how users assess their capacity to use research and how structures and processes are changed to support the use of research) and exchange efforts (how meaningful partnerships between researchers and users help them to jointly ask and answer relevant questions). The fourth element addresses approaches to evaluation (how support is provided for rigorous evaluations of efforts to link research to action).
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                Author and article information

                Journal
                Glob Health Action
                Glob Health Action
                GHA
                Global Health Action
                Co-Action Publishing
                1654-9716
                1654-9880
                13 February 2013
                2013
                : 6
                : 10.3402/gha.v6i0.20001
                Affiliations
                [1 ]MEASURE Evaluation, Futures Group, Chapel Hill, NC, USA
                [2 ]MEASURE Evaluation, Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
                Author notes
                [* ] Tara Nutley, MEASURE Evaluation, Futures Group, 308 West Rosemary Street, Suite 203, Chapel Hill, NC 27516, USA. Email: tnutley@ 123456futuresgroup.com
                Article
                20001
                10.3402/gha.v6i0.20001
                3573178
                23406921
                6be13b45-defa-425b-89c4-2fbeda5e0ba7
                © 2013 Tara Nutley and Heidi W. Reynolds

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 November 2012
                : 27 December 2012
                : 18 January 2013
                Categories
                Original Article

                Health & Social care
                data-informed decision making,data use,guidance,health information systems,health systems strengthening,logic model

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