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      A systems approach to assessing complexity in health interventions: an effectiveness decay model for integrated community case management

      research-article
      a , b , a , b , a , b , a , b
      Global Health Action
      Taylor & Francis
      iCCM, systems thinking tools, bottleneck analysis, sankey diagram, process mapping, data visualization

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          ABSTRACT

          Complexity is inherent to any system or program. This is especially true of integrated interventions, such as integrated community case management (iCCM). iCCM is a child health strategy designed to provide services through community health workers (CHWs) within hard-to-reach areas of low-and-middle-income countries (LMICs). It is comprised of many interlinked program components, processes and stakeholders. Elucidating the complexity of such programs is essential to designing interventions that respond to local contexts and successfully plan for sustainable integration. A pragmatic approach has yet to be developed that holistically assesses the many dimensions of iCCM or other integrated programs, their alignment with local systems, and how well they provide effective care. We propose an accessible systems approach to both measuring systems effectiveness and assessing its underlying complexity using a combination of systems thinking tools. We propose an effectiveness decay model for iCCM implementation to measure where patient loss occurs along the trajectory of care. The approach uses process mapping to examine critical bottlenecks of iCCM processes, their influence on effectiveness decay, and their integration into local systems; regression analysis and structural equation modeling to determine effects of key indicators on programmatic outcomes; and qualitative analysis with causal loop diagramming to assess stakeholder dynamics and their interactions within the iCCM program. An accurate assessment of the quality, effectiveness, and strength of community-based interventions relies on more than measuring core indicators and program outcomes; it requires an exploration of how its actors and core components interact as part of a system. Our approach produces an interactive iCCM effectiveness decay model to understand patient loss in context, examines key systems issues, and uses a range of systems thinking tools to assess the dynamic interactions that coalesce to produce observed program outcomes.

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          Most cited references38

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          Health service coverage and its evaluation.

          Health service coverage is considered as a concept expressing the extent of interaction between the service and the people for whom it is intended, this interaction not being limited to a particular aspect of service provision but ranging over the whole process from resource allocation to achievement of the desired objective. For the measurement of coverage, several key stages are first identified, each of them involving the realization of an important condition for providing the service; a coverage measure is then defined for each stage, namely the ratio between the number of people for whom the condition is met and the target population, so that a set of these measures represents the interaction between the service and the target population. This definition of coverage allows for variations, which are called "specific coverage", by limiting the target population to specific subgroups differentiated by certain conditions related to service provision or by demographic or socioeconomic factors.The evaluation of coverage on the basis of these concepts enables management to identify bottlenecks in the operation of the service, to analyse the constraining factors responsible for such bottlenecks, and to select effective measures for service development.
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            Building the Field of Health Policy and Systems Research: Framing the Questions

            In the first of a series of articles addressing the current challenges and opportunities for the development of Health Policy & Systems Research (HPSR), Kabir Sheikh and colleagues lay out the main questions vexing the field.
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              Implementation fidelity in community-based interventions.

              Implementation fidelity is the degree to which an intervention is delivered as intended and is critical to successful translation of evidence-based interventions into practice. Diminished fidelity may be why interventions that work well in highly controlled trials may fail to yield the same outcomes when applied in real life contexts. The purpose of this paper is to define implementation fidelity and describe its importance for the larger science of implementation, discuss data collection methods and current efforts in measuring implementation fidelity in community-based prevention interventions, and present future research directions for measuring implementation fidelity that will advance implementation science. (c) 2010 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                Glob Health Action
                Glob Health Action
                Global Health Action
                Taylor & Francis
                1654-9716
                1654-9880
                10 August 2020
                2020
                : 13
                : 1
                : 1794106
                Affiliations
                [a ]Department of Epidemiology & Public Health, Swiss Tropical and Public Health Institute (Swiss TPH); , Basel, Switzerland
                [b ]Department of Epidemiology & Public Health, University of Basel; , Basel, Switzerland
                Author notes
                CONTACT Aliya Karim aliya.karim@ 123456swisstph.ch Swiss Tropical & Public Health Institute; , Basel4051, Switzerland
                Author information
                https://orcid.org/0000-0002-3665-217X
                https://orcid.org/0000-0002-5920-1304
                https://orcid.org/0000-0001-5639-5337
                https://orcid.org/0000-0002-6903-4722
                Article
                1794106
                10.1080/16549716.2020.1794106
                7480477
                32772891
                db4c3110-49c3-4325-8f99-b26dac19c69f
                © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 7, Tables: 2, References: 65, Pages: 1
                Categories
                Research Article
                Study Design Article

                Health & Social care
                iccm,systems thinking tools,bottleneck analysis,sankey diagram,process mapping,data visualization

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