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      Leveraging phone-based mobile technology to improve data quality at health facilities in rural Malawi: a best practice project

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          Abstract

          Background

          To further reduce malaria burden, identification of areas with highest burden for targeted interventions needs to occur. Routine health information has the potential to indicate where and when clinical malaria occurs the most. Developing countries mostly use paper-based data systems however they are error-prone as they require manual aggregation, tallying and transferring of data. Piloting was done using electronic data capture (EDC) with a cheap and user friendly software in rural Malawian primary healthcare setting to improve the quality of health records.

          Methods

          Audit and feedback tools from the Joanna Briggs Institute (Practical Application of Clinical Evidence System and Getting Research into Practice) were used in four primary healthcare facilities. Using this approach, the best available evidence for a malaria information system (MIS) was identified. Baseline audit of the existing MIS was conducted in the facilities based on available best practice for MIS; this included ensuring data consistency and completeness in MIS by sampling 25 random records of malaria positive cases. Implementation of an adapted evidence-based EDC system using tablets on an OpenDataKit platform was done. An end line audit following implementation was then conducted. Users had interviews on experiences and challenges concerning EDC at the beginning and end of the survey.

          Results

          The existing MIS was paper-based, occupied huge storage space, had some data losses due to torn out papers and were illegible in some facilities. The existing MIS did not have documentation of necessary parameters, such as malaria deaths and treatment within 14 days. Training manuals and modules were absent. One health centre solely had data completeness and consistency at 100% of the malaria-positive sampled records. Data completeness and consistency rose to 100% with readily available records containing information on recent malaria treatment. Interview findings at the end of the survey showed that EDC was acceptable among users and they agreed that the tablets and the OpenDataKit were easy to use, improved productivity and quality of care.

          Conclusions

          Improvement of data quality and use in the Malawian rural facilities was achieved through the introduction of EDC using OpenDataKit. Health workers in the facilities showed satisfaction with the use of EDC.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12936-021-03742-x.

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          Most cited references22

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          Outcomes for Implementation Research: Conceptual Distinctions, Measurement Challenges, and Research Agenda

          An unresolved issue in the field of implementation research is how to conceptualize and evaluate successful implementation. This paper advances the concept of “implementation outcomes” distinct from service system and clinical treatment outcomes. This paper proposes a heuristic, working “taxonomy” of eight conceptually distinct implementation outcomes—acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability—along with their nominal definitions. We propose a two-pronged agenda for research on implementation outcomes. Conceptualizing and measuring implementation outcomes will advance understanding of implementation processes, enhance efficiency in implementation research, and pave the way for studies of the comparative effectiveness of implementation strategies.
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            Guidelines for the Treatment of Malaria

            (2015)
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              Information Systems to Support Surveillance for Malaria Elimination

              Robust and responsive surveillance systems are critical for malaria elimination. The ideal information system that supports malaria elimination includes: rapid and complete case reporting, incorporation of related data, such as census or health survey information, central data storage and management, automated and expert data analysis, and customized outputs and feedback that lead to timely and targeted responses. Spatial information enhances such a system, ensuring cases are tracked and mapped over time. Data sharing and coordination across borders are vital and new technologies can improve data speed, accuracy, and quality. Parts of this ideal information system exist and are in use, but have yet to be linked together coherently. Malaria elimination programs should support the implementation and refinement of information systems to support surveillance and response and ensure political and financial commitment to maintain the systems and the human resources needed to run them. National malaria programs should strive to improve the access and utility of these information systems and establish cross-border data sharing mechanisms through the use of standard indicators for malaria surveillance. Ultimately, investment in the information technologies that support a timely and targeted surveillance and response system is essential for malaria elimination.
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                Author and article information

                Contributors
                t.tizifa@amsterdamumc.nl
                williamnkhono@hotmail.com
                smtengula@medcol.mw
                m.vanvugt@amsterdamumc.nl
                zachary.munn@adelaide.edu.au
                akabaghe@medcol.mw
                Journal
                Malar J
                Malar J
                Malaria Journal
                BioMed Central (London )
                1475-2875
                27 April 2021
                27 April 2021
                2021
                : 20
                : 203
                Affiliations
                [1 ]GRID grid.7177.6, ISNI 0000000084992262, Division of Internal Medicine, Department of Infectious Diseases, Center for Tropical Medicine and Travel Medicine, , University Medical Center, University of Amsterdam, ; Amsterdam, The Netherlands
                [2 ]GRID grid.10595.38, ISNI 0000 0001 2113 2211, Training and Research Unit of Excellence (TRUE), School of Public Health and Family Medicine, College of Medicine, , University of Malawi, ; Blantyre, Malawi
                [3 ]GRID grid.1010.0, ISNI 0000 0004 1936 7304, JBI, Faculty of Health and Medical Sciences, , University of Adelaide, ; Adelaide, Australia
                Author information
                http://orcid.org/0000-0001-5040-2807
                Article
                3742
                10.1186/s12936-021-03742-x
                8077781
                33906650
                18763d48-d63b-49c8-80cc-e54b2bf8dd83
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 23 November 2020
                : 19 April 2021
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Infectious disease & Microbiology
                malaria,electronic data capture,information systems,evidence-based implementation,baseline audit,grip matrix,endline audit

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