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Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya
  1. Christiane Hagel1,
  2. Chris Paton1,
  3. George Mbevi2,
  4. Mike English1,2
  5. on behalf of the Clinical Information Network (CIN) information systems interest group
  1. 1Nuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
  2. 2KEMRI-Wellcome Trust Research Programme, Health Services Unit, Nairobi, Kenya
  1. Correspondence to Christiane Hagel; christiane.hagel{at}ndm.ox.ac.uk

Abstract

Background Target 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports on its use for collecting neonatal hospital data that are of increasing importance as births within facilities increase. To address this gap, we investigated implementation experiences of DHIS2 in LMICs and mapped the information flow relevant for neonatal data reporting in Kenyan hospitals.

Methods A narrative review of published literature and policy documents from LMICs was conducted. Information gathered was used to identify the challenges around DHIS2 and to map information flows from healthcare facilities to the national level. Two use cases explore how newborn data collection and reporting happens in hospitals. The results were validated, adjusted and system challenges identified.

Results Literature and policy documents report that DHIS2 is a useful tool with strong technical capabilities, but significant challenges can emerge with the implementation. Visualisations of information flows highlight how a complex, people-based and paper-based subsystem for inpatient information capture precedes digitisation. Use cases point to major challenges in these subsystems in accurately identifying newborn deaths and appropriate data for the calculation of mortality even in hospitals.

Conclusions DHIS2 is a tool with potential to improve availability of health information that is key to health systems, but it critically depends on people-based and paper-based subsystems. In hospitals, the subsystems are subject to multiple micro level challenges. Work is needed to design and implement better standardised information processes, recording and reporting tools, and to strengthen the information system workforce. If the challenges are addressed and data quality improved, DHIS2 can support countries to track progress towards the SDG target of improving neonatal mortality.

  • health policy
  • health systems
  • paediatrics
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This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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Footnotes

  • Handling editor Stephanie M Topp

  • Twitter @Christi_Hagel, @DrChrisPaton, @joji_ikuta, @ProfMikeEnglish

  • Collaborators Clinical Information Network (CIN) information systems interest group

  • Contributors CH, CP, GM and ME conceived the study. CH collected literature and created visualisations, GM helped to validate and adjust mappings together with the HRIOs, CP and ME assisted in analysis and interpretation. CH drafted the manuscript. CP, GM and ME critically revised the manuscript for intellectual content. All authors read and approved the final manuscript.

  • Funding CH, CP, GM and ME were supported by funds from the Global Challenges Research Fund (GCRF) (no. KCD00050 B904) and a Senior Research Fellowship awarded to ME by The Wellcome Trust (no. 207522).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data sharing not applicable as no datasets generated and/or analysed for this study. All data relevant to the study are included in the article or uploaded as online supplementary information. There is no sharable data set. All relevant information, search strategy and literature identified, is within this paper and its supporting appendix.