Evidence map›Paper›PMID 36962427›Full record

ArticlePLOS global public health2022

Assessing routine health information system performance during the tenth outbreak of Ebola virus disease (2018-2020) in the Democratic Republic of the Congo: A qualitative study in North Kivu.

Gabriel Kalombe Kyomba, Guillaume Mbela Kiyombo, Karen A Grépin, Serge Manitu Mayaka, Thérèse Nyangi-Mondo Mambu, Celestin Hategeka, Mala Ali Mapatano, Lys Alcayna-Stevens, Serge Kule Kapanga, Joël Nkima-Numbi Konde and 6 more

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Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Gabriel Kalombe KyombaKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.ORCID https://orcid.org/0000-0003-2695-7487
Guillaume Mbela KiyomboKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.
Karen A GrépinSchool of Public Health, University of Hong Kong, Pokfulam, Hong Kong SAR.ORCID https://orcid.org/0000-0003-4368-0045
Serge Manitu MayakaKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.ORCID https://orcid.org/0000-0002-9124-2114
Thérèse Nyangi-Mondo MambuKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.
Celestin HategekaDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-7808-4652
Mala Ali MapatanoKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.
Lys Alcayna-StevensDepartment of Anthropology, Harvard University, Cambridge, Massachusetts, United States of America.ORCID https://orcid.org/0000-0003-0653-1884
Serge Kule KapangaDépartement d'Anthropologie, Faculté des Sciences Sociales, Politiques et Administratives, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.
Joël Nkima-Numbi KondeKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.ORCID https://orcid.org/0000-0001-7191-2806
Dosithée Bebe NgoKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.ORCID https://orcid.org/0000-0002-7088-7271
Pélagie Diambalula BabakazoKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.ORCID https://orcid.org/0000-0001-5561-696X
Eric Musalu MafutaKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.ORCID https://orcid.org/0000-0001-7986-4618
Aimée Mampasi LuleboKinshasa School of Public Health, Université de Kinshasa, Kinshasa, The Democratic Republic of Congo.
Hinda RutonCentre for Health Services and Policy Research, The University of British Columbia, Vancouver, British Columbia, Canada.
Michael R LawCentre for Health Services and Policy Research, The University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0002-5637-6053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Democratic Republic of Congo has implemented reforms to its national routine health information system (RHIS) to improve timeliness, completeness, and use of quality data. However, outbreaks can undermine efforts to strengthen it. We assessed the functioning of the RHIS during the 2018-2020 outbreak of Ebola Virus Disease (EVD) to identify opportunities for future development. We conducted a qualitative study in North Kivu, from March to May 2020. Semi-structured interviews were conducted with 34 key informants purposively selected from among the personnel involved in the production of RHIS data. The topics discussed included RHIS functioning, tools, compilation, validation, quality, sharing, and the use of data. Audio recordings were transcribed verbatim and thematic analysis was used to study the interviewees' lived experience. The RHIS retained its structure, tools, and flow during the outbreak. The need for other types of data to inform the EVD response created other parallel systems to the RHIS. This included data from Ebola treatment centers, vaccination against Ebola, points of entry surveillance, and safe and dignified burial. The informants indicated that the availability of weekly surveillance data had improved, while timeliness and quality of monthly RHIS reporting declined. The compilation of data was late and validation meetings were irregular. The upsurge of patients following the implementation of the free care policy, the departure of healthcare workers for better-paid jobs, and the high prioritization of the outbreak response over routine activities led to RHIS disruptions. Delays in decision-making were one of the consequences of the decline in data timeliness. Adequate allocation of human resources, equitable salary policy, coordination, and integration of the response with local structures are necessary to ensure optimal functioning of the RHIS during an outbreak. Future research should assess the scale of data quality changes during outbreaks.

Identifiers

PMID36962427
PMCPMC10021379

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.