Evidence map›Paper›PMID 38625736›Full record

ArticleJMIR formative research2024

Experiences, Lessons, and Challenges With Adapting REDCap for COVID-19 Laboratory Data Management in a Resource-Limited Country: Descriptive Study.

Kagiso Ndlovu, Kabelo Leonard Mauco, Onalenna Makhura, Robin Hu, Nkwebi Peace Motlogelwa, Audrey Masizana, Emily Lo, Thongbotho Mphoyakgosi, Sikhulile Moyo

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

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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

9 authors at 5 institutions in 3 countries.

Kagiso NdlovuDepartment of Computer Science, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-4175-8366
Kabelo Leonard MaucoDepartment of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-9726-5966
Onalenna MakhuraDepartment of Computer Science, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0001-9976-4497
Robin HuCollege of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0003-0212-2039
Nkwebi Peace MotlogelwaDepartment of Computer Science, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0009-0000-1199-3659
Audrey MasizanaDepartment of Computer Science, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-2465-1946
Emily LoCollege of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0009-0007-8719-0546
Thongbotho MphoyakgosiNational Health Laboratory, Ministry of Health, Gaborone, Botswana.ORCID https://orcid.org/0009-0002-9646-9796
Sikhulile MoyoBotswana Harvard AIDS Institute Partnership, Gaborone, Botswana.ORCID https://orcid.org/0000-0003-3821-4592
University of Botswana · BWUniversity of the Sciences · USBotswana Harvard AIDS Institute Partnership · BWKarolinska Institutet · SEMinistry of Health · BW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic brought challenges requiring timely health data sharing to inform accurate decision-making at national levels. In Botswana, we adapted and integrated the Research Electronic Data Capture (REDCap) and the District Health Information System version 2 (DHIS2) platforms to support timely collection and reporting of COVID-19 cases. We focused on establishing an effective COVID-19 data flow at the national public health laboratory, being guided by the needs of health care professionals at the National Health Laboratory (NHL). This integration contributed to automated centralized reporting of COVID-19 results at the Ministry of Health (MOH).

objectiveThis paper reports the experiences, challenges, and lessons learned while designing, adapting, and implementing the REDCap and DHIS2 platforms to support COVID-19 data management at the NHL in Botswana.

methodsA participatory design approach was adopted to guide the design, customization, and implementation of the REDCap platform in support of COVID-19 data management at the NHL. Study participants included 29 NHL and 4 MOH personnel, and the study was conducted from March 2, 2020, to June 30, 2020. Participants' requirements for an ideal COVID-19 data management system were established. NVivo 11 software supported thematic analysis of the challenges and resolutions identified during this study. These were categorized according to the 4 themes of infrastructure, capacity development, platform constraints, and interoperability.

resultsOverall, REDCap supported the majority of perceived technical and nontechnical requirements for an ideal COVID-19 data management system at the NHL. Although some implementation challenges were identified, each had mitigation strategies such as procurement of mobile Internet routers, engagement of senior management to resolve conflicting policies, continuous REDCap training, and the development of a third-party web application to enhance REDCap's capabilities. Lessons learned informed next steps and further refinement of the REDCap platform.

conclusionsImplementation of REDCap at the NHL to streamline COVID-19 data collection and integration with the DHIS2 platform was feasible despite the urgency of implementation during the pandemic. By implementing the REDCap platform at the NHL, we demonstrated the possibility of achieving a centralized reporting system of COVID-19 cases, hence enabling timely and informed decision-making at a national level. Challenges faced presented lessons learned to inform sustainable implementation of digital health innovations in Botswana and similar resource-limited countries.

Indexed as

BotswanaCOVID-19data managementDHIS2eHealthinteroperabilityNational Health LaboratoryREDCap

Identifiers

PMID38625736
PMCPMC11061793
OpenAlexW4388235503

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.