Evidence map›Paper›PMID 37968578›Full record

ArticleBMC pediatrics2023

Avoid equipment graveyards: rigorous process to improve identification and procurement of effective, affordable, and usable newborn devices in low-resource hospital settings.

Elizabeth Asma, Megan Heenan, George Banda, Rebecca P Kirby, Lucky Mangwiro, Claudia Ziegler Acemyan, Kara M Palamountain, Philip Kortum, Kondwani Kawaza, Z Maria Oden and 2 more

Abstract read
In one paragraph

Article in BMC pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

12 authors.

Elizabeth AsmaRice University Rice360 Institute for Global Health Technologies, Houston, TX, USA. Elizabeth.asma@rice.edu.ORCID http://orcid.org/0000-0001-6093-9843
Megan HeenanRice University Rice360 Institute for Global Health Technologies, Houston, TX, USA.
George BandaKamuzu University of Health Sciences, Blantyre, Malawi.
Rebecca P KirbyNorthwestern University Kellogg School of Management, Evanston, IL, USA.
Lucky MangwiroKamuzu University of Health Sciences, Blantyre, Malawi.
Claudia Ziegler AcemyanDepartment of Psychological Sciences, Rice University, Houston, TX, USA.
Kara M PalamountainNorthwestern University Kellogg School of Management, Evanston, IL, USA.
Philip KortumDepartment of Psychological Sciences, Rice University, Houston, TX, USA.
Kondwani KawazaKamuzu University of Health Sciences, Blantyre, Malawi.
Z Maria OdenRice University Rice360 Institute for Global Health Technologies, Houston, TX, USA.
Rebecca Richards-KortumRice University Rice360 Institute for Global Health Technologies, Houston, TX, USA.
Technical Collaborative Authorship Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMillions of newborns die annually from preventable causes, with the highest rates occurring in Africa. Reducing neonatal mortality requires investment to scale hospital care, which includes providing hospitals with appropriate technology to care for small and sick newborns. Expensive medical devices designed for high-resource settings often fail to withstand conditions in low-resource hospitals, including humidity, dust, frequent user turnover, complex maintenance, lack of stable power, or difficulty sourcing expensive consumables. Rigorous evaluation protocols are needed to identify effective, affordable, rugged, and easy-to-use medical devices appropriate for quality hospital-based newborn care in low-resource hospitals.

methodsWe developed an evidence-based technology review process to identify medical devices suitable for small and sick newborn care in low-resource hospitals. The eight-step process consists of: identifying devices needed for effective newborn care; defining Target Product Profiles (TPPs); identifying commercially-available products that may meet TPPs; conducting desk research to evaluate technologies against TPPs; performing technical performance verification testing under laboratory conditions; verifying technical performance after exposure to heat, humidity, dust, and power loss; performing usability evaluations with nurses, and qualifying devices that pass all steps. Devices were purchased, installed, and monitored in newborn wards across Kenya, Malawi, Nigeria, and Tanzania.

resultsOf 271 devices considered, only 45 (16.6%) met corresponding TPPs based on desk research. Thirty-nine were purchased and evaluated in the laboratory; five (12.8%) failed to meet TPPs. Thirty-four products passing laboratory evaluation underwent short-term environmental testing; only one (2.9%) device failed. Thirty-seven products underwent usability testing with 127 clinicians; surprisingly, 14 (37.8%) failed to meet TPPs. Twenty-three products passed all evaluations, and 2457 devices were installed across 65 newborn wards in Kenya, Malawi, Nigeria, and Tanzania. Continuous device monitoring reported minimal device failures, with failed devices typically returned to service within two days, resulting in an average uptime (service days divided by days installed) of 99%.

conclusionAn evidence-based device selection process can improve procurement of effective, affordable, rugged, usable newborn care devices for low-resource hospitals, and feedback to manufacturers can improve device quality. Similar processes could be adapted beyond newborn care to identify medical devices suitable for implementation in any low-resource setting.

Indexed as

CemeteriesHospitalsDustHumansInfant MortalityInfant, NewbornKenyaDustAppropriate healthcare technologyLow- and Middle-Income CountriesMedical devicesNewbornTechnology assessmentUser centred design

Identifiers

PMID37968578
PMCPMC10652423

What OpenQuestion holds

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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.