Evidence map›Paper›PMID 34303370›Full record

ArticleBMC health services research2021

Management of chronic lung diseases in Sudan and Tanzania: how ready are the country health systems?

Uzochukwu Egere, Elizabeth Shayo, Nyanda Ntinginya, Rashid Osman, Bandar Noory, Stella Mpagama, ElHafiz Hussein, Rachel Tolhurst, Angela Obasi, Kevin Mortimer and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
2.7field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 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

13 authors at 3 institutions in 2 countries.

Uzochukwu EgereDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK. Uzochukwu.Egere@lstmed.ac.uk.
Elizabeth ShayoDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Nyanda NtinginyaNIMR-Mbeya Medical Research Center, Mbeya, Tanzania.
Rashid OsmanThe Epidemiological Laboratory, Khartoum, Sudan.
Bandar NooryThe Epidemiological Laboratory, Khartoum, Sudan.
Stella MpagamaKibong'oto Infectious Diseases Hospital, Mae Street, Kilimanjaro, Tanzania.
ElHafiz HusseinThe Epidemiological Laboratory, Khartoum, Sudan.
Rachel TolhurstDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Angela ObasiDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Kevin MortimerDepartment of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK.
Asma El SonyThe Epidemiological Laboratory, Khartoum, Sudan.
Miriam TaegtmeyerDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
IMPALA Consortium
Liverpool School of Tropical Medicine · GBKilimanjaro Christian Medical Centre · TZNational Institute for Medical Research · TZ

Funding

National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care Yorkshire and Humber 16/136/35
6 · The paper itself

Abstract

backgroundChronic lung diseases (CLDs), responsible for 4 million deaths globally every year, are increasingly important in low- and middle-income countries where most of the global mortality due to CLDs currently occurs. As existing health systems in resource-poor contexts, especially sub-Saharan Africa (SSA), are not generally oriented to provide quality care for chronic diseases, a first step in re-imagining them is to critically consider readiness for service delivery across all aspects of the existing system.

methodsWe conducted a mixed-methods assessment of CLD service readiness in 18 purposively selected health facilities in two differing SSA health system contexts, Tanzania and Sudan. We used the World Health Organization's (WHO) Service Availability and Readiness Assessment checklist, qualitative interviews of key health system stakeholders, health facility registers review and assessed clinicians' capacity to manage CLD using patient vignettes. CLD service readiness was scored as a composite of availability of service-specific tracer items from the WHO service availability checklist in three domains: staff training and guidelines, diagnostics and equipment, and basic medicines. Qualitative data were analysed using the same domains.

resultsOne health facility in Tanzania and five in Sudan, attained a CLD readiness score of ≥ 50 % for CLD care. Scores ranged from 14.9 % in a dispensary to 53.3 % in a health center in Tanzania, and from 36.4 to 86.4 % in Sudan. The least available tracer items across both countries were trained human resources and guidelines, and peak flow meters. Only two facilities had COPD guidelines. Patient vignette analysis revealed significant gaps in clinicians' capacity to manage CLD. Key informants identified low prioritization as key barrier to CLD care.

conclusionsGaps in service availability and readiness for CLD care in Tanzania and Sudan threaten attainment of universal health coverage in these settings. Detailed assessments by health systems researchers in discussion with stakeholders at all levels of the health system can identify critical blockages to reimagining CLD service provision with people-centered, integrated approaches at its heart.

Indexed as

Health FacilitiesLung DiseasesHealth Services AccessibilityHumansSudanTanzania

Identifiers

PMID34303370
PMCPMC8310588
OpenAlexW3135110699

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.