Evidence map›Paper›PMID 33334340›Full record

ArticleBMC medical informatics and decision making2020

Factors associated with the performance of routine health information system in Yaoundé-Cameroon: a cross-sectional survey.

Georges Nguefack-Tsague, Brian Bongwong Tamfon, Ismael Ngnie-Teta, Marie Nicole Ngoufack, Basile Keugoung, Serge Marcial Bataliack, Chanceline Bilounga Ndongo

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Routine Health Information Systems in the European Context: A Systematic Review of Systematic Reviews.International journal of environmental research and public health · 2021
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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

7 authors at 5 institutions in 2 countries.

Georges Nguefack-TsagueDepartment of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon. nguefacktsague@gmail.com.ORCID 0000-0002-3847-3490
Brian Bongwong TamfonDepartment of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon.
Ismael Ngnie-TetaHelen Keller International, Yaoundé, Cameroon.
Marie Nicole NgoufackChallenges Initiative Solutions, Yaoundé, Cameroon.
Basile KeugoungUNICEF, Yaoundé, Cameroon.
Serge Marcial BataliackWorld Health Organisation, Yaoundé, Cameroon.
Chanceline Bilounga NdongoDepartment of Disease Control, Epidemics and Pandemics, Ministry of Public Health, Yaoundé, Cameroon.
Université de Yaoundé I · CMHelen Keller International · CMMinistry of Public Health · CMUnited Nations Children's Fund Cameroon · CMWWF Cameroon · CM

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundRoutine Health Information Systems (RHIS) of low-income countries function below the globally expected standard, characterised by the production and use of poor-quality data, or the non-use of good quality data for informed decision making. This has negatively influenced the health service delivery and uptake. This study focuses on identifying the factors associated with the performance of RHIS of the health facilities (HF) in Yaoundé, so as to guide targeted RHIS strengthening.

methodsA HF-based cross-sectional study in the 6 health districts (HDs) of Yaoundé was conducted. HFs were chosen using stratified sampling with probability proportional to size per HD. Data were collected, entered into Microsoft Excel 2013 and analysed with IBM- SPSS version 25. Consistency of the questionnaire was measured using Cronbach's alpha coefficient. Pearson's chi-square (and Fisher exact where relevant) tests were used to establish relationships between qualitative variables. Associations were further quantified using unadjusted Odd ratio (OR) for univariable analysis and adjusted odds ratio (aOR) for multivariable analysis with 95% confidence interval (CI). A p-value of less than 0.05 was considered statistically significant.

resultsOf 111 selected HFs; 16 (14.4%) were public and 95 (85.6%) private. Respondents aged 24-60 years with an average of 38.3 ± 9.3 years; 58 (52.3%) males and 53(47.7%) females. Cronbach's alpha was 0.96 (95%CI: 0.95-0.98, p < 0.001), proving that the questionnaire was reliable in measuring RHIS performances. At univariable level, the following factors were positively associated with good performances: supportive supervision (OR = 3.03 (1.1, 8.3); p = 0.02), receiving feedback from hierarchy (OR = 3.6 (0.99, 13.2); p = 0.05), having received training on health information (OR = 5.0 (1.6, 16.0); p = 0.003), and presence of a performance evaluation plan (OR = 3.3 (1.4, 8.2), p = 0.007). At multivariable level, the only significantly associated factor was having received training on health information (aOR = 3.3 (1.01, 11.1), p = 0.04).

conclusionTraining of health staff in the RHIS favors RHIS good performance. Hence, emphasis should be laid on training and empowering staff, frequent and regular RHIS supervision, and frequent and regular feedback, for an efficient RHIS strengthening in Yaoundé.

Indexed as

Data AccuracyHealth Information SystemsAdultCameroonCross-Sectional StudiesFemaleHealth FacilitiesHumansMaleMiddle AgedYoung AdultAssociated factorsHealth informaticsMedical informaticsMedical informatics applicationsRoutine health information system

Identifiers

PMID33334340
PMCPMC7745475
OpenAlexW3110637330

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.