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Research article
Georges Nguefack-Tsague
University of Yaounde I
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3847-3490
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Routine 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.
Methods
A 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 univariate analysis and adjusted odds ratio (aOR) for multivariate analysis with 95% confidence interval (CI). A p-value of less than 0.05 was considered statistically significant.
Results
Of 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%) male and 53(47.7%) female. 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 Univariate 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 multivariate level, the only significantly associated factor was having received training on health information (aOR = 3.3 (1.01, 11.1), p = 0.04).
Conclusions
Training 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 mechanisms, for an efficient RHIS strengthening in Yaoundé.
Keywords
Routine Health Information System, Associated Factors, Medical Informatics, Medical Informatics Applications, Health Informatics
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Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
No community comments so far
Editorial decision: Accept
On 29 Nov, 2020
Review #1 received
Received 28 Nov, 2020
Reviewer #1 agreed
On 17 Nov, 2020
Reviewers invited
Invitations sent on 16 Nov, 2020
Editor assigned
On 09 Nov, 2020
Submission checks complete
On 09 Nov, 2020
Editor invited
On 09 Nov, 2020
Version 1
Posted 28 May, 2020
No comments provided
Editorial decision: Major revision
On 12 Oct, 2020
Review #2 received
Received 29 Sep, 2020
Reviewer #2 agreed
On 17 Sep, 2020
Review #1 received
Received 10 Sep, 2020
Reviewer #1 agreed
On 31 Aug, 2020
Reviewers invited
Invitations sent on 04 Jun, 2020
Editor assigned
On 15 May, 2020
First submitted
On 14 May, 2020
Submission checks complete
On 14 May, 2020
Editor invited
On 14 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BMC Medical Informatics and Decision Making.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Georges Nguefack-Tsague
University of Yaounde I
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3847-3490
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
No community comments so far
Editorial decision: Accept
On 29 Nov, 2020
Review #1 received
Received 28 Nov, 2020
Reviewer #1 agreed
On 17 Nov, 2020
Reviewers invited
Invitations sent on 16 Nov, 2020
Editor assigned
On 09 Nov, 2020
Submission checks complete
On 09 Nov, 2020
Editor invited
On 09 Nov, 2020
Version 1
Posted 28 May, 2020
No comments provided
Editorial decision: Major revision
On 12 Oct, 2020
Review #2 received
Received 29 Sep, 2020
Reviewer #2 agreed
On 17 Sep, 2020
Review #1 received
Received 10 Sep, 2020
Reviewer #1 agreed
On 31 Aug, 2020
Reviewers invited
Invitations sent on 04 Jun, 2020
Editor assigned
On 15 May, 2020
First submitted
On 14 May, 2020
Submission checks complete
On 14 May, 2020
Editor invited
On 14 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Medical Informatics and Decision Making.
Background
Routine 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.
Methods
A 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 univariate analysis and adjusted odds ratio (aOR) for multivariate analysis with 95% confidence interval (CI). A p-value of less than 0.05 was considered statistically significant.
Results
Of 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%) male and 53(47.7%) female. 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 Univariate 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 multivariate level, the only significantly associated factor was having received training on health information (aOR = 3.3 (1.01, 11.1), p = 0.04).
Conclusions
Training 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 mechanisms, for an efficient RHIS strengthening in Yaoundé.
Figure 1
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