Literature DB >> 33334340

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

Georges Nguefack-Tsague1,2, Brian Bongwong Tamfon3,4, Ismael Ngnie-Teta5, Marie Nicole Ngoufack4,6,7, Basile Keugoung8, Serge Marcial Bataliack9, Chanceline Bilounga Ndongo10.   

Abstract

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 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.
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%) 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).
CONCLUSION: 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, for an efficient RHIS strengthening in Yaoundé.

Entities:  

Keywords:  Associated factors; Health informatics; Medical informatics; Medical informatics applications; Routine health information system

Year:  2020        PMID: 33334340     DOI: 10.1186/s12911-020-01357-x

Source DB:  PubMed          Journal:  BMC Med Inform Decis Mak        ISSN: 1472-6947            Impact factor:   2.796


  11 in total

1.  [Health workers’ involvement for data quality improvement in Benin].

Authors:  Yolaine Glèlè Ahanhanzo; Jacques Saizonou; Alain Wodon; Bruno Dujardin; Michèle Wilmet-Dramaix; Michel Makoutodé
Journal:  Sante Publique       Date:  2015 Mar-Apr       Impact factor: 0.203

Review 2.  How can routine health information systems improve health systems functioning in low- and middle-income countries? Assessing the evidence base.

Authors:  David R Hotchkiss; Mark L Diana; Karen G Fleischman Foreit
Journal:  Adv Health Care Manag       Date:  2012

3.  Special People in Routine Health Information Systems Implementation in South Africa.

Authors:  Lyn A Hanmer; Edward Nicol
Journal:  Stud Health Technol Inform       Date:  2015

4.  Improving district facility readiness: a 12-month evaluation of a data-driven health systems strengthening intervention in rural Rwanda.

Authors:  Hari S Iyer; Emmanuel Kamanzi; Jean Claude Mugunga; Karen Finnegan; Alice Uwingabiye; Edward Shyaka; Saleh Niyonzima; Lisa R Hirschhorn; Peter C Drobac
Journal:  Glob Health Action       Date:  2015-07-01       Impact factor: 2.640

5.  Making sense of Cronbach's alpha.

Authors:  Mohsen Tavakol; Reg Dennick
Journal:  Int J Med Educ       Date:  2011-06-27

6.  Routine health information system utilization and factors associated thereof among health workers at government health institutions in East Gojjam Zone, Northwest Ethiopia.

Authors:  Atsede Mazengia Shiferaw; Dessalegn Tegabu Zegeye; Solomon Assefa; Melaku Kindie Yenit
Journal:  BMC Med Inform Decis Mak       Date:  2017-08-07       Impact factor: 2.796

7.  Facilitators, best practices and barriers to integrating family planning data in Uganda's health management information system.

Authors:  Stephen Ojiambo Wandera; Betty Kwagala; Olivia Nankinga; Patricia Ndugga; Allen Kabagenyi; Bridgit Adamou; Benjamin Kachero
Journal:  BMC Health Serv Res       Date:  2019-05-22       Impact factor: 2.655

Review 8.  Generating statistics from health facility data: the state of routine health information systems in Eastern and Southern Africa.

Authors:  Abdoulaye Maïga; Safia S Jiwani; Martin Kavao Mutua; Tyler Andrew Porth; Chelsea Maria Taylor; Gershim Asiki; Dessalegn Y Melesse; Candy Day; Kathleen L Strong; Cheikh Mbacké Faye; Kavitha Viswanathan; Kathryn Patricia O'Neill; Agbessi Amouzou; Bob S Pond; Ties Boerma
Journal:  BMJ Glob Health       Date:  2019-09-29

9.  Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People's Region, Ethiopia.

Authors:  Misganu Endriyas; Abraham Alano; Emebet Mekonnen; Sinafikish Ayele; Temesgen Kelaye; Mekonnen Shiferaw; Tebeje Misganaw; Teka Samuel; Tesfahun Hailemariam; Samuel Hailu
Journal:  BMC Health Serv Res       Date:  2019-03-18       Impact factor: 2.655

10.  Routine health information system in the health facilities in Yaoundé-Cameroon: assessing the gaps for strengthening.

Authors:  Brian Bongwong Tamfon; Chanceline Bilounga Ndongo; Serge Marcial Bataliack; Marie Nicole Ngoufack; Georges Nguefack-Tsague
Journal:  BMC Med Inform Decis Mak       Date:  2020-12-01       Impact factor: 2.796

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  1 in total

1.  Data quality and associated factors in the health management information system at health centers in Shashogo district, Hadiya zone, southern Ethiopia, 2021.

Authors:  Nigusu Getachew; Bereket Erkalo; Muluneh Getachew Garedew
Journal:  BMC Med Inform Decis Mak       Date:  2022-06-15       Impact factor: 3.298

  1 in total

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