Abstract

Background

In Cameroon, like in many other resource-limited countries, data generated by health settings including morbidity and mortality parameters are not always uniform. In the absence of a national guideline necessary for the standardization and harmonization of data, precision of data required for effective decision-making is therefore not guaranteed. The objective of the present study was to assess the reporting style of morbidity and mortality data in healthcare settings.

Methods

An institutional-based cross-sectional study was carried out from May to June 2022 at the Yaoundé Central Hospital. A questionnaire was used to assess the need to set up a standard tool to improve the reporting system. Medical records were used to collect mortality and morbidity data which were then compared to the International Statistical Classification of Diseases and Related Health Problems-11 (ICD-11) codification. Data were analyzed using IBM-SPSS version 26.

Results

Out of 200 patients’ morbidity causes recorded, nearly three-quarter (74.0%) were heterogeneous, and two over five (41.0%) of mortality causes reported were also heterogeneous. Most of respondents stated the need to set up a standard tool for collecting mortality and morbidity data (83.6%). Less than one-fifth (18.2%) of health care providers were able to understand data flow, correctly archived data (36.6%) and used electronic tools for data quality control (40.0%).

Conclusion

There were high levels of heterogeneities of morbidity and mortality causes among patients admitted to the Yaoundé Central Hospital in 2021. It is therefore urgent that Cameroon national health authorities implement the ICD-11 to allow the systematic recording, analysis, interpretation and comparison of mortality and morbidity data collected in Yaoundé Central Hospital at different times; and ensure interoperability and reusability of recorded data for medical decision support.

Details

Title
Mortality and morbidity patterns in Yaoundé, Cameroon: an ICD-11 classification-based analysis
Author
Georges Nguefack-Tsague; Fabrice Zobel Lekeumo Cheuyem; Noah, Boris Edmond; Ndobo-Koe, Valérie; Adidja Amani; Mekontchou, Léa Melataguia; Gweth, Marie Ntep; Annick Collins Mfoulou Minso Assala; Ngoufack, Marie Nicole; Binyom, Pierre René
Pages
1-7
Section
Research
Publication year
2025
Publication date
2025
Publisher
Springer Nature B.V.
e-ISSN
14726947
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3165425335
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.