Data quality assessment of mHealth systems: strengths, potential limitations and opportunities for improvement; Case of Yendanafe system in Neno District, Malawi
 
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1
University of Global Health Equity, Rwanda
 
2
University of Global Health Equity, Malawi
 
3
Partners in Health Malawi, Rwanda
 
4
University of Global Health Equity, United States
 
5
Partners in Health Malawi, Malawi
 
6
Havard University, Algeria
 
 
Publication date: 2023-04-27
 
 
Popul. Med. 2023;5(Supplement):A576
 
ABSTRACT
Background: Good quality data enables proper decision making in healthcare settings leading to better planning, higher management efficiency and improved patient outcomes. The Yendanafe data system in Malawi was designed to promote comprehensive patient care and improve public health services through an evidence-based approach. This study assessed the quality of the Yendanafe data system. Methods: All available data in the Yendanafe data system for the year 2021 were analyzed in their data completeness, timeliness, accuracy, and consistency by measuring against the who recommended standards. A quantitative survey was conducted on a random sample of community health workers at six participating sites to identify end-user perspectives on the system and potential sources of variability. Results: The median completion rate was 100%, significantly higher than the who recommended standard of 90% (p=0.043). The overall timeliness of the Yendanafe system was 87.4%, significantly higher than the who recommended score of 80% (p>0.001). The overall average accuracy rate was 48.8%, significantly below the who recommended accuracy rate of 95% (p>0.001). The overall consistency was 98.77%. The strength of the system included having a language that is easy to understand (86%), having enough time to synchronize data into database (89%) and the ability to make edits in case information is wrongly filled (88%). However, some respondents found the phone were not user-friendly (86%), the system operated slowly (75%) and limited previous experience in collecting data via phone (85%). Conclusions: The Yendanafe system is an innovative and powerful tool that has the potential to revolutionize data collection and use to contribute positively to the improvement of the healthcare system in Malawi. Future studies to validate the accuracy of the Yendanafe system and to assess the accuracy of EMR data systems are needed. More technical support was needed and the design of the system could be improved.
ISSN:2654-1459
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