Data Quality Assessment of Yendanafe System: Strengths, Potential Limitations and Opportunities for Improvement, Neno Malawi

Background:
Good quality data enables proper decision making in healthcare settings leading to better planning,
higher management efficiency and improved patient outcomes. This study aimed to assess the
quality of the Yendanafe data system in Malawi. The Yendanafe data system was designed to
promote comprehensive patient care and improve public health services through an evidence-based
approach. The study highlights the strengths of the system and its potential limitations while
proposing opportunities for improvement.
Methods:
An explanatory mixed approach was used to evaluate the Yendanafe data system using three
distinct sources: 1) data quality dimensions, 2) survey data, and 3) focus group discussions and
interviews. An analysis was conducted using all available retrospective data collected in the
Yendanafe data system between January 1 and December 31, 2021. Twelve data sets were
extracted for quality data dimension analysis for examination of 96 variables and 254,736
observations in total. Data completeness, timeliness, accuracy, and consistency were reviewed and
benchmarked against existing standards. A quantitative survey using a Likert scale approach was
conducted on a random proportional sample of community health workers (n=131) at the
participating sites to identify end-user perspectives and potential sources of variability. Focus
group discussions and interviews were conducted to review the preliminary findings of the quality
data dimensions and survey analyses, to evaluate possible root causes of the observed limitations,
and identify possible solutions. Two focus group discussions were held with a randomly selected
group of community health workers (n=19) as end-users of the Yendanafe data system. In addition,
in-depth interviews with six PIH staff members well versed in the use of Yendanafe were
conducted.
Results
Our results indicate that the Yendanafe system data is complete and reported in a timely manner
(completeness=89.70%, timeliness=87.40%). While accuracy of the data remainsinconclusive due
to lack of a gold standard for reference. Data has also been shown to be highly consistent within
the system (98.77%). Overall, data quality dimensions met or even exceeded the World Health
Organization standards for all quality data dimensions except accuracy. Data gathered through
community health worker surveys, focus group discussions and interviews confirmed the ease-of use and practicality of the system and identified possible areas of improvement including:
technology (devices, chargers), connectivity (remote synchronization, air-time), methods (design
of case report forms), processes (standardized guidance), and training (length and content).
Our study recommends subsequent study to validate the accuracy of the Yendanafe System and
another study to assess the accuracy of EMR data system. This study further recommends
sufficient trainings and education for CHWs, more technical support and systems design and
improvement.
Conclusion:
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 health care system in
Malawi