Abstract:
Background: health information system is one of the six building blocks of a health system designed
for the generation and use of information for other functions of the health system. In most developing
countries, routine health information systems are described as ineffective due to the poor quality of
the data collected, and low levels of use in real-time decision-making. Hence, the aim of this study
was to assess health management information system data quality in the health centers of project and
non-project area and identify associated factors.
Objective: To assess health management information system data quality and associated factors in
the health centers of the project and non-project areas, Oromia Region, Ethiopia 2022.
Method: Facility-based comparative cross-sectional study design was employed from June 15 to July
15, 2022. A total of 13 health centers were selected using simple random sampling to assess data
quality. All 229 health professionals, (117 from the project and 112 from the non-project area) who
were working in selected health facilities were considered to assess associated factors. Data quality
was assessed using accuracy, completeness, and timeliness dimensions. Descriptive statistics were
used for data quality and multivariate logistic regression was run to identify factors influencing data
quality. The level of significance was declared at P- value<0.05.
Results: A total of 219 (111 from the project and 108 from the non-project area) respondents
participated in the study with a response rate of 95.6%. The average data quality of the project
implemented area was 78.51%, whereas 72.51% in the non-project area. Data accuracy, completeness
and timeliness of project area versus non-project area was 97.95% versus 96.27%, 85.2% versus
76.83% and 52.38% versus 44.44% respectively. Years of experience [AOR=5.79, 95% CI
(1.51,22.2)], Training [AOR = 14.32, 95% CI (6.56, 31.2)], reward for good work [AOR = 0.197 CI
95 (0.084,0.46)], utilizing evidence for decision making [AOR =2.74 CI 95 (1.287,5.83)] were
significantly associated with data quality.
Conclusion: This study found that the overall data quality in the project area was greater than non project area. However, in both areas, it was lower than the national target (90%). Therefore, all
stakeholders should give all necessary support to improve data quality.
