Background
Disease prevention and control requires prompt and adequate actions towards reduction or elimination of existing conditions, and preventing new occurrences. Efficient decisions to such action should be based on correctly collected, analyzed, interpreted and timely data. Quality information is essential to monitor, evaluate, prioritize and improve the delivery of health care services. The aim of this project is to identify data quality issues that can affect surveillance data and to describe some of the consequences of poor data quality at Facilities level by the year 2022 in Gura Damole.

Methods
Institutional based cross-sectional study design employed to assess data quality and utilization of collected surveillance data among Guradhamole Woreda health facilities. The field activities were performed from January, 2022 up to February, 2022G.C. The district is administratively organized into 16 rural and 2 urban kebeles with~43,353 population. The Woreda have 3 Public health centers and 18 health posts with primary health Coverage of 100%. Data quality audit were conducted in three primary health care units.

Results
We reviewed almost all data quality assessment tools and found weak and interrupted information flow. All visited health centers were collect data on weekly basis both from health posts, but they would review their data on monthly basis. So, this may put them for late or missed case. There were high variations in the tool utilization and data accuracy at department or service unit and facility levels.

Conclusion
The gaps in collecting data routinely from health posts and departments, weak health post surveillance practices and knowledge gap of health extension workers and health workers in identifying cases needs to design tailored and inter-service strategies for improving data quality.