Augmented Capacity Development Interventions (ACDI) Improved Data Quality Performance in the Routine Health...

Area of Science:

• Public Health
• Health Information Systems
• Health Services Research

Background:

• Routine health information systems are crucial for monitoring health service outcomes.
• Existing data quality improvement interventions in Ethiopia have shown limited success.
• There is a need to evaluate novel approaches to strengthen health data quality.

Purpose of the Study:

• To assess the impact of Augmented Capacity Development Interventions (ACDI) on data quality within Ethiopia's routine health information system.
• To identify key components of ACDI that contribute to improved data quality.

Main Methods:

• A cluster-randomized controlled trial involving 72 health institution clusters and 304 health workers was conducted.
• Interventions included training, supportive supervision, mentorship, and recognition.
• General Linear Mixed Model was used for data analysis.

Main Results:

• Data quality perception scores significantly increased from 2.32 at baseline to 3.13 at end-line (P < .001).
• ACDI implementation led to significant improvements in data quality practice (β = .17, P = .007), ease of data management (β = .14, P < .001), and information use (β = .15, P < .001).
• Encouragement and training combined were strong predictors of data quality improvement (β = .44, P < .001).

Conclusions:

• Augmented Capacity Development Interventions (ACDI) effectively enhance data quality in routine health information systems.
• Key drivers for improved data quality include an encouraging system, streamlined data management, clear guidelines, supportive supervision, and comprehensive training.
• The study recommends adapting and scaling up ACDI packages to improve health data quality and outcomes.