Effect of capacity building, staffing levels and technology on quality of health management information system data on maternal deliveries at Arua referral hospital, Uganda

Abstract

This study aimed to investigate the impact of capacity building, staffing levels, and technology on the Quality of Health Management Information System (HMIS) Data concerning maternal deliveries at Arua Referral Hospital (ARRH) in Uganda. The research focused on three specific objectives: evaluating how capacity building influences the completeness of HMIS data for deliveries, assessing the effect of staffing levels on the timeliness of HMIS data related to deliveries, and examining the impact of technology on the accuracy of HMIS data concerning deliveries. Using a descriptive cross-sectional design incorporating quantitative and qualitative methodologies, the study involved a population of 120 hospital staff members (6 administrators, 6 records officers, 58 midwives, and 50 nurses). Respondents were selected through a combination of random and purposive sampling methods. Quantitative data was analyzed using SPSS and R software, while qualitative data utilized Nvivo V14 for thematic analysis. Findings revealed a predominantly female workforce in departments critical to maternal health, aligning with national nursing demographics. Notably, capacity building initiatives showed a strong positive correlation (r=0.6) with the completeness of HMIS data for maternal deliveries. Staffing levels also correlated positively (r=0.5) with timeliness, particularly influenced by the presence of Records Officers. Technology showed a weaker positive correlation (r=0.4) with data accuracy, access to DHIS2 and computers contributing mildly, while internet connectivity showed limited impact. Recommendations from the study emphasize clear responsibilities in data management to address issues like incorrect register filling. It advocates for inclusive training sessions involving junior staff and promotes enhanced data sharing and dissemination practices to bolster data quality assurance processes. In conclusion, this study highlights the pivotal roles of capacity building, staffing adequacy, and appropriate technology utilization in enhancing quality of HMIS data for maternal deliveries.