Towards Improving Data Quality in Electronic Medical Records: An Investigation of Data Completeness in a Tertiary Hospital in Rwanda

Stud Health Technol Inform. 2023 Jun 29:305:390-393. doi: 10.3233/SHTI230513.

Abstract

Data quality is a primary barrier to using electronic medical records (EMR) data for clinical and research purposes. Although EMR has been in use for a long time in LMICs, its data has been seldomly used. This study aimed to assess the completeness of demographic and clinical data in a tertiary hospital in Rwanda. We conducted a cross-sectional study and assessed 92,153 patient data recorded in EMR from October 1st to December 31st, 2022. The findings indicated that over 92% of social demographic data elements were complete, and the completeness of clinical data elements ranged from 27% to 89%. The completeness of data varied markedly by departments. We recommend an exploratory study to understand further reasons associated with the completeness of data in clinical departments.

Keywords: Data completeness; Data quality; Data use; EMR.

MeSH terms

  • Cross-Sectional Studies
  • Data Accuracy*
  • Electronic Health Records*
  • Humans
  • Rwanda
  • Tertiary Care Centers