Analysis of Electronic Medical Record Data Quality Following the Implementation of a New Hospital Information System at Hospital X

Abstract

The transition to a new Hospital Information System (SIMRS) at Hospital X changed the electronic medical record (EMR) documentation workflow and created a need to evaluate the quality of recorded data. Preliminary observations identified inconsistencies in diagnosis entries and patient age data. This study analyzed EMR data quality after implementation of the new SIMRS, focusing on completeness and accuracy. A descriptive quantitative design was used with 195 general outpatient EMRs. Primary data were obtained through direct observation using a checklist and were processed in SPSS using frequency and percentage distributions. Thirteen relevant data elements achieved 100% completeness. Three elements—civil-service rank/grade, NRP/NIP, and organizational unit—were unfilled, but these fields were considered conditionally applicable and therefore were not interpreted as deficiencies for general patients. Accuracy was high across the assessed dimensions: patient name and identity, ICD-10 coding, and follow-up data reached 100%; patient age data reached 99.5%; and diagnosis-entry conformity reached 95%. The average accuracy reported in the source study was 98.9%. Overall, EMR data quality following implementation of the new SIMRS was very good, although diagnosis-entry consistency and the design of conditionally applicable fields require improvement. Periodic monitoring, automatic input validation, clearer electronic-form logic, and regular staff training are recommended to maintain and improve EMR data quality.