AAssessment of completeness of the outpatient’s electronic clinical documents in EMRS (Openclinic) to enhance patient care service delivery. Case study: University Teaching Hospital of Kigali (CHUK)

Abstract

Background: A patient's medical and treatment information is contained in an electronic medical record (EMR), which is a patient-centered record. EMR data completeness is a matter for research, patient data analysis, and disease reporting, as the patients’ clinical and medication information is stored in the EMR database. Aim: This study mainly aimed to assess the completeness of the outpatient’s electronic clinical documents recorded in EMRs in order to enhance patient care service delivery. Design: A retrospective quantitative study design using data extracted from the open clinic-EMRs database was conducted. Setting: The EMRs data was obtained from Kigali Teaching Hospital, a tertiary hospital in Rwanda. Main outcome measure(s): The completeness of data was measured considering if a patient’s record file contains all desired types of data (i.e., patients’ demographics, clinical patient consultation documentation, Laboratory and Radiology information). Results: A total of 104 unique individuals were identified after extracting the data from the EMR database. The study found a frequency of 57.02% for the overall data completeness in EMR-OpenClinic. Furthermore, 87.77% of the patients had complete data in the main six categories (i.e., patient ID, age, gender, encounter type, clinical diagnosis, and treatments). The completeness of the consultation file, which includes vital signs and patient assessment documentation, was determined to be 50.52%. The completeness of the laboratory file was found to be 43.08%, and for the radiology file, it was 44.44%. Conclusion: Based on the type of information needed and the type of interaction, the study's findings show that data completeness varies. The EMR-OpenClinic system database can be used to undertake data completeness for patient care service delivery through clinical research, as we largely gathered data on most of the patient demographics, clinical laboratory document, clinical radiology document, and clinical consultation document from the EMRs database. However, further studies are required to investigate the content and completeness of EMRs for specific patient populations to evaluate other dimensions of data quality in Electronic Health Records (EHRs) to ensure their reliability and validity.