Hospitals, as healthcare service providers, are required to improve the quality and efficiency of their services, one of which is through the implementation of Electronic Medical Records (EMR). This transformation impacts the workload of staff, particularly in the Medical Records Unit. This study aims to analyze the workload and staffing needs of the Medical Records Unit at Dr. Sitanala Central General Hospital using a descriptive quantitative approach with the Health Workload Analysis (ABK-Kes) method. Data were collected through observation and interviews with six staff members using observation sheets, interview guidelines, and informed consent forms. The results show that the Available Working Time (AWT) is 72,000 minutes per year, exceeding the national standard. There are 11 core tasks and 3 supporting tasks, with the highest Standard Workload (SWL) found in the recording and filing activity (72,000), and the Standard Supporting Task (SST) value is 1.2. Based on achievements, SWL, and SST, a total of four staff members are needed to balance the workload. Currently, only one staff member remains due to staff rotation, resulting in a shortage of three personnel. Therefore, Dr. Sitanala Hospital needs to recruit three additional medical record officers with a minimum qualification of a D3 in Medical Records to maintain optimal service and manageable workloads.

The accuracy of the diagnosis code is a statement that shows a code for a convincing diagnosis, and has been said to be certain and clear according to the ICD-10 guidelines. The purpose of this study was to obtain an overview of the analysis of the accuracy of injury codes and external causes of injury in emergency care electronic medical records at the Jakarta Islamic Hospital Sukapura. This research is descriptive research with a Mix Methode approach. Data collection techniques using observation and interview methods. Samples were taken using saturated sampling techniques totaling 81 electronic medical records of emergency care patients. The accuracy of the injury code is 22% correct, and the accuracy of the external cause of injury code incorporated in traffic accident cases and other accident cases is 0% correct. The low accuracy of injury codes was due to not adding character 5, block code errors, and errors in determining code categories. The results of the accuracy of the external cause of injury code obtained were 0% correct because 80 electronic medical records of emergency care patients did not contain the code for the external cause of injury. Factors that hinder the accuracy of injury codes and external causes of injury are influenced by man factors, namely high workload, dependence on ICD-10 codes on doctors, and lack of feedback audits. Then the influence of material factors, namely the incompleteness of supporting documents, lack of detail in diagnosis, and lack of chronological letters of events. Then the influence of method factors, namely unsupportive policies and procedures, lack of training and understanding, and weak application of external cause of injury codes.