Healthcare data governance assessment based on hospital management perspectives

• Health data are used for multiple purposes: patient treatment, research, organization planning, health insurance claims, and police work. • Health data governance helps hospitals improve patient safety and research in the health sector, establishes policy, protects data and information assets, and determines accountabilities and processes for managing data and information. • The most required data governance domain areas: data quality management, metadata management, and data security management. • In developing countries, implementation of health data governance aims to improve the quality of health services and increase new partnerships in global health program. Hospitals are the most prominent health data producers of clinical data and administrative data. Reusing health data from hospitals has problems regarding data quality and integrity within the institution. These problems raise healthcare expenses, cause errors in patient treatment, and consume a lot of hospital IT personnel's work time for data extraction and synchronization. Implementing health data governance helps hospitals improve patient safety, increase research in the health sector, establish policy, protect data and information assets, and determine accountabilities and processes for managing data and information. However, only a few countries can implement health data governance in hospitals. In developing countries, research related to health data governance is rare. We conducted this research to determine the requirement for health data governance for hospitals in developing countries. This study is qualitative research with a single case study. The data was taken from the National Cardiovascular Center in Jakarta from June 2022 until December 2023. We used semi-structured interviews with IT and hospital management. There are 18 people as our interviewees. We used thematic analysis. Data governance domain areas are used in our initial code, and we continue to open coding to find the meaning of the interviewee's statement. The axial code was performed to get critical problem-related health data in the hospital. We got six themes as our problem identification. The themes were incomplete data, incorrect data, data redundancy, lack of documentation, data discoverability issues, and no ethical consideration in data access. After that, we mapped the problem to the domain area of data governance. This research found that the domain areas most required for health data governance were data quality management, metadata management, and data security management.