Health professionals and stakeholders in the Twifo Ati-Morkwa District gathered for an important training session on Family Planning (FP) and Comprehensive Abortion Care (CAC) data capturing using the RSLOG platform. The session aimed to enhance the efficiency and accuracy of data management in healthcare services.

The training featured presentations from key facilitators from the regional, Madam Jennifer Konadu and Madam Anima in the presence of Madam Cynthia Wilson, the District Public Health Nurse. The speakers emphasized the importance of accurate data collection in improving healthcare delivery, particularly in reproductive health services. One of the central issues raised during the session was the lack of FP commodities, which led to an urgent appeal for necessary supplies to ensure continuous healthcare services. Participants also received practical guidance on navigating the RSLOG platform, covering: How to download the APP, Creating and accessing an account and Logging in with unique credentials(Email & Password).

Madam Jennifer Konadu provided an in-depth explanation of using the RSLOG system for family planning and contraceptive methods data capturing. She detailed the role of RSLOG as an electronic system for aggregating and tracking health transactions, making it easier to manage and analyze data. Participants were introduced to three modes of accessing the system: Web-based (Online), Mobile (Offline capability) and Desktop (Offline capability). To ensure comprehensive understanding, a live demonstration was conducted, allowing participants to practice real-time data entry and troubleshooting techniques.

The training session concluded with a call for continued capacity-building programs to enhance data accuracy and service delivery. Stakeholders were encouraged to advocate for improved access to FP commodities while leveraging RSLOG to streamline healthcare management. The training session ended on a high note, with participants expressing gratitude for the opportunity to improve their technical skills in reproductive health data management.