Objective: The objective of this group work is to bring together health sector professionals to discuss and strategize on improving maternal healthcare in flood-prone regions, taking inspiration from the challenges faced by Rina and other pregnant women in the Haor region of Bangladesh.
Introduction (5 minutes)
v Provide an overview of the story of Rina and the challenges she faced during her pregnancy in a flood-prone area.
v Highlight the importance of maternal healthcare in such vulnerable environments.
v Set the goals for the group work session.
Understanding the Challenges (5 minutes)
v Facilitate a discussion to identify the key challenges faced by pregnant women in flood-prone regions.
v Discuss the impact of limited resources, inadequate facilities, and overwhelmed medical services on maternal health.
v Explore the implications of unsanitary conditions, lack of nutrition, and disrupted access to prenatal and postnatal care.
Sharing Best Practices (10 minutes)
v Encourage participants to share their experiences and success stories related to managing maternal healthcare during natural disasters.
v Discuss strategies that have proven effective in improving preparedness, resource allocation, and coordination in similar contexts.
v Explore innovative approaches and technologies that can be leveraged to enhance maternal healthcare in flood-prone regions.
Developing Action Plans (10 minutes)
v Divide participants into smaller groups and assign each group a specific aspect of maternal healthcare (e.g., prenatal care, emergency obstetric services, postnatal support, infrastructure development).
v Task the groups with brainstorming actionable steps to address the identified challenges in their assigned area.
v Discuss and refine the action plans within each group.
v Share the action plans with the larger group and foster a collaborative discussion to prioritize and consolidate the ideas.
Strategies for Implementation (10 minutes)
v Discuss the potential barriers and limitations that may hinder the implementation of the action plans.
v Identify strategies to overcome these barriers, including advocacy, policy reforms, partnerships, and resource mobilization.
v Highlight the importance of multi-sectoral collaboration and community engagement in achieving sustainable improvements.
Presentation (15 minutes)
v Invite each group to present their action plan to the larger group.
v Facilitate a discussion to receive feedback, suggestions, and questions from participants.
v Encourage participants to identify common themes or strategies that can be adopted collectively.
v Discuss potential barriers and limitations to implementation and strategies to overcome them.
Conclusion and Next Steps (5 minutes)
v Summarize the key points discussed during the session.
v Encourage participants to pledge their commitment to supporting maternal healthcare in flood-prone regions.
v Discuss potential follow-up actions, such as forming working groups, seeking funding opportunities, or collaborating on research and knowledge sharing initiatives.
By engaging health sector professionals in this group work, we can foster collaboration and collective efforts to address the challenges faced by pregnant women in flood-prone regions. The session aims to generate practical solutions and inspire participants to take actionable steps towards ensuring resilient and effective maternal healthcare in these vulnerable environments.
Guidelines for Data Quality Assessment (DQA) What is Data Quality Assessment (DQA)? DQA stands for Data Quality Assessment or Data Quality Audit. It is a systematic process of evaluating the quality of data that is being collected, processed, stored, and used in a program or project. The objective of DQA is to identify and address any issues or challenges related to data quality that may affect the validity, reliability, and usefulness of the data. The DQA process typically involves a review of data collection methods, data entry processes, data management systems, data analysis procedures, and data reporting and dissemination processes. The DQA may also include a review of the quality of the data itself, including data completeness, accuracy, consistency, and timeliness. The results of the DQA are used to identify areas for impr
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