Key components influencing the sustainability of a multi-professional obstetric emergencies training programme in a middle-income setting: a qualitative study

BMC HEALTH SERVICES RESEARCH(2021)

引用 3|浏览3
暂无评分
摘要
Background Multi-professional obstetric emergencies training is one promising strategy to improve maternity care. Sustaining training programmes following successful implementation remains a challenge. Understanding, and incorporating, key components within the implementation process can embed interventions within healthcare systems, thereby enhancing sustainability. This study aimed to identify key components influencing sustainability of PRactical Obstetric Multi-Professional Training (PROMPT) in the Philippines, a middle-income setting. Methods Three hospitals were purposively sampled to represent private, public and teaching hospital settings. Two focus groups, one comprising local trainers and one comprising training participants, were conducted in each hospital using a semi-structured topic guide. Focus groups were audio recorded. Data were analysed using thematic analysis. Three researchers independently coded transcripts to ensure interpretation consistency. Results Three themes influencing sustainability were identified; attributes of local champions , multi-level organisational involvement and addressing organisational challenges . Conclusions These themes, including potential barriers to sustainability, should be considered when designing and implementing training programmes in middle-income settings. When ‘scaling-up’, local clinicians should be actively involved in selecting influential implementation champions to identify challenges and strategies specific to their organisation. Network meetings could enable shared learning and sustain enthusiasm amongst local training teams. Policy makers should be engaged early, to support funding and align training with national priorities.
更多
查看译文
关键词
Obstetric emergencies, multi-professional training, Sustainability, Middle-income setting, Implementation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要