Knowledge translation in emergency medical services: A qualitative survey of barriers to guideline implementation

Resuscitation(2010)

引用 59|浏览16
暂无评分
摘要
Background: The American Heart Association (AHA) released guidelines to improve survival rates from out-of-hospital cardiac arrest in 2005. We sought to identify what barriers delayed the implementation of these guidelines in EMS agencies. Methods: We surveyed 178 EMS agencies as part of a larger quantitative survey regarding guideline implementation and conducted a single-question semi-structured interview using the Grounded Theory method. We asked "What barriers if any, delayed implementation of the (2005 AHA) guidelines in your EMS agency?" Data were coded and member validation was employed to verify our findings. Results: 176/178 agencies completed the quantitative survey. Qualitative data collection ceased after reaching theoretical saturation with 34 interviews. Ten unique barriers were identified. We categorized these 10 barriers into three themes. The theme instruction delays (reported by 41% of respondents) included three barriers: booking/training instructors (9%), receiving training materials (15%), and scheduling staff for training (18%). The second theme, defibrillator delays (38%), included two barriers; reprogramming defibrillators (24%) and receiving new defibrillators to replace non-upgradeable units (15%). The third theme was decision-making (38%) and included five barriers; coordinating with allied agencies (9%), government regulators such as state and provincial health authorities (9%), medical direction and base hospitals (9%), ROC participation (9%), and internal crises (3%). Conclusion: Many barriers contributed to delays in the implementation of the 2005 AHA guidelines in EMS agencies. These identified barriers should be proactively addressed prior to the 2010 Guidelines to facilitate rapid translation of science into clinical practice. (C) 2010 Elsevier Ireland Ltd. All rights reserved.
更多
查看译文
关键词
Heart arrest,Emergency medical services
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