谷歌Chrome浏览器插件
订阅小程序
在清言上使用

What goes bump in the night? An analysis of unplanned contacts to a Regional UK Children’s Long Term Ventilation team

E Queen, R Gregory, A Frost, N Mcnarry, H Borrill,A Prayle, M Hurley

01.01 - Clinical problems - no related to asthma or COPD(2022)

引用 0|浏览3
暂无评分
摘要
Background: Nottingham Children’s Long Term Ventilation (LTV) team supports children and young people (CYP) across three counties in the Midlands, UK. Supporting CYP who are using LTV and their families can be challenging. Reasons for unplanned contacts can be varied and managing these, time consuming. Objectives: To evaluate reason and resource impact of managing unplanned contacts to the LTV team. Method: Prospective observational study over two weeks (November 2021) using time sheets of unplanned contacts by members of the team - two specialist nurses, one doctor and one physiotherapist. Reasons for contact, action required and time spent were recorded alongside basic demographic information. Thematic analysis descriptive numerical analysis was used to establish reasons and resource demand for such contact. Results: 58 contacts were received over 34 worked days. One nurse recorded 60% of the contacts. Average time spent on each contact was 27.8 minutes. 64% of contacts required an immediate response. Six key themes were identified as reason for contact: clinical issues, administrative requests, care planning and delivery, specialist information sharing, equipment and training. Five themes were explored for action/outcome: further contact, care planning, advice given, equipment management and administration. Conclusion: Managing unplanned contacts to the CYP LTV team consume a lot of time, some of which did not require a clinical professional. Some contacts are of a high clinical priority. Managing demand in a resource-limited service can be challenging. There may be possibilities for triage although accessibility of the team is rated as important by families.
更多
查看译文
关键词
long term ventilation team,regional uk childrens,night
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