School of Nursing and Midwifery, Queen's University Belfast, Belfast, United Kingdom.
School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
PLoS One. 2023 Jul 11;18(7):e0288433. doi: 10.1371/journal.pone.0288433. eCollection 2023.
Heart failure (HF) affects up to 64.3 million people globally. Advancements in pharmaceutical, device or surgical therapies, have led to patients living longer with HF. Heart failure affects 20% of care home residents, with these individuals presenting as older, frailer, and with more complex needs compared to those living at home. Thus, improving care home staff (e.g., registered nurse and care assistant) knowledge of HF has the potential to benefit patient care and reduce acute care utilization. Our aim is to co-design, and feasibility test, a digital intervention to improve care home staff knowledge of HF and optimise quality of life for those living with the condition in long-term residential care.
Using a logic model, three workstreams have been identified. Workstream 1 (WS1), comprised of three steps, will inform the 'inputs' of the model. First, qualitative interviews (n = 20) will be conducted with care home staff to identify facilitators and barriers in the provision of care to people with HF. Concurrently, a scoping review will be undertaken to synthesise current evidence of HF interventions within care homes. The last step will involve a Delphi study with 50-70 key stakeholders (for example care home staff, people with HF and their family and friends) to determine key education priorities related to HF. Using data from WS1, a digital intervention to improve care home staff knowledge and self-efficacy of HF will be co-designed in workstream 2 (WS2) alongside those living with HF or their carers, HF professionals, and care home staff. Lastly, workstream 3 (WS3) will involve mixed-methods feasibility testing of the digital intervention. Outcomes include staff knowledge on HF and self-efficacy in caring for HF residents, intervention usability, perceived benefits of the digital intervention on quality of life for care home residents, and care staff experience of implementing the intervention.
As HF affects many care home residents, it is vital that care home staff are equipped to support people living with HF in these settings. With limited interventional research in this area, it is envisaged that the resulting digital intervention will have relevance for HF resident care both nationally and internationally.
心力衰竭(HF)影响全球多达 6430 万人。在药物、设备或手术治疗方面的进步,使得 HF 患者的寿命延长。心力衰竭影响着 20%的养老院居民,与在家居住的人相比,这些人年龄更大、身体更脆弱,且需求更复杂。因此,提高养老院工作人员(如注册护士和护理助理)对 HF 的了解,有可能改善患者的护理,并减少急性护理的使用。我们的目标是共同设计和测试一种数字干预措施,以提高养老院工作人员对 HF 的认识,并优化长期居住在养老院的 HF 患者的生活质量。
使用逻辑模型,确定了三个工作流程。工作流程 1(WS1)由三个步骤组成,将为模型的“投入”提供信息。首先,将对养老院工作人员进行 20 次定性访谈,以确定向 HF 患者提供护理的促进因素和障碍。同时,将进行范围综述,以综合目前 HF 干预措施在养老院中的证据。最后一步将涉及与 50-70 名主要利益相关者(例如养老院工作人员、HF 患者及其家人和朋友)进行德尔菲研究,以确定与 HF 相关的关键教育重点。使用来自 WS1 的数据,将与 HF 患者或其照顾者、HF 专业人员和养老院工作人员一起共同设计提高养老院工作人员 HF 知识和自我效能的数字干预措施。最后,工作流程 3(WS3)将涉及对数字干预措施进行混合方法可行性测试。结果包括 HF 知识和照顾 HF 居民的自我效能、干预措施的可用性、数字干预措施对养老院居民生活质量的预期益处,以及护理人员实施干预措施的经验。
由于 HF 影响着许多养老院居民,因此养老院工作人员必须具备在这些环境中支持 HF 患者的能力。由于这一领域的干预研究有限,预计由此产生的数字干预措施将对全国和国际范围内 HF 居民的护理具有相关性。