Department of Internal Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
Pulmonary, Allergy, & Critical Care Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, USA.
BMJ Open Qual. 2023 Dec 28;12(4):e002466. doi: 10.1136/bmjoq-2023-002466.
Cystic fibrosis (CF) is a systemic autosomal recessive condition characterised by progressive lung disease. CF pulmonary exacerbations (PEx) are episodes of worsening respiratory status, and frequent PEx are a risk factor for accelerated lung function decline, yet many people with CF (PwCF) go untreated at the time of decline. The goal of this quality improvement (QI) initiative was to improve recognition, treatment and follow-up of PEx in PwCF.
Using the Model for Improvement, the Cystic Fibrosis Learning Network (CFLN) initiated a QI innovation laboratory (iLab) with a global aim to decrease the rate of lung function decline in PwCF. The iLab standardised definitions for signals of PEx using a threshold for decline in forced expiratory volume in one second (FEV) and/or changes in symptoms. The FEV decline signal was termed FIES (FEV-indicated exacerbation signal). Processes for screening and recognition of FIES and/or symptom changes, a treatment algorithm and follow-up in the presence of a signal were tested concurrently in multiple settings.
The specific aim is to increase the per cent of PwCF assessed for a PEx signal at ambulatory encounters and to increase the per cent of recommendations to follow-up within 6 weeks for PwCF experiencing a PEx signal.
FIES recognition increased from 18.6% to 73.4% across all teams during the iLab, and every team showed an improvement. Of PwCF assessed, 15.8% experienced an FIES event (>10% decline in FEV per cent predicted (FEVpp)). Follow-up within 6 weeks was recommended for an average of 70.5% of those assessed for FIES and had an FEVpp decline greater than 5%.
The CFLN iLab successfully defined and implemented a process to recognise and follow-up PEx signals. This process has the potential to be spread to the larger CF community. Further studies are needed to assess the impact of these processes on PwCF outcomes.
囊性纤维化(CF)是一种系统性常染色体隐性疾病,其特征是进行性肺部疾病。CF 肺部恶化(PEx)是呼吸状况恶化的发作,频繁的 PEx 是加速肺功能下降的风险因素,但许多 CF 患者(PwCF)在下降时未得到治疗。本质量改进(QI)计划的目标是改善 PwCF 中 PEx 的识别、治疗和随访。
使用改进模型,囊性纤维化学习网络(CFLN)启动了一个全球 QI 创新实验室(iLab),旨在降低 PwCF 中肺功能下降的速度。该 iLab 使用一秒用力呼气量(FEV)下降和/或症状变化的阈值来标准化 PEx 信号的定义。FEV 下降信号称为 FIES(FEV 指示的恶化信号)。同时在多个环境中测试了用于筛查和识别 FIES 和/或症状变化、治疗算法以及存在信号时的随访的流程。
具体目标是增加在门诊就诊时评估 PwCF 出现 PEx 信号的百分比,并增加对出现 PEx 信号的 PwCF 进行 6 周内随访的百分比。
在 iLab 期间,所有团队的 FIES 识别率从 18.6%增加到 73.4%,每个团队都有所提高。在评估的 PwCF 中,有 15.8%经历了 FIES 事件(FEVpp 预测值下降超过 10%)。平均有 70.5%的评估对象因 FIES 而建议在 6 周内进行随访,并且 FEVpp 下降超过 5%。
CFLN iLab 成功定义并实施了识别和随访 PEx 信号的流程。该流程有可能推广到更大的 CF 社区。需要进一步的研究来评估这些流程对 PwCF 结果的影响。