Personalizing Selection of Inhaled Delivery Systems in Chronic Obstructive Pulmonary Disease

ANNALS OF THE AMERICAN THORACIC SOCIETY(2023)

引用 0|浏览0
暂无评分
摘要
It can be challenging for healthcare professionals (HCPs) to prescribe inhaled therapy for patients with chronic obstructive pulmonary disease (COPD) because of the multiple individual and combinations of inhaled medications available in numerous delivery systems. Guidance on the selection of an inhaled delivery system has received limited attention compared with the emphasis on prescribing the class of the inhaled molecule(s). Although numerous recommendations and algorithms have been proposed to guide the selection of an inhaled delivery system for patients with COPD, no specific approach has been endorsed in COPD guidelines/strategies or by professional organizations. To provide recommendations for an inhaler selection strategy at initial and follow-up appointments, we examined the impact of patient errors using handheld inhalers on clinical outcomes and performed a focused narrative review to consider patient factors (continuity of the inhaled delivery system, cognitive function, manual function/dexterity, and peak inspiratory flow) when selecting an inhaled delivery system. On the basis of these findings, five questions are proposed for HCPs to consider in the initial selection of an inhaler delivery system and three questions to consider at follow-up. We propose that HCPs consider the inhaled medication delivery system as a unit and to match appropriate medication(s) with the unique features of the delivery system to individual patient factors. Assessment of inhaler technique and adherence together with patient outcomes/satisfaction at each visit is essential to determine whether the inhaled medication delivery system is providing benefits. Continued and repeated education on device features and correct technique is warranted to optimize efficacy.
更多
查看译文
关键词
inhaled delivery systems, dyspnea, exacerbations, shared decision making, inhaled bronchodilators
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