Integration of lung function data: turning snapshots into stories

Abstract

Missing or inaccessible lung function measurements, gathered over time, have the potential to stagnate or impair clinical care decisions being made. This jeopardises patient safety and often contributes to excessive resource utilisation. Data integration is fundamental to clinical decision-making and entails amalgamating lung function data from multiple sources in a user-friendly format. Despite this, current systems for recording lung function data are suboptimal, with copious gaps in the clinical picture arising from missing or inaccessible lung function measurements. This article discusses the importance of data integration for lung function, with a call to action for key stakeholders involved in the performance, management and interpretation of such tests.