Estimating rate of lung function change using clinical spirometry data.

In chronic obstructive pulmonary disease (COPD), accurately estimating lung function from electronic health record (EHR) data would be beneficial but requires addressing complexities in clinically obtained testing. This study compared analytic methods for estimating rate of forced expiratory volume in one second (FEV We estimated rate of FEV Among 1417 participants, median rate of change was approximately -30 mL/year or -2%/year. Non-regressive methods frequently generated erroneous estimates due to outlier first measurements or short intervals between tests. Average change yielded the most extreme estimates (minimum=-3761 mL/year), while regressive methods, and Huber specifically, minimised extreme estimates. Huber, Total Change and Quantile FEV Using EHR data to estimate FEV

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© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

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Competing interests: None declared.