Objective Frailty is a prevalent risk factor for adverse outcomes among patients with chronic lung disease. However, identifying frail patients who may benefit from interventions is challenging using standard data sources. We therefore sought to identify phrases in clinical notes in the electronic health record (EHR) that describe actionable frailty syndromes. Materials and Methods We used an active learning strategy to select notes from the EHR and annotated each sentence for 4 actionable aspects of frailty: respiratory impairment, musculoskeletal problems, fall risk, and nutritional deficiencies. We compared the performance of regression, tree-based, and neural network models to predict the labels for each sentence. We evaluated performance with the scaled Brier score (SBS), where 1 is perfect and 0 is uninformative, and the positive predictive value (PPV). Results We manually annotated 155 952 sentences from 326 patients. Elastic net regression had the best performance across all 4 frailty aspects (SBS 0.52, 95% confidence interval [CI] 0.49–0.54) followed by random forests (SBS 0.49, 95% CI 0.47–0.51), and multi-task neural networks (SBS 0.39, 95% CI 0.37–0.42). For the elastic net model, the PPV for identifying the presence of respiratory impairment was 54.8% (95% CI 53.3%–56.6%) at a sensitivity of 80%. Discussion Classification models using EHR notes can effectively identify actionable aspects of frailty among patients living with chronic lung disease. Regression performed better than random forest and neural network models. Conclusions NLP-based models offer promising support to population health management programs that seek to identify and refer community-dwelling patients with frailty for evidence-based interventions.

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Many health care organizations made public commitments to become antiracist in the wake of George Floyd's murder. These actions raise questions about the appropriateness of health care's engagement in racial justice and social justice movements generally. We argue that health care organizations can be usefully thought of as having two roles: a functional role to care for the sick and a meta‐role as an organizational citizen. Fulfilling the role of citizen may require participating in the pursuit of social justice, including efforts to achieve racial equity. The demands of these two roles will need to be balanced, but the role of organizational citizen has been largely ignored and merits serious attention.

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