Abstract Rationale Early detection of disease worsening in interstitial lung disease (ILD) remains a critical unmet need, as acute exacerbations and unrecognized progression drive high morbidity, mortality, and healthcare use. Home-based monitoring offers a transformative opportunity to detect clinically meaningful change earlier, improve triage for in-person care, and reduce preventable hospitalizations. Yet, despite growing availability of digital tools, the optimal combination of home monitoring components that maximizes clinical utility, feasibility, and patient acceptability in ILD remains undefined. Building on the 2025 ATS Research Statement which highlighted the heterogeneity and implementation challenges of home-based monitoring in chronic lung disease, this study applied an implementation-driven, quantitative optimization framework to identify home monitoring components best suited for early detection of clinically significant ILD events - defined as acute exacerbation, hospitalization, or ≥ 10% relative decline in FVC over 3 months. Methods This single-center Multiphase Optimization Strategy Trial (MOST) of adults with ILD consists of three sequential phases: preparation, optimization and evaluation. In the preparation phase a scoping review of evidence and device validation studies was conducted to assess available home monitoring tools. Candidate components were evaluated using a weighted composite scoring framework incorporating seven optimization criteria: clinical alignment (0.25), data quality (0.20), feasibility (0.15), sensitivity to change (0.15), equity and scalability (0.10), patient engagement (0.10) and incremental value (0.05). Scores were derived from available from ILD-specific data when available or extrapolated from other chronic lung diseases. Results Ten candidate components were systematically scored (Table 1), with five additional components designated as exploratory due to limited ILD-specific evidence. Electronic PROs (4.60) and spirometry (4.05) demonstrated the strongest evidence for clinical alignment, sensitivity to change, and feasibility. Oximetry (3.90) and weight (3.85) ranked highest for scalability, affordability, and patient engagement, while continuous cough monitoring (3.70) emerged as a promising tool with high incremental value. Supporting components - including activity, heart rate, and medication monitoring - offered complementary behavioral and physiologic insights but lower ILD specificity. Conclusion Applying a structured implementation-informed optimization framework, this study defines an evidence-based foundation for assembling a pragmatic, feasible, and scalable home monitoring package for early detection of clinically significant ILD events. In the next optimization phase, electronic PROs, spirometry, oximetry, weight, and cough monitoring will be tested using a randomized factorial design to identify the most effective and acceptable combination of components for confirmatory testing (evaluation phase.) This approach represents a critical step towards translating digital health research into actionable, equitable, and evidence-based ILD care. This abstract is funded by: NIH
Farrand et al. (Fri,) studied this question.