Back

Study Report from the Pragmatic Assessment of the NuvoAir Clinical Service in the Management of Patients with Chronic Obstructive Pulmonary Disease

Harker, E.; Van Wormer, J. J.; Qiao, D.

2025-11-13 respiratory medicine
10.1101/2025.11.11.25339788 medRxiv
Show abstract

BackgroundCOPD is one of the leading causes of death, disability and avoidable hospitalization in the US and abroad, yet proactive management of COPD has historically been limited. This study evaluates NuvoAir Home Service (NAHS), a novel intervention that integrates telemedicine, remote monitoring, and chronic-care management to deliver proactive care to patients with COPD. MethodsWe present findings from a six-month pragmatic program evaluation. Patients with COPD enrolled in NAHS were compared with propensity-matched controls using a two-period difference-in-difference (DID) design. Results280 NAHS participants compared to 840 propensity matched controls showed a reduction of 47% in post-to-pre risk ratio (RR) for COPD-related hospitalization (p = 0.06), 55% in average days of hospital stay (p = 0.02), 53% in hospital readmissions (p = 0.32). There was no significant change in ED visits (p=0.83), and in outpatient office visits (p=0.89). All-cause utilization moved in similar directions, but none of those changes were statistically significant. COPD-related total medical cost and hospitalization cost from medical claims were also significantly reduced with a 28% reduction (p-value = 0.05) and a 53% reduction (p-value = 0.02) in post-to-pre cost ratio. No significant changes were observed in all-cause hospitalization, all-cause and COPD-related ED, outpatient, or pharmacy costs. ConclusionThese data indicate that NuvoAir Home Service had a clinically positive impact on COPD-related hospital utilization and costs without significantly increasing ED or outpatient use, though not all results met statistical significance.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.