Remote Evaluation and Surveillance of Patients With Interstitial Lung Disease: Transforming ILD Care Delivery With Remote Monitoring
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Home Monitoring in Patients with f-ILD.
- Who it may be relevant to
- Registry conditions: Fibrotic Interstitial Lung Disease, IPF and PPF, Lung Fibrosis Interstitial. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
The purpose of this interventional study is to identify which combination of remote monitoring devices (e.g. home spirometry, pulse oximetry, scale, ePROs) is the most feasible (as defined by adherence, retention, and data completeness) and acceptable when used for the detection of clinically significant Interstitial Lung Disease events.
Detailed description
Participants in this 12-month study will use home-based monitoring tools provided by the study and complete electronic patient-reported outcome (ePRO) questionnaires to help assess changes in health status over time. Study procedures include weekly home spirometry for all participants, with some participants also asked to complete daily pulse oximetry monitoring and/or weekly weight measurements, depending on study assignment. The study includes an initial in-person baseline visit and a final in-person visit at Month 12 at the UCSF Interstitial Lung Disease Clinic at the Parnassus Campus. Follow-up study visits at Months 3, 6, and 9 will be conducted remotely via Zoom. Participants will complete study-related assessments throughout the study period using electronic devices and questionnaires from home.
Interventions
- Behavioral Home Monitoring in Patients with f-ILD
Participants will be expected to engage in home monitoring using study-provided devices, including a spirometer, pulse oximeter, and/or wireless scale, all of which will be connected to a secure application on the participant's mobile phone for remote data collection and transmission. Participants will also be expected to adhere to scheduled study visits and complete required study activities throughout the study period.
Primary outcome measures
- Detection rate of clinically significant ILD events [Time frame: Baseline, Month 12]
- Time to detection of first ILD event [Time frame: Baseline, Month 12]
- Adherence [Time frame: 12 months]
- Retention [Time frame: 12 months]
- Data Completeness [Time frame: 12 months]
Secondary outcome measures (9)
- Change in health-related quality of life [Time frame: Baseline, Month 12]
- Change in health-related quality of life [Time frame: Baseline, Month 12]
- Change in FVC [Time frame: Baseline, Month 12]
- Proportion of patients with ≥10% decline in FVC [Time frame: Baseline, Month 12]
- Proportion of patients with a change in ILD-related treatment [Time frame: Baseline, Month 12]
- Patient Engagement and Activation [Time frame: 12 months]
- Patient-reported Satisfaction [Time frame: 12 months]
- Total implementation cost of home monitoring intervention components (per-patient, US dollars) [Time frame: 12 month]
- Unintended Implementation Impact [Time frame: 12 month]
Eligibility criteria
Inclusion criteria
- age 18 or older
- English or Spanish speaking
- have a UCSF diagnosis of one of the major ILD subtypes seen in the ILD Clinic (Idiopathic Pulmonary Fibrosis, Chronic Hypersensitivity Pneumonitis, Connective-tissue disease related ILD, Sarcoidosis, Familial Fibrosis). Languages are limited to those for which both device instructional materials and user support are available (written and video). The ILD diagnosis will be based on multidisciplinary conference review, which is the diagnostic gold standard. We have restricted the ILD subtypes to those for which there is efficacy data for RPM or comparable clinical trajectories, and subtypes that account for >10% of the ILD diagnoses seen at UCSF.
Exclusion criteria
- Patients who are unable provide informed consent for any reason or are acutely ill.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Factorial
- Masking
- Open label
- Primary purpose
- Health services research
Study locations
United States · 1 center
- University of California, San Francisco — San Francisco
Publications
- Ilowite J, Lisker G, Greenberg H. Digital Health Technology and Telemedicine-Based Hospital and Home Programs in Pulmonary Medicine During the COVID-19 Pandemic. Am J Ther. 2021 Feb 3;28(2):e217-e223. doi: 10.1097/MJT.0000000000001342. PMID 33590991
- Handley MA, Lyles CR, McCulloch C, Cattamanchi A. Selecting and Improving Quasi-Experimental Designs in Effectiveness and Implementation Research. Annu Rev Public Health. 2018 Apr 1;39:5-25. doi: 10.1146/annurev-publhealth-040617-014128. Epub 2018 Jan 12. PMID 29328873
- Russell AM, Adamali H, Molyneaux PL, Lukey PT, Marshall RP, Renzoni EA, Wells AU, Maher TM. Daily Home Spirometry: An Effective Tool for Detecting Progression in Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med. 2016 Oct 15;194(8):989-997. doi: 10.1164/rccm.201511-2152OC. PMID 27089018
- Ku JP, Sim I. Mobile Health: making the leap to research and clinics. NPJ Digit Med. 2021 May 14;4(1):83. doi: 10.1038/s41746-021-00454-z. PMID 33990671
- Ge J, Fontil V, Ackerman S, Pletcher MJ, Lai JC. Clinical decision support and electronic interventions to improve care quality in chronic liver diseases and cirrhosis. Hepatology. 2025 Apr 1;81(4):1353-1364. doi: 10.1097/HEP.0000000000000583. Epub 2023 Aug 23. PMID 37611253
- Farrand E, Gologorskaya O, Mills H, Radhakrishnan L, Collard HR, Butte AJ. Machine-Learning Algorithm to Improve Cohort Identification in Interstitial Lung Disease. Am J Respir Crit Care Med. 2023 May 15;207(10):1398-1401. doi: 10.1164/rccm.202211-2092LE. No abstract available. PMID 36943196
- Sim I. Mobile Devices and Health. N Engl J Med. 2019 Sep 5;381(10):956-968. doi: 10.1056/NEJMra1806949. No abstract available. PMID 31483966
- Odisho AY, Liu AW, Maiorano AR, Bigazzi MOA, Medina E, Leard LE, Shah R, Venado A, Perez A, Golden J, Kleinhenz ME, Kolaitis NA, Maheshwari J, Trinh BN, Kukreja J, Greenland J, Calabrese D, Neinstein AB, Singer JP, Hays SR. Design and implementation of a digital health home spirometry intervention for remote monitoring of lung transplant function. J Heart Lung Transplant. 2023 Jun;42(6):828-837. d PMID 37031033
Identifiers
NCT: NCT07673237 · 25-44428 · 5K23HL175213-02