Rational Acquiring high-quality spirometry data in a clinical setting is important, particularly when clinical decisions are being aided by the data. This analysis investigates if a remote spirometry monitoring program can be used to support children with Cystic Fibrosis (CF) to achieve a high level of spirometry quality.

Methods Children with CF, from a tertiary centre, were offered a remote monitoring program (patient-facing app + Bluetooth-connected spirometer) as part of their normal CF care. Patients were asked to measure spirometry (3 forced expiratory maneuvers) either if they were unwell at home or if they were using it to improve technique. All data recorded via the app were visible to the patient and to the healthcare providers in real-time via a secure browser-based portal. Patients and the clinical team were provided with feedback on the quality of their home spirometry readings through the use of artificial intelligence (AI) based quality control software (ArtiQ.QC) which assessed the quality of the home spirometry test using the 2019 ATS/ERS criteria and provided a grading of ‘Acceptable, Usable or Unusable’. If the quality of blows were consistently low the clinical team ensured further spirometry training was undertaken either virtually or at their next clinic appointment.

Results 175 patients have been enrolled of which 87 were patients with CF. In May-2023, 18 patients with CF completed home spirometry readings. These patients spent a median time of 5 minutes on the patientMpower app during the month. A total of 91 spirometry maneuvers were completed. All patients achieved a home spirometry graded as ‘Usable’ of those a further 61% (n=11) achieved Acceptable spirometry blow. 44% (n=8) of patients achieved 3 blows that were deemed ‘Acceptable or Usable’ in a session. 62% (n=56) of the home spirometry maneuvers were graded as ‘Usable’ or ‘Acceptable’ by the quality control software.

Conclusion Remote monitoring can be used to support spirometry coaching as seen through patients achieving a high level of usable home spirometry readings (as assessed by quality control software). This high-quality data can support clinical decisions on patient care.

Please refer to page A289 for declarations of interest related to this abstract.