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Using Remote Telemonitoring to Detect Early Decline in Lung Function & Streamline Clinics in Adults With Cystic Fibrosis

Not Applicable
Completed
Conditions
Cystic Fibrosis
Interventions
Device: Bluetooth enabled nebuliser device (I-neb)
Registration Number
NCT02399241
Lead Sponsor
Sheffield Teaching Hospitals NHS Foundation Trust
Brief Summary

Lung Health research study (Development of a predictive model) - To determine whether the I-neb breathing parameters (flow data) can act as a surrogate marker for lung function (Forced Expiratory Volume in 1 second FEV1) hence allow early detection of decline in lung function in cystic fibrosis patients.

Detailed Description

1. Initial phase of the study will involve retrospective data collection, to review 36 months of retrospectively collected clinic time data (i.e. total length of appointment, length of time seen by each discipline, waiting time). This data is routinely collected and displayed in run charts. It will be used to allow an understanding of the baseline variability in a standard un-streamed clinic and whether distinct patient sub-populations can be identified i.e. red (complicated and time consuming) and green (simple and rapidly processed) streams. These data may suggest a starting structure for clinic slot lengths and provide a baseline comparator for the subsequent bespoke clinic structures.

2. In the prospective intervention phase, To recruit 50 participants to take part in the bespoke clinics using a home spirometer, weighing scales, and Bluetooth enabled I-neb providing breathing parameter and adherence data.

3. Participants' baseline routinely collected demographics (age, gender, genotype) and clinical data (including comorbidities, number of intravenous antibiotic days and clinic attendances per year, and treatment regime) will be recorded.

4. At baseline participants will be asked to complete the Patient Activation Measure questionnaire. This patient-reported measure is a powerful reliable tool which has been validated in the UK24. It involves 13 quick questions to identify a patient's knowledge, skills, and confidence in managing their own health and health care.

5. Participants will be asked to measure lung function and weight one week prior to clinic. The I-neb adherence and flow data will be routinely captured and transferred.

6. Prior to clinic when this data is collected participants will be asked the EQ-5D-5L as before, if they require a repeat prescription, and whether there are any issues they would like to focus on when they attend for their consultation.

7. This data will then be reviewed to determine which stream patients would be predicted to need to require. i.e. adherence support, diagnostic, or stable brief review.

8. Following review the standard clinic process will be analysed to see whether the streaming would have been appropriate and if it could have potentially saved time and resources.

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
50
Inclusion Criteria
  • Patients with a confirmed diagnosis of cystic fibrosis via genetic testing
  • Patients aged 16 and above
  • Patients using inhaled mucolytics (to loosen secretions) or antibiotic treatments via the I-neb for all or part of their treatment
  • Patients who have capacity to give informed consent
Exclusion Criteria
  • Patients with a lung transplant
  • Patients on the active transplant list
  • Patients who are pregnant (due to the variability of lung function during pregnancy)
  • Patients in the palliative end stage of their life
  • Patients using inhaled treatments with no objective adherence measure

Study & Design

Study Type
INTERVENTIONAL
Study Design
SINGLE_GROUP
Arm && Interventions
GroupInterventionDescription
Remote telemonitoring of clinical dataBluetooth enabled nebuliser device (I-neb)Bluetooth enabled nebuliser device (I-neb) providing breathing parameters and adherence data.
Primary Outcome Measures
NameTimeMethod
Forced Expiratory Volume in 1 secondBaseline to 6 months

The study will develop a predictive model and conduct a parallel service improvement project. It therefore does not have a specific primary outcome measure. The predictive model will be attempting to identify if there is a correlation between the I-neb breathing parameters (i.e. inhalation time, rest time) and lung function (Forced Expiratory Volume in 1 second FEV1). The clinic streaming will attempt to identify if the preclinic data (lung function, weight, adherence) can predict the clinic needs of a patient.

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Northern General Hospital, Sheffield Teaching Hospitals NHS Foundation Trust

🇬🇧

Sheffield, South Yorkshire, United Kingdom

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