Using domiciliary non-invasive ventilator data downloads to inform clinical decision-making to optimise ventilation delivery and patient compliance

Stephanie K Mansell, Steven Cutts, Isobel Hackney, Martin J Wood, Kevin Hawksworth, Dean D Creer, Cherry Kilbride, Swapna Mandal, Stephanie K Mansell, Steven Cutts, Isobel Hackney, Martin J Wood, Kevin Hawksworth, Dean D Creer, Cherry Kilbride, Swapna Mandal

Abstract

Introduction: Ventilation parameter data from patients receiving home mechanical ventilation can be collected via secure data cards and modem technology. This can then be reviewed by clinicians and ventilator prescriptions adjusted. Typically available measures include tidal volume (VT), leak, respiratory rate, minute ventilation, patient triggered breaths, achieved pressures and patient compliance. This study aimed to assess the potential impact of ventilator data downloads on management of patients requiring home non-invasive ventilation (NIV).

Methods: A longitudinal within-group design with repeated measurements was used. Baseline ventilator data were downloaded, reviewed and adjustments made to optimise ventilation. Leak, VT and compliance data were collected for comparison at the first review and 3-7 weeks later. Ventilator data were monitored and amended remotely via a modem by a consultant physiotherapist between the first review and second appointment.

Results: Analysis of data from 52 patients showed increased patient compliance (% days used >4 hours) from 90% to 96% (p=0.007), increased usage from 6.53 to 6.94 hours (p=0.211) and a change in VT(9.4 vs 8.7 mL/kg/ideal body weight, p=0.022). There was no change in leak following review of NIV prescriptions (mean (SD): 43 (23.4) L/min vs 45 (19.9)L/min, p=0.272).

Conclusion: Ventilator data downloads, via early remote assessment, can help optimise patient ventilation through identification of modifiable factors, in particular interface leak and ventilator prescriptions. However, a prospective study is required to assess whether using ventilator data downloads provides value in terms of patient outcomes and cost-effectiveness. The presented data will help to inform the design of such a study.

Keywords: Non-invasive Ventilation; Software; Technology.

Conflict of interest statement

Competing interests: SKM and SC have received sponsorship from Philips Respironics for conference attendance. SKM has provided consultation and speaker services to Philips Respironics.

Figures

Figure 1
Figure 1
Flow diagram of patient progress through the study. ITU, intensive treatment unit; NIV, non-invasive ventilation.
Figure 2
Figure 2
Changes in tidal volume (VT, mL/kg/ideal body weight) following non-invasive ventilation prescription review.
Figure 3
Figure 3
Compliance with non-invasive ventilation percentage of days with >4 hours use.
Figure 4
Figure 4
Compliance with non-invasive ventilation average hours/day before and after non-invasive ventilation prescription review.

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Source: PubMed

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