Waveform data capture substantial variation in tidal volume and other respiratory parameters

Area of Science:

• Critical Care Medicine
• Biomedical Engineering
• Health Informatics

Background:

• Accurate assessment of invasive mechanical ventilation (IMV) parameters is crucial for patient care.
• Routine electronic health record (EHR) documentation often misses critical variations in ventilator data due to intermittent missingness.

Purpose of the Study:

• To evaluate the variability of continuously measured ventilator parameters.
• To assess the agreement between continuous measurements and intermittent EHR documentation.

Main Methods:

• Retrospective cohort study of patients on IMV in a medical intensive care unit.
• Comparison of continuous device waveform data with intermittent EHR documentation for key ventilator parameters.
• Statistical analysis including descriptive statistics and measures of agreement.

Main Results:

• Continuous measurements captured significantly more parameter variation than EHR documentation.
• Tidal volume showed the largest errors (mean absolute error 69 mL) and poorer agreement in mandatory ventilation modes (correlation coefficient 0.454).

Conclusions:

• Intermittent ventilator parameter measurement fails to capture substantial variability present in continuous waveform data.
• Discrepancies in parameters like tidal volume suggest ventilator waveform data can enhance patient care and research for IMV patients.