BACKGROUND: The Acute Respiratory Distress Syndome (ARDS) Network low tidal volume (VT) trial paved the ground for mechanically ventilating ARDS patients with a VT of 6 mL/kg ideal body weight (IBW). Although there is no consensus that a low VT is advantageous in non-ARDS patients,it is accepted that high VT should be avoided. Because compliance rates with ventilator recommendations are 30%, there is a need for process improvement. We postulated that a computerized screen prompt that recommended VT based on height would improve compliance with low VT.During ventilator order entry, the computerized decision tool prompts the clinician and encourages ventilation of patients at 8 mL/kg IBW, and 6 mL/kg IBW for patients with ARDS. METHODS: A retrospective review was performed on patients who required volume controlled mechanical ventilation over a 3-y period. Subjects were chosen randomly from the respiratory records of 6 different ICUs at a single tertiary care academic center. Half of the charts selected were before intervention of on-screen prompt, and the other half were after implementation of the computerized decision tool. RESULTS: The initial set VT ranged from 6.26 to 13.45 mL/kg IBW, with a mean of 8.92 mL/kg. After implementation of the on-screen prompt, mean VT decreased by 0.84 mL/kg to 8.07 mL/kg (P= .001) with a lower range of 4.73-11.56 mL/kg IBW. We also noted a significant decrease in the number of subjects placed on an initial VT > 10 mL/kg IBW from 20% to 4% (P= .003). CONCLUSIONS: A computerized clinical decision tool with the preferred initial VT settings based on the patients' sex and height is a safe and reliable way to increase low VT strategy compliance across multiple ICUs. Its limitations are similar to those shared by other computer-generated prompts.
BACKGROUND: The Acute Respiratory Distress Syndome (ARDS) Network low tidal volume (VT) trial paved the ground for mechanically ventilating ARDS patients with a VT of 6 mL/kg ideal body weight (IBW). Although there is no consensus that a low VT is advantageous in non-ARDS patients,it is accepted that high VT should be avoided. Because compliance rates with ventilator recommendations are 30%, there is a need for process improvement. We postulated that a computerized screen prompt that recommended VT based on height would improve compliance with low VT.During ventilator order entry, the computerized decision tool prompts the clinician and encourages ventilation of patients at 8 mL/kg IBW, and 6 mL/kg IBW for patients with ARDS. METHODS: A retrospective review was performed on patients who required volume controlled mechanical ventilation over a 3-y period. Subjects were chosen randomly from the respiratory records of 6 different ICUs at a single tertiary care academic center. Half of the charts selected were before intervention of on-screen prompt, and the other half were after implementation of the computerized decision tool. RESULTS: The initial set VT ranged from 6.26 to 13.45 mL/kg IBW, with a mean of 8.92 mL/kg. After implementation of the on-screen prompt, mean VT decreased by 0.84 mL/kg to 8.07 mL/kg (P= .001) with a lower range of 4.73-11.56 mL/kg IBW. We also noted a significant decrease in the number of subjects placed on an initial VT > 10 mL/kg IBW from 20% to 4% (P= .003). CONCLUSIONS: A computerized clinical decision tool with the preferred initial VT settings based on the patients' sex and height is a safe and reliable way to increase low VT strategy compliance across multiple ICUs. Its limitations are similar to those shared by other computer-generated prompts.
Authors: Curtis H Weiss; David W Baker; Katrina Tulas; Shayna Weiner; Meagan Bechel; Alfred Rademaker; Angela Fought; Richard G Wunderink; Stephen D Persell Journal: Ann Am Thorac Soc Date: 2017-11
Authors: Neil R Euliano; Paul Stephan; Konstantinos Michalopoulos; Michael A Gentile; A Joseph Layon; Andrea Gabrielli Journal: Med Devices (Auckl) Date: 2022-08-05
Authors: Anoopindar K Bhalla; Margaret J Klein; Guillaume Emeriaud; Yolanda M Lopez-Fernandez; Natalie Napolitano; Analia Fernandez; Awni M Al-Subu; Rainer Gedeit; Steven L Shein; Ryan Nofziger; Deyin Doreen Hsing; George Briassoulis; Stavroula Ilia; Florent Baudin; Byron Enrique Piñeres-Olave; Ledys Maria Izquierdo; John C Lin; Ira M Cheifetz; Martin C J Kneyber; Lincoln Smith; Robinder G Khemani; Christopher J L Newth Journal: Crit Care Med Date: 2021-10-01 Impact factor: 9.296
Authors: Briana Short; Alexis Serra; Abdul Tariq; Vivek Moitra; Daniel Brodie; Sapana Patel; Matthew R Baldwin; Natalie H Yip Journal: J Crit Care Date: 2020-09-20 Impact factor: 4.298