Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy. Issue 4 (8th April 2021)
- Record Type:
- Journal Article
- Title:
- Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy. Issue 4 (8th April 2021)
- Main Title:
- Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy
- Authors:
- Marx, Gernot
Bickenbach, Johannes
Fritsch, Sebastian Johannes
Kunze, Julian Benedict
Maassen, Oliver
Deffge, Saskia
Kistermann, Jennifer
Haferkamp, Silke
Lutz, Irina
Voellm, Nora Kristiana
Lowitsch, Volker
Polzin, Richard
Sharafutdinov, Konstantin
Mayer, Hannah
Kuepfer, Lars
Burghaus, Rolf
Schmitt, Walter
Lippert, Joerg
Riedel, Morris
Barakat, Chadi
Stollenwerk, André
Fonck, Simon
Putensen, Christian
Zenker, Sven
Erdfelder, Felix
Grigutsch, Daniel
Kram, Rainer
Beyer, Susanne
Kampe, Knut
Gewehr, Jan Erik
Salman, Friederike
Juers, Patrick
Kluge, Stefan
Tiller, Daniel
Wisotzki, Emilia
Gross, Sebastian
Homeister, Lorenz
Bloos, Frank
Scherag, André
Ammon, Danny
Mueller, Susanne
Palm, Julia
Simon, Philipp
Jahn, Nora
Loeffler, Markus
Wendt, Thomas
Schuerholz, Tobias
Groeber, Petra
Schuppert, Andreas
… (more) - Abstract:
- Abstract : Introduction: The acute respiratory distress syndrome (ARDS) is a highly relevant entity in critical care with mortality rates of 40%. Despite extensive scientific efforts, outcome-relevant therapeutic measures are still insufficiently practised at the bedside. Thus, there is a clear need to adhere to early diagnosis and sufficient therapy in ARDS, assuring lower mortality and multiple organ failure. Methods and analysis: In this quality improvement strategy (QIS), a decision support system as a mobile application (ASIC app), which uses available clinical real-time data, is implemented to support physicians in timely diagnosis and improvement of adherence to established guidelines in the treatment of ARDS. ASIC is conducted on 31 intensive care units (ICUs) at 8 German university hospitals. It is designed as a multicentre stepped-wedge cluster randomised QIS. ICUs are combined into 12 clusters which are randomised in 12 steps. After preparation (18 months) and a control phase of 8 months for all clusters, the first cluster enters a roll-in phase (3 months) that is followed by the actual QIS phase. The remaining clusters follow in month wise steps. The coprimary key performance indicators (KPIs) consist of the ARDS diagnostic rate and guideline adherence regarding lung-protective ventilation. Secondary KPIs include the prevalence of organ dysfunction within 28 days after diagnosis or ICU discharge, the treatment duration on ICU and the hospital mortality.Abstract : Introduction: The acute respiratory distress syndrome (ARDS) is a highly relevant entity in critical care with mortality rates of 40%. Despite extensive scientific efforts, outcome-relevant therapeutic measures are still insufficiently practised at the bedside. Thus, there is a clear need to adhere to early diagnosis and sufficient therapy in ARDS, assuring lower mortality and multiple organ failure. Methods and analysis: In this quality improvement strategy (QIS), a decision support system as a mobile application (ASIC app), which uses available clinical real-time data, is implemented to support physicians in timely diagnosis and improvement of adherence to established guidelines in the treatment of ARDS. ASIC is conducted on 31 intensive care units (ICUs) at 8 German university hospitals. It is designed as a multicentre stepped-wedge cluster randomised QIS. ICUs are combined into 12 clusters which are randomised in 12 steps. After preparation (18 months) and a control phase of 8 months for all clusters, the first cluster enters a roll-in phase (3 months) that is followed by the actual QIS phase. The remaining clusters follow in month wise steps. The coprimary key performance indicators (KPIs) consist of the ARDS diagnostic rate and guideline adherence regarding lung-protective ventilation. Secondary KPIs include the prevalence of organ dysfunction within 28 days after diagnosis or ICU discharge, the treatment duration on ICU and the hospital mortality. Furthermore, the user acceptance and usability of new technologies in medicine are examined. To show improvements in healthcare of patients with ARDS, differences in primary and secondary KPIs between control phase and QIS will be tested. Ethics and dissemination: Ethical approval was obtained from the independent Ethics Committee (EC) at the RWTH Aachen Faculty of Medicine (local EC reference number: EK 102/19) and the respective data protection officer in March 2019. The results of the ASIC QIS will be presented at conferences and published in peer-reviewed journals. Trial registration number: DRKS00014330. … (more)
- Is Part Of:
- BMJ open. Volume 11:Issue 4(2021)
- Journal:
- BMJ open
- Issue:
- Volume 11:Issue 4(2021)
- Issue Display:
- Volume 11, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 11
- Issue:
- 4
- Issue Sort Value:
- 2021-0011-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04-08
- Subjects:
- adult intensive & critical care -- information technology -- health informatics -- respiratory medicine (see thoracic medicine)
Medicine -- Research -- Periodicals
610.72 - Journal URLs:
- http://www.bmj.com/archive ↗
http://bmjopen.bmj.com/ ↗ - DOI:
- 10.1136/bmjopen-2020-045589 ↗
- Languages:
- English
- ISSNs:
- 2044-6055
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
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