Dataset Information

Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy.

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.

SUBMITTER: Marx G

PROVIDER: S-EPMC8039261 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy.

Marx Gernot G Bickenbach Johannes J Fritsch Sebastian Johannes SJ Kunze Julian Benedict JB Maassen Oliver O Deffge Saskia S Kistermann Jennifer J Haferkamp Silke S Lutz Irina I Voellm Nora Kristiana NK Lowitsch Volker V Polzin Richard R Sharafutdinov Konstantin K Mayer Hannah H Kuepfer Lars L Burghaus Rolf R Schmitt Walter W Lippert Joerg J Riedel Morris M Barakat Chadi C Stollenwerk André A Fonck Simon S Putensen Christian C Zenker Sven S Erdfelder Felix F Grigutsch Daniel D Kram Rainer R Beyer Susanne S Kampe Knut K Gewehr Jan Erik JE Salman Friederike F Juers Patrick P Kluge Stefan S Tiller Daniel D Wisotzki Emilia E Gross Sebastian S Homeister Lorenz L Bloos Frank F Scherag André A Ammon Danny D Mueller Susanne S Palm Julia J Simon Philipp P Jahn Nora N Loeffler Markus M Wendt Thomas T Schuerholz Tobias T Groeber Petra P Schuppert Andreas A

BMJ open 20210408 4

<h4>Introduction</h4>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.<h4>Methods and analysis</h4>In this quality improvement strategy (QIS), a decision suppor ...[more]

PMID: 34550901

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Dataset Information

Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy.

Introduction

Methods and analysis

Ethics and dissemination

Trial registration number

Publications

Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy.

Similar Datasets

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