Intensive Care Medicine

Impact of Computer-Applications in Intensive Care Medicine

One of the scientific focal points of our research group in the Intensive Care Unit is the investigation of the effects of electronic data processing systems on the treatment of intensive care patients. Here, approaches for the optimal introduction of IT systems are developed and accompanying evaluations of the effects of patient data management systems (PDMS) are carried out.

The focus here is on examining user satisfaction, changes in work processes, effects on various professional groups, cost-benefit analyses and effects on treatment quality and treatment outcome. A particular focus is on projects to expand the system functionality to include decision-support functions of the PDMS and their clinical effects. In doing so, decision-supporting functions are developed in cooperation with the Chair of Medical Informatics, applied clinically, and their effects are examined within the framework of studies.

The data in the electronic patient file are systematically examined for new and unknown facts. To this end, new methods for early disease detection, complex alerting and clinical decision support are being developed. The goal is to improve the quality of treatment and patient safety and thus generate additional clinical benefits from the use of EDP in the intensive care environment.

Current Publications:

1. Castellanos I, Martin M, Kraus S, Bürkle T, Prokosch HU, Schüttler J, Toddenroth D.
   Effects of staff training and electronic event monitoring on long-term adherence to lung-protective ventilation recommendations.
   J Crit Care 2018;43:13-20,  doi.org/10.1016/j.jcrc.2017.06.027
2.  Kraus S, Enders M, Prokosch HU, Castellanos I, Lenz R, Sedlmayr M. Accessing complex patient data from Arden Syntax Medical Logic Modules. Artif Intell Med. 2018 Nov;92:95-102. doi: 10.1016/j.artmed.2015.09.003. Epub 2015 Sep 12. PMID:26409750.
3. Kraus S, Castellanos I, Albermann M, Schuettler C, Prokosch HU, Staudigel M, Toddenroth D.
   Using Arden Syntax for the Generation of Intelligent Intensive Care Discharge Letters.
   Stud Health Technol Inform  2016;228:471-5
4.  Kraus S, Drescher C, Sedlmayr M, Castellanos I, Prokosch HU, Toddenroth D. Using Arden Syntax for the creation of a multi-patient surveillance dashboard. Artif Intell Med. 2018 Nov;92:88-94. doi: 10.1016/j.artmed.2015.09.009. Epub 2015 Oct 9. PMID: 26603750.
5. Castellanos I, Kraus S, Toddenroth D, Prokosch HU, Bürkle T.
   Using Arden Syntax Medical Logic Modules to reduce overutilization of laboratory tests for detection of bacterial infections - Success or failure?
   Artif Intell Med. 2015 Sep 25. doi: 10.1016/j.artmed.2015.09.005
6. Mate S, Bürkle T, Kapsner LA, Toddenroth D, Kampf MO, Sedlmayr M, Castellanos I, Prokosch HU, Kraus S. A method for the graphical modeling of relative temporal constraints. J Biomed Inform. 2019 Dec;100:103314. doi:10.1016/j.jbi.2019.103314. Epub 2019 Oct 17. PMID: 31629921.
7. Schüttler C, Hinderer M, Kraus S, Lang AK, Prokosch HU, Castellanos I. Requirements Analysis for a Clinical Decision Support System Aiming at Improving the Artificial Nutrition of Critically Ill Patients. Stud Health Technol Inform. 2017;243:137-141. PMID: 28883187.