gms | German Medical Science

49. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds)
19. Jahrestagung der Schweizerischen Gesellschaft für Medizinische Informatik (SGMI)
Jahrestagung 2004 des Arbeitskreises Medizinische Informatik (ÖAKMI)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie
Schweizerische Gesellschaft für Medizinische Informatik (SGMI)

26. bis 30.09.2004, Innsbruck/Tirol

The use of a PDMS for an immediate indication of nutrition status in an intensive care unit

Meeting Abstract (gmds2004)

  • corresponding author presenting/speaker Joachim Steinwendner - Department of Anaesthesiology, perioperative Medicine and Intensive Care Medicine, Paracelsus Private Medical University Hospital, Salzburg, Österreich
  • A Pobatschnig - Department of Anaesthesiology, perioperative Medicine and Intensive Care Medicine, Paracelsus Private Medical University Hospital, Salzburg, Österreich
  • A Zimmermann - Department of Anaesthesiology, perioperative Medicine and Intensive Care Medicine, Paracelsus Private Medical University Hospital, Salzburg, Österreich

Kooperative Versorgung - Vernetzte Forschung - Ubiquitäre Information. 49. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 19. Jahrestagung der Schweizerischen Gesellschaft für Medizinische Informatik (SGMI) und Jahrestagung 2004 des Arbeitskreises Medizinische Informatik (ÖAKMI) der Österreichischen Computer Gesellschaft (OCG) und der Österreichischen Gesellschaft für Biomedizinische Technik (ÖGBMT). Innsbruck, 26.-30.09.2004. Düsseldorf, Köln: German Medical Science; 2004. Doc04gmds324

The electronic version of this article is the complete one and can be found online at: http://www.egms.de/en/meetings/gmds2004/04gmds324.shtml

Published: September 14, 2004

© 2004 Steinwendner et al.
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Outline

Text

Introduction

The determination of the nutrition status and decision for a nutrition therapy in an intensive care unit requires a multitude of indicators and calculations (lab findings, patient status, enteral or parenteral nutrition, energy supply, excretion, etc.). As a result the ward round is often considerably delayed since the information is distributed on various documentation pages, or the importance of nutrition is often neglected by resorting to patient-independent feeding standards. The goal of this work is to include all the relevant parameters as well as the latest insights in intensive care nutrition [1], [2] in a patient data management system (PDMS) to enable a quick and reliable nutrition overview for the attending practitioner, nurses and dieticians. This approach results in an optimal feeding of intensive care patients and effective time usage per ward round.

Methods

At the intensive care unit of the department of anaesthesiology, perioperative medicine and intensive care medicine, Salzburg, the PDMS, quantitative sentinel (QS) from General Electric [3], is in use. This system allows a flexible configuration to the requirements of an intensive care unit.

The nutrition page of the QS-system [Fig. 1] is composed of a tabular chart of parameters over 3 days enabling to see not only the current status but also a trend over time. This is especially important in the first few days of a post-operative phase, where a careful patient-dependent nutrition development is required. Secondly, parameter description pages are provided as information source for the medical staff. This allows to react to new findings in intensive care and nutrition science. Thirdly, an excretion page provides information about the patient's reaction to feeding. In the following, a more detailed description of the nutrition page is given:

Patient parameters: These parameters consist of length of stay, the actual weight, the normal weight and the body mass index (BMI) of the patient.

Supply of energy: The whole supply of energy, the non-protein energy and the whole energy exclusive the parenteral protein energy is given in kcal per 24 hours. These columns show on the one hand the actual supply of energy and on the other hand the required supply of energy based upon the patients degree of illness and patient parameters, thus allowing a comparison of actual and required energy supply at a glance.

Nutrient composition:This part calculates glucose, proteins and lipids in g/24 h and in energy percentage based on the enteral and parenteral supply and nutrition-effective medication.

Lab findings: Only the most relevant parameters are included in these columns, i.e. glucosis, lactate for glucose assessment; urea and prealbumin for protein assessment; and triglyceride for lipids assessment. In addition, dispositions are made for a bi-weekly calculation of the nitrogen-balance.

Nutrition: Last but not least the current rate of nutrition and nutrition-effective medication is indicated.

Note that the nutrition page provides an abbreviated view of the nutrition-relevant information available. In case of need of more detailed information, all data is available for an in-depth analysis of the patient.

Results

The installation of this page in the intensive care unit leads to a significant time reduction in judging the nutrition status of a patient. More time is therefore available on the decision for the optimal therapy rather than calculating and finding the relevant patient information.

Discussion

Note that this is not an expert system (as for example in [4]) but rather a pure information system, since it gives no suggestion on the nutrition therapy. It is planned to provide a web-based decision support system concerning intensive care nutrition. However, the authors think that the information about the nutrition status and a knowledge-based support system should be kept strictly separated in order not to confuse information and therapy suggestions.

Acknowledgments

We would like to thank the "Arbeitsgruppe Ernährung (Maria Benedikt, Nina Mitteregger, Sabine Neumann, Sandra Stanzel, Michaela Mandl)" of the Salzburger Landeskliniken for fruitful discussions.


References

1.
Hackl JM. Leitfaden Künstliche Ernährung. 3. Auflage. Wien: Zuckerschwerdt; 1999.
2.
Stein J, Jauch KW. Praxishandbuch klinische Ernährung und Infusionstherapie. Berlin: Springer; 2003.
3.
GE Medical Systems. QS Version 5.06.0 Patient Care Manual. 2001.
4.
Horn W, Popow C, Miksch S, Kirchner L, Seyfang A. Development and Evaluation of VIE-PNN, a knowledge-based system for calculating the parenteral nutrition of newborn infants. Artificial Intelligence in Medicine, Special Issue: Knowledge-based Systems in Routine Use: Lessons Learnt, pp. 217-228, 24(3), 2002.