Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jan 24;21(1):5.
doi: 10.1186/s12938-021-00974-5.

Transparent decision support for mechanical ventilation using visualization of clinical preferences

Stephen Edward Rees  1 , Savino Spadaro  2 , Francesca Dalla Corte  3 , Nilanjan Dey  4 , Jakob Bredal Brohus  5 , Gaetano Scaramuzzo  2 , David Lodahl  6 , Robert Ravnholt Winding  4 , Carlo Alberto Volta  2 , Dan Stieper Karbing  7
Affiliations

Transparent decision support for mechanical ventilation using visualization of clinical preferences

Stephen Edward Rees et al. Biomed Eng Online. .

Abstract

Background: Systems aiding in selecting the correct settings for mechanical ventilation should visualize patient information at an appropriate level of complexity, so as to reduce information overload and to make reasoning behind advice transparent. Metaphor graphics have been applied to this effect, but these have largely been used to display diagnostic and physiologic information, rather than the clinical decision at hand. This paper describes how the conflicting goals of mechanical ventilation can be visualized and applied in making decisions. Data from previous studies are analyzed to assess whether visual patterns exist which may be of use to the clinical decision maker.

Materials and methods: The structure and screen visualizations of a commercial clinical decision support system (CDSS) are described, including the visualization of the conflicting goals of mechanical ventilation represented as a hexagon. Retrospective analysis is performed on 95 patients from 2 previous clinical studies applying the CDSS, to identify repeated patterns of hexagon symbols.

Results: Visual patterns were identified describing optimal ventilation, over and under ventilation and pressure support, and over oxygenation, with these patterns identified for both control and support modes of mechanical ventilation. Numerous clinical examples are presented for these patterns illustrating their potential interpretation at the bedside.

Conclusions: Visual patterns can be identified which describe the trade-offs required in mechanical ventilation. These may have potential to reduce information overload and help in simple and rapid identification of sub-optimal settings.

Keywords: Clinical decision support; Clinical preferences; Mechanical ventilation.

PubMed Disclaimer

Conflict of interest statement

DSK and SER are minor shareholders and SER a board member of Mermaid Care A/S the manufacturer of the Beacon Caresystem. JBB is an employee of Mermaid Care A/S.

Figures

Fig. 1
Fig. 1
Patterns of clinical trade-offs identified in clinical data
Fig. 2
Fig. 2
The structure of the Beacon Caresystem and output screens illustrating physiologic state and advice/preference visualisation screen illustrating a patient in control mode ventilation. The following abbreviations are used on the physiologic screen (all others in text): Shunt: pulmonary shunt; ΔPO2: partial pressure O2 drop due to low V/Q; ΔPCO2: partial pressure CO2 drop due to high V/Q; EELV: end expiratory lung volume; Vd: serial dead space; COMP: respiratory system compliance; SID-CSF: model estimated strong ion difference of the CSF; Tc: Threshold to central respiratory drive; BE: base excess; Hb: haemoglobin; DPG: 2,3 diphosphoglycerate; VO2: oxygen consumption; VCO2: carbon dioxide production; CO: cardiac output. For the physiologic screen where values are missing, they were not necessary for this specific patient and not estimated by the system
Fig. 3
Fig. 3
Balances necessary when setting the appropriate levels of mechanical ventilation
See this image and copyright information in PMC

References

    1. Brower RG, Matthay MA, Morris A, et al. Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N Engl J Med. 2000;342(18):1301–1308. doi: 10.1056/NEJM200005043421801. - DOI - PubMed
    1. Bellani G, Laffey JG, Pham T, LUNG SAFE Investigators. ESICM Trials Group et al. Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in intensive care units in 50 countries. JAMA. 2016;315(8):788–800. doi: 10.1001/jama.2016.0291. - DOI - PubMed
    1. Blagev DP, Hirshberg EL, Sward K, et al. The evolution of eProtocols that enable reproducible clinical research and care methods. J Clin Monit Comput. 2012;26:305–317. doi: 10.1007/s10877-012-9356-y. - DOI - PubMed
    1. East TD, Heermann LK, Bradshaw RL, et al. Efficacy of computerized decision support for mechanical ventilation: results of a prospective multi-center randomized trial. In: Proceedings of the American medical Informatics Association. 1999, pp. 251–5. - PMC - PubMed
    1. Dojat M, Brochard L, Lemaire F, et al. A knowledge-based system for assisted ventilation of patients in intensive care units. Int J Clin Monit Comput. 1992;9:239–250. doi: 10.1007/BF01133619. - DOI - PubMed

LinkOut - more resources