Top

International Journal of Computer Assisted Radiology and Surgery

Published in:

01-08-2018 | Original Article

Information architecture for a patient-specific dashboard in head and neck tumor boards

Authors: Alexander Oeser, Jan Gaebel, Andreas Dietz, Susanne Wiegand, Steffen Oeltze-Jafra

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 8/2018

Abstract

Purpose

Overcoming the flaws of current data management conditions in head and neck oncology could enable integrated information systems specifically tailored to the needs of medical experts in a tumor board meeting. Clinical dashboards are a promising method to assist various aspects of the decision-making process in such cognitively demanding scenarios. However, in order to provide extensive and intuitive assistance to the participating physicians, the design and development of such a system have to be user-centric. To accomplish this task, conceptual methods need to be performed prior to the technical development and integration stages.

Methods

We have conducted a qualitative survey including eight clinical experts with different levels of expertise in the field of head and neck oncology. According to the principles of information architecture, the survey focused on the identification and causal interconnection of necessary metrics for information assessment in the tumor board.

Results

Based on the feedback by the clinical experts, we have constructed a detailed map of the required information items for a tumor board dashboard in head and neck oncology. Furthermore, we have identified three distinct groups of metrics (patient, disease and therapy metrics) as well as specific recommendations for their structural and graphical implementation.

Conclusion

By using the information architecture, we were able to gather valuable feedback about the requirements and cognitive processes of the tumor board members. Those insights have helped us to develop a dashboard application that closely adapts to the specified needs and characteristics, and thus is primarily user-centric.

Murdoch TB, Detsky AS (2013) The inevitable application of big data to health care. JAMA 309(13):1351–1352CrossRefPubMed

Knaup P, Harkener S, Ellsaesser KH, Haux R, Wiedemann T (2001) On the necessity of systematically planning clinical tumor documentation. Methods Inf Med 40(2):90–98CrossRefPubMed

Gaebel J, Cypko MA, Lemke HU (2016) Accessing patient information for probabilistic patient models using existing standards. Stud Health Technol Inform 223:107–112PubMed

Dowding D, Randell R, Gardner P, Fitzpatrick G, Dykes P, Favela J, Hamer S, Whitewood-Moores Z, Hardiker N, Borycki Currie L (2015) Dashboards for improving patient care: review of the literature. Int J Med Inform 84(2):87–100CrossRefPubMed

Meier J, Boehm A, Kielhorn A, Dietz A, Bohn S, Neumuth T (2014) Design and evaluation of a multimedia electronic patient record “oncoflow” with clinical workflow assistance for head and neck tumor therapy. Int J CARS 9(6):949–965CrossRef

Gaebel J, Cypko MA, Oeltze-Jafra S (2017) Considering information up-to-dateness to increase the accuracy of therapy decision support systems. Stud Health Technol Inform 243:217–221PubMed

Stadler JG, Donlon K, Siewert JD, Franken T, Lewis NE (2016) Improving the efficiency and ease of healthcare analysis through use of data visualization dashboards. Big Data 4(2):129–135CrossRefPubMed

Halford GS, Baker R, McCredden JE, Bain JD (2005) How many variables can humans process? Psychol Sci 16(1):70–76CrossRefPubMed

Shneiderman B (1996) The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings 1996 IEEE symposium on visual languages, pp 336–343

10.

Few S (2006) Information dashboard design: the effective visual communication of data. O’Reilly & Associates, Cambridge (MA)

11.

Pauwels K, Ambler T, Clark B, LaPointe P, Reibstein D, Skiera B, Wierenga B, Wiesel T (2009) Dashboards as a service?: Why, what, how, and what research is needed? J Serv Res 12:175–189CrossRef

12.

Daley K, Richardson J, James I, Chambers A, Corbett D (2013) Clinical dashboard: use in older adult mental health wards. Psychiatr Online 37(3):85–88CrossRef

13.

Toms EG (2002) Information interaction: providing a framework for information architecture. J Am Soc Inf Sci 53(10):855–862CrossRef

14.

Karami M, Langarizadeh M, Fatehi M (2017) Evaluation of effective dashboards: key concepts and criteria. Open Med Inform J 11:52–57CrossRefPubMedPubMedCentral

15.

Batley NJ, Osman HO, Kazzi AA, Musallam KM (2011) Implementation of an emergency department computer system: design features that users value. J Emerg Med 41(6):693–700CrossRefPubMed

16.

Morgan MB, Branstetter BF, Lionetti DM, Richardson JS, Chang PJ (2008) The radiology digital dashboard: effects on report turnaround time. J Digit Imaging 21(1):50–58CrossRefPubMed

17.

Dolan JG, Veazie PJ, Russ AJ (2013) Development and initial evaluation of a treatment decision dashboard. BMC Med Inform Decis Mak 13:51CrossRefPubMedPubMedCentral

18.

Roche. NAVIFY\(^{{\rm TM}}\) Tumor Board solution—Roche diagnostics information solutions [Internet]. Navify\(^{{\rm TM}}\) Tumor Board. [cited 8th January 2018]. https://www.navify.com/tumorboard/

19.

Cypko MA, Wojdziak J, Stoehr M, Kirchner B, Preim B, Dietz A, Lemke HU, Oeltze-Jafra S (2017) Visual verification of cancer staging for therapy decision support. Comput Graph Forum 36(3):109–120

20.

Cypko MA, Stoehr M, Kozniewski M, Druzdzel MJ, Dietz A, Berliner L, Lemke HU (2017) Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment. Int J CARS 12(11):1959–1970CrossRef

21.

Lam H, Bertini E, Isenberg P, Plaisant C, Carpendale S (2012) Empirical studies in information visualization: seven scenarios. IEEE Trans Vis Comput Graph 18(9):1520–1536CrossRefPubMed

22.

Isenberg T, Isenberg P, Chen J, Sedlmair M, Moller T (2013) A systematic review on the practice of evaluating visualization. IEEE Trans Vis Comput Graph 19(12):2818–2827CrossRefPubMed

Title: Information architecture for a patient-specific dashboard in head and neck tumor boards
Authors: Alexander Oeser
Jan Gaebel
Andreas Dietz
Susanne Wiegand
Steffen Oeltze-Jafra
Publication date: 01-08-2018
Publisher: Springer International Publishing
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 8/2018
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-018-1741-7

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Information architecture for a patient-specific dashboard in head and neck tumor boards

Abstract

Purpose

Methods

Results

Conclusion

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 8/2018

An automated liver tumour segmentation from abdominal CT scans for hepatic surgical planning

A novel technology for 3D knee prosthesis planning and treatment evaluation using 2D X-ray radiographs: a clinical evaluation

The intelligent OR: design and validation of a context-aware surgical working environment

3D/2D model-to-image registration by imitation learning for cardiac procedures

Viewpoint planning for quantitative coronary angiography

Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair