This document describes a project called HCC Viz that aims to improve clinical decision making for hepatocellular carcinoma (HCC) patients through the use of visual analytics. It establishes a user-centered design process where clinicians identify questions, visualization experts design visualizations of national HCC registry data, and clinicians provide feedback. The goal is to incorporate successful visualizations into a clinical decision support tool to help multidisciplinary teams treating HCC patients.

1. Learning from the Data: Exploring a Hepatocellular Carcinoma Registry Using
Visual Analytics to Improve Multidisciplinary Clinical Decision-Making
Michelle Hribar PhD, L. Nelson Sanchez-Pinto MD, Kate Fultz Hollis MS, Gene Ren, Deborah Woodcock MBA
Department of Medical Informatics & Clinical Epidemiology
Oregon Health & Science University, Portland, OR
SOLUTION: HCC VIZ
http://hccviz.azurewebsites.net/
Each visualization includes information about how it may be used;
the website also provides space for user feedback and discussion.
CLINICAL CHALLENGES
 Oncology care is increasingly complex.
 Treatment modalities have become more integrated, with
multidisciplinary teams (MDTs) delivering patient care.
 MDTs are particularly necessary for hepatocellular
carcinoma (HCC), the most common primary liver cancer
and a multifaceted disease offering a poor prognosis.1
 MDTs offer:
 Improved care through collaborative decision-making.
 The potential to become rapid-learning environments if
given access to meaningful information.
 MDT treatment decision-making is difficult.
 Treatment guidelines are often vague.
 Patient data resides in multiple locations.
 Decisions are affected by local treatment patterns.
 The OHSU HCC MDT is developing the
Multidisciplinary Bioinformatics Data (MDBD) tool to:
 Gather data about patients, treatments, and outcomes.
 Create national registry of HCC treatment data.
Design question:
How can we display HCC national population data in
ways that improve MDT clinical decision-making?
USER-CENTERED DESIGN
1. HCC tumor board members identify clinical
questions for exploration with national MDBD
data and post them to HCC Viz.
2. HCC Viz community members iteratively
discuss, design, and update visualizations.
 Informaticians
 Data visualization developers
 Data analysts
 HCC providers
3. HCC providers test visualizations.
4. Best visualizations are incorporated into the
MDBD.
5. Informaticians and analysts evaluate the
usability and impact of the visualizations.
 Clinical decision-making
 Patient outcomes
DATA CHALLENGES
 Unlocking national registry data will be key to
improving treatments and outcomes.
 Detailed national HCC data has not been available.
 Most clinicians cannot envision how data might be used.
 Complex healthcare data visualization is an emerging
field.
 Data interaction can be even more difficult to envision.
 Data visualization developers do not have clinical
knowledge.
 Development cycle can be slow.
 It is difficult to elicit meaningful user feedback.
FUTURE PLANS
 Launch HCC Viz website with pilot visualizations.
 Recruit MDBD providers and data visualization experts.
 Disseminate visualizations at clinical and data
visualization conferences.
 Include successful visualizations in MDBD tool.
 Formally evaluate visualizations for effectiveness of
MDT decision-making and patient outcomes.
 Extend HCC Viz and visualization use cases to other
cancer and disease areas, such as:
 Endocrine oncology
 Dermatology
2015
HCC Viz is an online community of clinicians,
informaticians, and data analysts that creates
meaningful visualizations of complex data.
Users can discuss and update
existing visualizations, as well
as request new visualizations.
Note: Sample visualizations use artificial data and
should not be used for clinical care.
1. Naugler WE, Alsina AE, Frenette CT, Rossaro L, Sellers MT. Building the Multidisciplinary Team for Management
of Patients With Hepatocellular Carcinoma. Clin Gastroenterol Hepatol. Elsevier, Inc; 2015;13(5):827–35.