CareVis: Integrated visualization of computerized protocols and temporal patient data

https://doi.org/10.1016/j.artmed.2006.04.002Get rights and content

Summary

Objective

Currently, visualization support for patient data analysis is mostly limited to the representation of directly measured data. Contextual information on performed treatment steps is an important source to find reasons and explanations for certain phenomena in the measured patient data, but is mostly spared out in the analysis process. This work aims to fill this gap via integrating classical data visualization and visualization of treatment information.

Methods and material

We considered temporal as well as logical data aspects and applied a user-centered development approach that was guided by user input gathered via a user study, design reviews, and prototype evaluations. Furthermore, we investigated the novel PlanningLine glyph, that is used to represent plans in the temporal domain, via a comparative empirical user study.

Results

Our interactive visualization approach CareVis provides multiple simultaneous views to cover different aspects of the complex underlying data structure of treatment plans and patient data. The tightly coupled views use visualization methods well-known to domain experts and are designed to facilitate users’ tasks. The views are based on the concepts of clinical algorithm maps and LifeLines which have been extended in order to cope with the powerful and expressive plan representation language Asbru. Initial feedback of physicians was encouraging and is accompanied by empirical evidence which verifies that PlanningLines are well suited to manage temporal uncertainty.

Conclusion

The interactive integration of different visualization methods forms a novel way of combining, relating, and analyzing different kinds of medical data and information that otherwise would be separated.

Introduction

Visualization is an integral part of intelligent data analysis. On the one hand, visualization is applied for presenting results and on the other hand, human perception might be utilized for driving the analysis process. In the medical domain, mostly patient data measurements are used as basis for analysis either in form of high-frequency data of intensive care settings or low-frequency data, e.g., for long term studies. Current visualization methods are mostly bound to the representation of such measured patient data only, which can be subsumed by the term “data visualization”.

But, there is much more information to be taken into consideration in the analysis process. One of these informational pieces is treatment information, that is, data on which therapeutic steps have been taken at what time, for how long, how often, and the like. So far, contextual information on treatment steps and performed treatments is mostly excluded from first-hand data analysis. The integration is either only performed mentally by physicians or worse, contextual information is lost completely. Such information could be an important source for finding reasons and explanations for certain phenomena in the measured patient data. The goal of this work is the integration and combination of various kinds of data as well as information and presenting it in a coherent way for supporting the data analysis process.

Computer-supported protocol-based care is a field of research that aims for supporting the treatment process along protocols semi-automatically by the use of information technology. The core entity, medical treatment plans, are complex documents, mostly in the form of prose text including tables and figures [1]. Protocol-based care utilizes clinical protocols to assist in quality improvement and reduce process irregularities. Such clinical protocols are a standard set of tasks that define precisely how different classes of patients should be managed or treated. They can be seen as reusable definitions of a particular care process. Not much work has been done in order to communicate the computerized treatment plans to the medical staff. Moreover, a combination with the presentation of patient data when treating a patient along a plan for monitoring and analytic tasks has been considered even less. However, the integrated visualization of patient data and medical treatment plans could be of great assistance to ease the complex task of analyzing medical data and protocols.

In the upcoming section, we will provide a task and data analysis of the problem domain followed by a discussion of related work in Section 3. After this, we will describe the design of our visualization approach CareVis in Section 4. Subsequently, we discuss our user-centered design methodology including prototype implementation, evaluation, and user study results in Section 5. Finally, we describe how users’ tasks are supported and sum up our findings.

Section snippets

Problem analysis

In this section, we analyze the problem domain from a data as well as user’s perspective. At the beginning, we will shortly explain the plan representation language Asbru that our project is based upon. Following this, we illustrate use-cases in form of scenarios and identify major task classes. Finally, we will combine the constraints and requirements to a summary of data characteristics that need to be dealt with.

Related work

In the following, we discuss related work in the areas of medical treatment planning, information visualization, and commercial medical software.

Design of the integrated visualization CareVis

The underlying data structure that we want to communicate to medical domain experts is very complex. Since none of the existing visualization methods can be used to represent all needed data characteristics, we decided to use the approach of multiple views [24]. Multiple views are a well known information visualization method, whereby a number of representations that focus on different aspects of the data are provided for a common underlying data structure [25].

User-centered design, prototype, and evaluation

“New medical information systems, no matter how fast, inexpensive, and easy to use, will not be used more widely until it has been demonstrated to practitioners that these systems provide answers that help solve the problems of patient care.” [31]

When developing our interactive visualization methods, we put forward a user-centered design approach. This included a user study, the discussion of the designed methods in a review step, and the evaluation of our Java prototype as described in the

Supporting users’ tasks

So how can Markus Zolte, Andrea Habacher, and Heinrich Kovanic benefit from our visualization methods in accomplishing their work tasks as described in Section 2.2?

Conclusion

Our goal was to develop visualization and interaction methods for supporting medical personnel in computerized protocol-based care. To achieve this goal, we had to consider several data aspects like the logic, structure, and temporal constraints of plans as given at design-time, data of instantiated plans at execution-time, as well as patient data in form of parameters and variables. Applying a multiple views approach helped to master the complexity of the underlying data structure while using

Acknowledgment

This project is supported by “Fonds zur Förderung der wissenschaftlichen Forschung—FWF” (Austrian Science Fund), grant P15467-INF.

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