Visual Analysis of Compliance with Clinical Guidelines

Bodesinsky, Peter; Federico, Paolo; Miksch, Silvia

doi:10.1145/2494188.2494202

Cited by 12 publications

(8 citation statements)

References 22 publications

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“…Other examples use visualizations to identify interesting behavior and patterns in the event log data (e.g., [43,7]), or to investigate process conformance (e.g. [49,1,8]). In this position paper I give by no means a comprehensive list of visualization approaches in the context of process mining.…”

Section: Visual Approaches For Process Miningmentioning

confidence: 99%

“…Hence, they can be seen as process models. Bodesinsky et al [8] presented a visual interactive approach to analyze the compliance of clinical care with these guidelines. The approach is aimed at supporting (1) physicians at the point of care to display clinical guidelines and point them to omitted clinical actions, and (2) medical experts in retrospective analysis of the quality of the treatment and also of the quality of the clinical practice guideline.…”

Section: Visual Analysis Of Guideline Conformancementioning

confidence: 99%

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Visual Analytics Meets Process Mining: Challenges and Opportunities

Gschwandtner

2017

Lecture Notes in Business Information Processing

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Event data or traces of activities often exhibit unexpected behavior and complex relations. Thus, before and during the application of automated analysis methods, such as process mining algorithms, the analyst needs to investigate and understand the data at hand in order to decide which analysis methods might be appropriate. Visual analytics integrates the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment. The combination of visual data exploration with process mining algorithms makes complex information structures more comprehensible and facilitates new insights. In this position paper I portray various concepts of interactive visual support for process mining, focusing on the challenges, but also the great opportunities for analyzing process data with visual analytics methods.

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Section: Visual Approaches For Process Miningmentioning

confidence: 99%

Section: Visual Analysis Of Guideline Conformancementioning

confidence: 99%

Visual Analytics Meets Process Mining: Challenges and Opportunities

Gschwandtner

2017

Lecture Notes in Business Information Processing

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“…Another recent work using Asbru, following from CareVis, and specifically designed to analyse compliance with clinical guidelines is presented by Bodesinsky et al [35]. The authors use visualisation to integrate information about executed treatments with Computer Interpretable Guidelines.…”

Section: State-of-the-artmentioning

confidence: 99%

Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice

Bettencourt‐Silva

Mannu

Iglesia

2016

Lecture Notes in Computer Science

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Abstract. Routinely collected data in hospital Electronic Medical Records (EMR) is rich and abundant but often not linked or analysed for purposes other than direct patient care. We have created a methodology to integrate patient-centric data from different EMR systems into clinical pathways that represent the history of all patient interactions with the hospital during the course of a disease and beyond. In this paper, the literature in the area of data visualisation in healthcare is reviewed and a method for visualising the journeys that patients take through care is discussed. Examples of the hidden knowledge that could be discovered using this approach are explored and the main application areas of visualisation tools are identified. This paper also highlights the challenges of collecting and analysing such data and making the visualisations extensively used in the medical domain. This paper starts by presenting the state-of-the-art in visualisation of clinical and other health related data. Then, it describes an example clinical problem and discusses the visualisation tools and techniques created for the utilisation of these data by clinicians and researchers. Finally, we look at the open problems in this area of research and discuss future challenges.

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“…The main objective of CareCruiser [12] is to support the simultaneous visualization of the logical structure and the time-oriented aspects of computer-executable clinical plans, as well as the effects of treatments on the patient's condition. The visualization of quantitative data as a line plot can be complemented by several qualitative abstractions, such as the distance from the intended value, the progress from the initial value and the slope (gradient), as well as the compliance with the clinical guidelines [7]; these metrics are encoded in a level for each time point, and mapped to the chart background colour along the time axis.…”

Section: Related Workmentioning

confidence: 99%

Qualizon graphs

Federico

Hoffmann

Rind

et al. 2014

Proceedings of the 2014 International Working Conference on Advanced Visual Interfaces

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In several application fields, the joint visualization of quantitative data and qualitative abstractions can help analysts make sense of complex time series data by associating precise numeric values with corresponding domain-specific interpretations, such as good, bad, high, low, normal. At the same time, the need to analyse large multivariate time-oriented datasets often calls for keeping visualizations as compact as possible. In this paper, we introduce Qualizon Graphs, a compact visualization that combines quantitative data and qualitative abstractions. It is based on the well known Horizon Graphs, but instead of a predefined number of equally sized bands, it uses as many bands as qualitative categories with corresponding different sizes. In this way, Qualizon Graphs increase the data density of visualized quantitative values and inherently integrate qualitative abstractions. A user study shows that Qualizon Graphs are as fast and accurate as Horizon Graphs for quantitative data, and are an alternative to state-of-the-art visualizations for both quantitative and qualitative data, enabling a trade-off between speed and accuracy.

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Visual Analysis of Compliance with Clinical Guidelines

Cited by 12 publications

References 22 publications

Visual Analytics Meets Process Mining: Challenges and Opportunities

Visual Analytics Meets Process Mining: Challenges and Opportunities

Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice

Qualizon graphs

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