Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations

Wang, Taowei David; Wongsuphasawat, Krist; Plaisant, Catherine; Shneiderman, Ben

doi:10.1007/s10916-011-9718-x

Cited by 52 publications

(42 citation statements)

References 26 publications

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“…The characterization (▶ Table 2) of the visualization methods applied in the reviewed projects was based on the results and conclusions sections of the papers [24][25][26][27][28][30][31][32][33][34][35][36][37][38].…”

Section: Characterization Of the Visualization Methodsmentioning

confidence: 99%

Visualization of Medical Data Based on EHR Standards

Kopanitsa

Hildebrand²,

Stausberg³

et al. 2013

Methods Inf Med

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SummaryBackground: To organize an efficient interaction between a doctor and an EHR the data has to be presented in the most convenient way. Medical data presentation methods and models must be flexible in order to cover the needs of the users with different backgrounds and requirements. Most visualization methods are doctor oriented, however, there are indications that the involvement of patients can optimize healthcare. Objectives: The research aims at specifying the state of the art of medical data visualization. The paper analyzes a number of projects and defines requirements for a generic ISO 13606 based data visualization method. In order to do so it starts with a systematic search for studies on EHR user interfaces. Methods: In order to identify best practices visualization methods were evaluated according to the following criteria: limits of application, customizability, re-usability. The visualization methods were compared by using specified criteria. Results: The review showed that the analyzed projects can contribute knowledge to the development of a generic visualization method. However, none of them proposed a model that meets all the necessary criteria for a re-usable standard based visualization method. The shortcomings were mostly related to the structure of current medical concept specifications. Conclusion:The analysis showed that medical data visualization methods use hardcoded GUI, which gives little flexibility. So medical data visualization has to turn from a hardcoded user interface to generic methods. This requires a great effort because current standards are not suitable for organizing the management of visualization data. This contradiction between a generic method and a flexible and user-friendly data layout has to be overcome.

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Section: Characterization Of the Visualization Methodsmentioning

confidence: 99%

Visualization of Medical Data Based on EHR Standards

Kopanitsa

Hildebrand²,

Stausberg³

et al. 2013

Methods Inf Med

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“…If an interface is designed such that the user can filter, arrange, and annotate the information in ways that facilitate the categorization task, the actions can be viewed as complementary. Empirical studies (e.g., [25][26][27][28][29][30]) suggest that complementary interactions can contribute positively towards performing diverse sensemaking activities with visualizations. For example, Groth and Streefkerk [26] found that allowing users to interact with 3D molecular visualizations, by rotating and annotating their elements, seemed to support users' performance of knowledge discovery tasks.…”

Section: Complementary Interactionsmentioning

confidence: 99%

Supporting Sensemaking of Complex Objects with Visualizations: Visibility and Complementarity of Interactions

et al. 2016

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Making sense of complex objects is difficult, and typically requires the use of external representations to support cognitive demands while reasoning about the objects. Visualizations are one type of external representation that can be used to support sensemaking activities. In this paper, we investigate the role of two design strategies in making the interactive features of visualizations more supportive of users' exploratory needs when trying to make sense of complex objects. These two strategies are visibility and complementarity of interactions. We employ a theoretical framework concerned with human-information interaction and complex cognitive activities to inform, contextualize, and interpret the effects of the design strategies. The two strategies are incorporated in the design of Polyvise, a visualization tool that supports making sense of complex four-dimensional geometric objects. A mixed-methods study was conducted to evaluate the design strategies and the overall usability of Polyvise. We report the findings of the study, discuss some implications for the design of visualization tools that support sensemaking of complex objects, and propose five design guidelines. We anticipate that our results are transferrable to other contexts, and that these two design strategies can be used broadly in visualization tools intended to support activities with complex objects and information spaces.

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“…Lifelines2 [23,24] aligns patient records by chosen events and can group patients by matching exact sequences of events. More sophisticated temporal queries (including temporal constraints and time spans between query elements) have been implemented in PatternFinder [25].…”

Section: Cohort Visualizationmentioning

confidence: 99%

Bringing cohort studies to the bedside: framework for a ‘green button’ to support clinical decision-making

Gallego

Walter

Day

et al. 2015

J. Compar. Effect. Res.

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When providing care, clinicians are expected to take note of clinical practice guidelines, which offer recommendations based on the available evidence. However, guidelines may not apply to individual patients with comorbidities, as they are typically excluded from clinical trials. Guidelines also tend not to provide relevant evidence on risks, secondary effects and long-term outcomes. Querying the electronic health records of similar patients may for many provide an alternate source of evidence to inform decision-making. It is important to develop methods to support these personalized observational studies at the point-of-care, to understand when these methods may provide valid results, and to validate and integrate these findings with those from clinical trials.

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Extracting Insights from Electronic Health Records: Case Studies, a Visual Analytics Process Model, and Design Recommendations

Cited by 52 publications

References 26 publications

Visualization of Medical Data Based on EHR Standards

Visualization of Medical Data Based on EHR Standards

Supporting Sensemaking of Complex Objects with Visualizations: Visibility and Complementarity of Interactions

Bringing cohort studies to the bedside: framework for a ‘green button’ to support clinical decision-making

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