Heimdall, a Computer Program for Electronic Health Records Data Visualization. Martignene, N.; Balcaen, T.; Bouzille, G.; Calafiore, M.; Beuscart, J.; Lamer, A.; Legrand, B.; Ficheur, G.; and Chazard, E. Studies in Health Technology and Informatics, 270:247–251, June, 2020.
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INTRODUCTION: Electronic health records (EHR) comprehend structured and unstructured data, that are usually time dependent, enabling the use of timelines. However, it is often difficult to display all data without inducing information overload. In both clinical usual care and medical research, users should be able to quickly find relevant information, with minimal cognitive overhead. Our goal was to devise simple visualization techniques for handling medical data in both contexts. METHODS: An abstraction layer for structured EHR data was devised after an informal literature review and discussions between authors. The "Heimdall" prototype was developed. Two experts evaluated the tool by answering 5 questions on 24 clinical cases. RESULTS: Temporal data was abstracted in three simple types: events, states and measures, with appropriate visual representations for each type. Heimdall can load and display complex heterogeneous structured temporal data in a straightforward way. The main view can display events, states and measures along a shared timeline. Users can summarize data using temporal, hierarchical compression and filters. Default and custom views can be used to work in problem- oriented ways. The evaluation found conclusive results. CONCLUSION: The "Heimdall" prototype provides a comprehensive and efficient graphical interface for EHR data visualization. It is open source, can be used with an R package, and is available at https://koromix.dev/files/R.
@article{martignene_heimdall_2020,
	title = {Heimdall, a {Computer} {Program} for {Electronic} {Health} {Records} {Data} {Visualization}},
	volume = {270},
	issn = {1879-8365},
	doi = {10.3233/SHTI200160},
	abstract = {INTRODUCTION: Electronic health records (EHR) comprehend structured and unstructured data, that are usually time dependent, enabling the use of timelines. However, it is often difficult to display all data without inducing information overload. In both clinical usual care and medical research, users should be able to quickly find relevant information, with minimal cognitive overhead. Our goal was to devise simple visualization techniques for handling medical data in both contexts.
METHODS: An abstraction layer for structured EHR data was devised after an informal literature review and discussions between authors. The "Heimdall" prototype was developed. Two experts evaluated the tool by answering 5 questions on 24 clinical cases.
RESULTS: Temporal data was abstracted in three simple types: events, states and measures, with appropriate visual representations for each type. Heimdall can load and display complex heterogeneous structured temporal data in a straightforward way. The main view can display events, states and measures along a shared timeline. Users can summarize data using temporal, hierarchical compression and filters. Default and custom views can be used to work in problem- oriented ways. The evaluation found conclusive results.
CONCLUSION: The "Heimdall" prototype provides a comprehensive and efficient graphical interface for EHR data visualization. It is open source, can be used with an R package, and is available at https://koromix.dev/files/R.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Martignene, Niels and Balcaen, Thibaut and Bouzille, Guillaume and Calafiore, Matthieu and Beuscart, Jean-Baptiste and Lamer, Antoine and Legrand, Bertrand and Ficheur, Grégoire and Chazard, Emmanuel},
	month = jun,
	year = {2020},
	pmid = {32570384},
	keywords = {Electronic health records, Feature extraction, Timeline, Visualization},
	pages = {247--251},
}
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