Cargando…

Health timeline: an insight-based study of a timeline visualization of clinical data

BACKGROUND: The increasing complexity and volume of clinical data poses a challenge in the decision-making process. Data visualizations can assist in this process by speeding up the time required to analyze and understand clinical data. Even though empirical experiments show that visualizations faci...

Descripción completa

Detalles Bibliográficos
Autores principales: Ledesma, Andres, Bidargaddi, Niranjan, Strobel, Jörg, Schrader, Geoffrey, Nieminen, Hannu, Korhonen, Ilkka, Ermes, Miikka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6704521/
https://www.ncbi.nlm.nih.gov/pubmed/31438942
http://dx.doi.org/10.1186/s12911-019-0885-x
_version_ 1783445517967032320
author Ledesma, Andres
Bidargaddi, Niranjan
Strobel, Jörg
Schrader, Geoffrey
Nieminen, Hannu
Korhonen, Ilkka
Ermes, Miikka
author_facet Ledesma, Andres
Bidargaddi, Niranjan
Strobel, Jörg
Schrader, Geoffrey
Nieminen, Hannu
Korhonen, Ilkka
Ermes, Miikka
author_sort Ledesma, Andres
collection PubMed
description BACKGROUND: The increasing complexity and volume of clinical data poses a challenge in the decision-making process. Data visualizations can assist in this process by speeding up the time required to analyze and understand clinical data. Even though empirical experiments show that visualizations facilitate clinical data understanding, a consistent method to assess their effectiveness is still missing. METHODS: The insight-based methodology determines the quality of insights a user acquires from the visualization. Insights receive a value from one to five points based on a domain-specific criteria. Five professional psychiatrists took part in the study using real de-identified clinical data spanning 4 years of medical history. RESULTS: A total of 50 assessments were transcribed and analyzed. Comparing a total of 558 insights using Health Timeline and 576 without, the mean value using the Timeline (1.7) was higher than without (1.26; p<0.01), similarly the cumulative value with the Timeline (11.87) was higher than without (10.96: p<0.01). The average time required to formulate the first insight with the Timeline was higher (13.16 s) than without (7 s; p<0.01). Seven insights achieved the highest possible value using Health Timeline while none were obtained without it. CONCLUSIONS: The Health Timeline effectively improved understanding of clinical data and helped participants recognize complex patterns from the data. By applying the insight-based methodology, the effectiveness of the Health Timeline was quantified, documented and demonstrated. As an outcome of this exercise, we propose the use of such methodologies to measure the effectiveness of visualizations that assist the clinical decision-making process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0885-x) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6704521
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-67045212019-08-22 Health timeline: an insight-based study of a timeline visualization of clinical data Ledesma, Andres Bidargaddi, Niranjan Strobel, Jörg Schrader, Geoffrey Nieminen, Hannu Korhonen, Ilkka Ermes, Miikka BMC Med Inform Decis Mak Research Article BACKGROUND: The increasing complexity and volume of clinical data poses a challenge in the decision-making process. Data visualizations can assist in this process by speeding up the time required to analyze and understand clinical data. Even though empirical experiments show that visualizations facilitate clinical data understanding, a consistent method to assess their effectiveness is still missing. METHODS: The insight-based methodology determines the quality of insights a user acquires from the visualization. Insights receive a value from one to five points based on a domain-specific criteria. Five professional psychiatrists took part in the study using real de-identified clinical data spanning 4 years of medical history. RESULTS: A total of 50 assessments were transcribed and analyzed. Comparing a total of 558 insights using Health Timeline and 576 without, the mean value using the Timeline (1.7) was higher than without (1.26; p<0.01), similarly the cumulative value with the Timeline (11.87) was higher than without (10.96: p<0.01). The average time required to formulate the first insight with the Timeline was higher (13.16 s) than without (7 s; p<0.01). Seven insights achieved the highest possible value using Health Timeline while none were obtained without it. CONCLUSIONS: The Health Timeline effectively improved understanding of clinical data and helped participants recognize complex patterns from the data. By applying the insight-based methodology, the effectiveness of the Health Timeline was quantified, documented and demonstrated. As an outcome of this exercise, we propose the use of such methodologies to measure the effectiveness of visualizations that assist the clinical decision-making process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0885-x) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-22 /pmc/articles/PMC6704521/ /pubmed/31438942 http://dx.doi.org/10.1186/s12911-019-0885-x Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Ledesma, Andres
Bidargaddi, Niranjan
Strobel, Jörg
Schrader, Geoffrey
Nieminen, Hannu
Korhonen, Ilkka
Ermes, Miikka
Health timeline: an insight-based study of a timeline visualization of clinical data
title Health timeline: an insight-based study of a timeline visualization of clinical data
title_full Health timeline: an insight-based study of a timeline visualization of clinical data
title_fullStr Health timeline: an insight-based study of a timeline visualization of clinical data
title_full_unstemmed Health timeline: an insight-based study of a timeline visualization of clinical data
title_short Health timeline: an insight-based study of a timeline visualization of clinical data
title_sort health timeline: an insight-based study of a timeline visualization of clinical data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6704521/
https://www.ncbi.nlm.nih.gov/pubmed/31438942
http://dx.doi.org/10.1186/s12911-019-0885-x
work_keys_str_mv AT ledesmaandres healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata
AT bidargaddiniranjan healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata
AT strobeljorg healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata
AT schradergeoffrey healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata
AT nieminenhannu healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata
AT korhonenilkka healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata
AT ermesmiikka healthtimelineaninsightbasedstudyofatimelinevisualizationofclinicaldata