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

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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.

In: BMC Medical Informatics and Decision Making, Vol. 19, No. 1, 170, 22.08.2019.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Ledesma, A, Bidargaddi, N, Strobel, J, Schrader, G, Nieminen, H, Korhonen, I & Ermes, M 2019, 'Health timeline: an insight-based study of a timeline visualization of clinical data', BMC Medical Informatics and Decision Making, vol. 19, no. 1, 170. https://doi.org/10.1186/s12911-019-0885-x

APA

Ledesma, A., Bidargaddi, N., Strobel, J., Schrader, G., Nieminen, H., Korhonen, I., & Ermes, M. (2019). Health timeline: an insight-based study of a timeline visualization of clinical data. BMC Medical Informatics and Decision Making, 19(1), [170]. https://doi.org/10.1186/s12911-019-0885-x

Vancouver

Ledesma A, Bidargaddi N, Strobel J, Schrader G, Nieminen H, Korhonen I et al. Health timeline: an insight-based study of a timeline visualization of clinical data. BMC Medical Informatics and Decision Making. 2019 Aug 22;19(1). 170. https://doi.org/10.1186/s12911-019-0885-x

Author

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. In: BMC Medical Informatics and Decision Making. 2019 ; Vol. 19, No. 1.

Bibtex - Download

@article{88f5daf866e2429fb268566401af4ef9,
title = "Health timeline: an insight-based study of a timeline visualization of clinical data",
abstract = "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.",
keywords = "Health informatics, data visualisation, decision making, electronic health records",
author = "Andres Ledesma and Niranjan Bidargaddi and J{\"o}rg Strobel and Geoffrey Schrader and Hannu Nieminen and Ilkka Korhonen and Miikka Ermes",
year = "2019",
month = "8",
day = "22",
doi = "10.1186/s12911-019-0885-x",
language = "English",
volume = "19",
journal = "BMC Medical Informatics and Decision Making",
issn = "1472-6947",
publisher = "Springer Verlag",
number = "1",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Health timeline: an insight-based study of a timeline visualization of clinical data

AU - Ledesma, Andres

AU - Bidargaddi, Niranjan

AU - Strobel, Jörg

AU - Schrader, Geoffrey

AU - Nieminen, Hannu

AU - Korhonen, Ilkka

AU - Ermes, Miikka

PY - 2019/8/22

Y1 - 2019/8/22

N2 - 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.

AB - 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.

KW - Health informatics

KW - data visualisation

KW - decision making

KW - electronic health records

U2 - 10.1186/s12911-019-0885-x

DO - 10.1186/s12911-019-0885-x

M3 - Article

VL - 19

JO - BMC Medical Informatics and Decision Making

JF - BMC Medical Informatics and Decision Making

SN - 1472-6947

IS - 1

M1 - 170

ER -