TY - JOUR
T1 - Health timeline
T2 - 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
N1 - Funding Information:
This research work was supported by VTT Technical Research Centre of Finland and the EU program for Research and Innovation Horizon 2020.
Funding Information:
VTT Technical Research Centre of Finland has funded the design of the study, collection, analysis and interpretation of data. The writing of the manuscript was funded by the EU program for Research and Innovation Horizon 2020 under the Grant Agreement number 689260.
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 - Clinical data
KW - Data visualization
KW - Electronic health record
KW - Health informatics
KW - Insight-based methodology
UR - http://www.scopus.com/inward/record.url?scp=85071301071&partnerID=8YFLogxK
U2 - 10.1186/s12911-019-0885-x
DO - 10.1186/s12911-019-0885-x
M3 - Article
C2 - 31438942
AN - SCOPUS:85071301071
VL - 19
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
SN - 1472-6947
IS - 1
M1 - 170
ER -