A Human Centered GeoVisualization framework to facilitate visual exploration of telehealth data: A case study

Article type: Research Article

Authors: Joshi, Ashish^{a; b; *} | de Araujo Novaes, Magdala^a | Machiavelli, Josiane^c | Iyengar, Sriram^c | Vogler, Robert^b | Johnson, Craig^b | Zhang, Jiajie^b | Hsu, Chiehwen E.^b

Affiliations: [a] Center for Global Health and Development, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA | [b] School of Biomedical Informatics, University of Texas Health Science Center, University of Texas, Houston, TX, USA | [c] Department of Medicine, Federal University of Pernambuco, Recife, Pernambuco, Brazil

Correspondence: [*] Corresponding author: Ashish Joshi, MD, Center for Global Health and Development, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA. Tel.: +1 402 559 2327; Fax: +1 402 559 4961; E-mail: ashish.joshi@unmc.edu.

Abstract: Purpose:Public health data is typically organized by geospatial units. Routine geographic monitoring of health data enables an understanding of the spatial patterns of events in terms of causes and controls. GeoVisualization (GeoVis) allows users to see information hidden both visually and explicitly on a map. Despite the applicability of GeoVis in public health, it is still underused for visualizing public health data. The objective of this study is to examine the perception of telehealth users' to utilize GeoVis as a proof of concept to facilitate visual exploration of telehealth data in Brazil using principles of human centered approach and cognitive fit theory. Methods:A mixed methods approach combining qualitative and quantitative assessments was utilized in this cross sectional study conducted at the Telehealth Center of the Federal University of Pernambuco (NUTE-UFPE), Recife, Brazil. A convenient sample of 20 participants currently involved in NUTES was drawn during a period of Sep–Oct 2011. Data was gathered using previously tested questionnaire surveys and in-person interviews. Socio-demographic Information such as age, gender, prior education, familiarity with the use of computer and GeoVis was gathered. Other information gathered included participants' prior spatial analysis skills, level of motivation and use of GeoVis in telehealth. Audio recording was done for all interviews conducted in both English and Portuguese, and transcription of the audio content to English was done by a certified translator. Univariate analysis was performed and means and standard deviations were reported for the continuous variables and frequency distributions for the categorical variables. For the open-ended questions, we utilized a grounded theory to identify themes and their relationship as they emerge from the data. Analysis of the quantitative data was performed using SAS V9.1 and qualitative data was performed using NVivo9. Results:The average age of participants was 28 years (SD=7), a majority of them were females and 100% were professionals with graduate degrees. The users had diverse backgrounds including nursing, computer science, biomedical informatics, statistics, dentistry, administration and engineering. The users had varied roles and responsibilities, used computers frequently but only 5% of them were familiar with GeoVis. Google maps were the most common GeoVis application that the users were familiar with. Despite having minimal spatial skills, there was a strong motivation and relevance among the telehealth users to use GeoVis to facilitate visual exploration of telehealth data for better informed decision making. Results also showed that of the 60% participants with no GeoVis familiarity; 33% had moderate to large data exploratory role, 83% had no spatial skills but 58% preferred analyzing both spatial and temporal dimensions of the data. Majority of the participants agreed to have maps as the first choice to represent the data as it will be able to display the events both in place and time. Discussion:The results demonstrate a potentially growing need for the use of GeoVis applications to evaluate telehealth data. Understanding of user needs is essential to ensure that the technology is appropriately functional and will be useful to complete the tasks.

Keywords: GeoVisualization, Human Centered, public health, cognitive fit theory, telehealth

DOI: 10.3233/THC-2012-0683

Journal: Technology and Health Care, vol. 20, no. 6, pp. 487-501, 2012