Visualizing Opportunity Index Data Using a Dashboard Application: A Tool to Communicate Infant Mortality-Based Area Deprivation Index Information

Abstract

Background An area deprivation index (ADI) is a geographical measure that accounts for socioeconomic factors (e.g., crime, health, and education). The state of Ohio developed an ADI associated with infant mortality: Ohio Opportunity Index (OOI). However, a powerful tool to present this information effectively to stakeholders was needed.

Objectives We present a real use-case by documenting the design, development, deployment, and training processes associated with a dashboard solution visualizing ADI data.

Methods The Opportunity Index Dashboard (OID) allows for interactive exploration of the OOI and its seven domains—transportation, education, employment, housing, health, access to services, and crime. We used a user-centered design approach involving feedback sessions with stakeholders, who included representatives from project sponsors and subject matter experts. We assessed the usability of the OID based on the effectiveness, efficiency, and satisfaction dimensions. The process of designing, developing, deploying, and training users in regard to the OID is described.

Results We report feedback provided by stakeholders for the OID categorized by function, content, and aesthetics. The OID has multiple, interactive components: choropleth map displaying OOI scores for a specific census tract, graphs presenting OOI or domain scores between tracts to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. Changes based on parameter and filter selections are described using a general use-case. In the usability evaluation, the median task completion success rate was 83% and the median system usability score was 68.

Conclusion The OID could assist health care leaders in making decisions that enhance care delivery and policy decision making regarding infant mortality. The dashboard helps communicate deprivation data across domains in a clear and concise manner. Our experience building this dashboard presents a template for developing dashboards that can address other health priorities.

Keywords

data visualization - area level deprivation - geographical information system - infant mortality - social determinants of health

Protection of Human and Animal Subjects

Our study was reviewed by our institutional IRB and deemed exempt.

• References

• 1 Centers for Disease Control and Prevention. Infant Mortality Rates by States. 2019 . Available at: https://www.cdc.gov/nchs/pressroom/sosmap/infant_mortality_rates/infant_mortality.htm . Accessed June 24, 2020
• 2 Ohio Department of Health. 2017 Infant Mortality Report. 2018 . Available at: https://odh.ohio.gov/wps/portal/gov/odh/know-our-programs/infant-and-fetal-mortality/reports/2017-ohio-infant-mortality-report-final
• 3 MacDorman MF, Matthews TJ, Mohangoo AD, Zeitlin J. International comparisons of infant mortality and related factors: United States and Europe, 2010. Natl Vital Stat Rep 2014; 63 (05) 1-6
• 4 Taruscio D, Mantovani A, Carbone P. , et al. Primary prevention of congenital anomalies: recommendable, feasible and achievable. Public Health Genomics 2015; 18 (03) 184-191
• 5 Bada HS, Das A, Bauer CR. , et al. Low birth weight and preterm births: etiologic fraction attributable to prenatal drug exposure. J Perinatol 2005; 25 (10) 631-637
• 6 Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet 2008; 371 (9606): 75-84
• 7 Hauck FR, Tanabe KO, Moon RY. Racial and ethnic disparities in infant mortality. Semin Perinatol 2011; 35 (04) 209-220
• 8 Hogan VK, Rowley D, Bennett T, Taylor KD. Life course, social determinants, and health inequities: toward a national plan for achieving health equity for African American infants--a concept paper. Matern Child Health J 2012; 16 (06) 1143-1150
• 9 Lobel M, Cannella DL, Graham JE, DeVincent C, Schneider J, Meyer BA. Pregnancy-specific stress, prenatal health behaviors, and birth outcomes. Health Psychol 2008; 27 (05) 604-615
• 10 Nagahawatte NT, Goldenberg RL. Poverty, maternal health, and adverse pregnancy outcomes. Ann N Y Acad Sci 2008; 1136: 80-85
• 11 Partridge S, Balayla J, Holcroft CA, Abenhaim HA. Inadequate prenatal care utilization and risks of infant mortality and poor birth outcome: a retrospective analysis of 28,729,765 U.S. deliveries over 8 years. Am J Perinatol 2012; 29 (10) 787-793
• 12 Bryant AS, Worjoloh A, Caughey AB, Washington AE. Racial/ethnic disparities in obstetric outcomes and care: prevalence and determinants. Am J Obstet Gynecol 2010; 202 (04) 335-343
• 13 Ely DM, Driscoll AK. Infant mortality in the United States, 2017: data from the period linked birth/infant death file. Natl Vital Stat Rep 2019; 68 (10) 1-20
• 14 Brown Speights JS, Goldfarb SS, Wells BA, Beitsch L, Levine RS, Rust G. State-level progress in reducing the black-white infant mortality gap, United States, 1999-2013. Am J Public Health 2017; 107 (05) 775-782
• 15 Rossen LM, Khan D, Schoendorf KC. Mapping geographic variation in infant mortality and related black-white disparities in the US. Epidemiology 2016; 27 (05) 690-696
• 16 Northridge ME, Freeman L. Urban planning and health equity. J Urban Health 2011; 88 (03) 582-597
• 17 Williams DR, Collins C. Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Rep 2001; 116 (05) 404-416
• 18 Link BG, Phelan J. Social conditions as fundamental causes of disease. J Health Soc Behav 1995; ; (Spec No): 80-94
• 19 Everett E, Mathioudakis N. Association of area deprivation and diabetic ketoacidosis readmissions: comparative risk analysis of adults vs children with type 1 diabetes. J Clin Endocrinol Metab 2019; 104 (08) 3473-3480
• 20 Allik M, Brown D, Dundas R, Leyland AH. Developing a new small-area measure of deprivation using 2001 and 2011 census data from Scotland. Health Place 2016; 39: 122-130
• 21 Atkinson J, Salmond C, Crampton P. NZDep2013 Index of Deprivation. 2014 . Available at: http://www.otago.ac.nz/wellington/research/hirp/otago020194.html . Accessed November 13, 2019
• 22 Noble M, Wright G, Smith G, Dibben C. Measuring multiple deprivation at the small-area level. Environ Plann A 2006; 38 (01) 168-185
• 23 Mehra R, Shebl FM, Cunningham SD. , et al. Area-level deprivation and preterm birth: results from a national, commercially-insured population. BMC Public Health 2019; 19 (01) 236
• 24 Vos AA, Posthumus AG, Bonsel GJ, Steegers EA, Denktaş S. Deprived neighborhoods and adverse perinatal outcome: a systematic review and meta-analysis. Acta Obstet Gynecol Scand 2014; 93 (08) 727-740
• 25 Acevedo-Garcia D, McArdle N, Noelke C, Huber R, Huntington N, Sofer N. A snapshot of child opportunity across the U.S. 2020 . Available at: http://www.diversitydatakids.org/research-library/data-visualization/snapshot-child-opportunity-across-us . Accessed April 2, 2020
• 26 Virginia Department of Health. Virginia Health Opportunity Index. Available at: https://www.vdh.virginia.gov/omhhe/hoi/dashboards/counties . Accessed April 2, 2020
• 27 Opportunity Nation. Opportunity Index. Available at: https://opportunityindex.org . Accessed April 2, 2020
• 28 UC Davis Center for Regional Change. Regional Opportunity Index. 2014 . Available at: https://interact.regionalchange.ucdavis.edu/roi/webmap/webmap.html . Accessed April 2, 2020
• 29 Streeb D, El-Assady M, Keim D, Chen M. Why Visualize? Untangling a Large Network of Arguments. IEEE transactions on visualization and computer graphics 2019; Advance online publication. Available at: https://doi.org/10.1109/TVCG.2019.2940026 . Accessed April 2, 2020
• 30 Card S. Information visualization. In: Jacko J. , ed. The Human-Computer Interaction Handbook. Boca Raton, FL: CRC Press; 2012: 515-548
• 31 Shneiderman B, Plaisant C, Cohen M, Jacobs S, Elmqvist N, Diakopoulos N. Designing the user interface: strategies for effective human-computer interaction. New York: Pearson; 2016
• 32 Ware C. Information Visualization: Perception for Design. 3rd ed. Waltham, MA: Morgan Kaufmann; 2013
• 33 Townsend P, Phillimore P, Beattie A. Health and Deprivation: Inequality and the North. London: Croom Helm; 1988
• 34 Wahi MM, Dukach N. Visualizing infection surveillance data for policymaking using open source dashboarding. Appl Clin Inform 2019; 10 (03) 534-542
• 35 Jones B. Communicating Data with Tableau. Sebastopol, CA: O'Reilly Media; 2014
• 36 Esri. GIS Mapping Software, Spatial Data Analytics & Location Intelligence. 2019 . Available at: https://www.esri.com/en-us/home . Accessed November 13, 2019
• 37 Wu DTY, Vennemeyer S, Brown K. , et al. Usability testing of an interactive dashboard for surgical quality improvement in a large congenital heart center. Appl Clin Inform 2019; 10 (05) 859-869
• 38 Dowding D, Merrill JA, Barrón Y, Onorato N, Jonas K, Russell D. Usability evaluation of a dashboard for home care nurses. CIN: computers, informatics. Comput Inform Nurs 2019; 37 (01) 11-19
• 39 Bangor A, Kortum P, Miller J. Determining what individual SUS scores mean: adding an adjective rating scale. J Usability Stud 2009; 4 (03) 114-123
• 40 North C. Toward measuring visualization insight. IEEE Comput Graph Appl 2006; 26 (03) 6-9
• 41 Nielsen J, Landauer TK. A mathematical model of the finding of usability problems. Proceedings of ACM INTERCHI'93 Conference on Human Factors in Computing Systems; 1993: 206-213
• 42 Bangor A, Kortum P, Miller J. An empirical evaluation of the System Usability Scale. Int J Hum Comput Interact 2008; 24 (06) 574-594
• 43 Alexander KP. The usability of print and online video instructions. Tech Commun Q 2013; 22 (03) 237-259