Abstract

DBA’s perspective for Information Visualization (IV) assists in providing a detailed insight about patient history in Electronic Health Records (EHR). These data visualizations are used by different stake holders in public hospitals such as Doctors, Database Administrators (DBA) and visual designers in order to improve health services for patients. This is not possible without the contribution of DBAs, who are directly involved in launching efficient query system and required data retrieval for resulting visualization. EHR database is comprising of different forms of data i.e., numbers, texts, pictures and graphs resulting in a challenge for creating a meaningful visualization for single or multiple patients. DBAs have EHR knowledge gaps, lesser exposure to the transformation process of data into effective visualization and understanding about IV limitations result in poor and less efficient IV tools. This study highlights the challenging factors that affect DBAs in understanding, developing and controlling EHR visualization. These factors are selected after a literature review and further analysis by a questionnaire based study on DBAs in two different government hospitals. This will help in highlighting the limitations of DBAs skills and experience and assist in determining the contribution of their role in the development of future IV applications. This work is a second phase of our ongoing research for designing a model, CARE 1.0, as a future IV solution in multiple EHR.

Keywords:

CARE 1.0, EHR, information visualization, IV knowledge areas, patient data visualization, visual interfaces,

References

1. Bowman, B., N. Elmqvist and T.J. Kelly, 2012. Toward visualization for games: Theory, design space and patterns. IEEE T. Vis. Comput. Gr., 99: 1-1.
   CrossRef    
2. Bui, A.A.T., D.R. Aberle and H. Kangarloo, 2007. TimeLine: Visualizing integrated patient records. IEEE T. Inf. Technol. B., 11: 462-473.
   CrossRef    
3. Faisal, S., A. Blandford and H.W.W. Potts, 2013. Making sense of personal health information: Challenges for information visualization. Health Inform. J., 19(198): 21.
   CrossRef    
4. Farri, O., D.S. Pieckiewicz, A.S. Rahman, T.J. Adam, S.V. Pakhom and G.B. Melton, 2012. A qualitative analysis of EHR clinical document synthesis by clinicians. Proceeding of the AMIA Annual Symposium, pp: 1211-1220.
   PMid:23304398 PMCid:PMC3540510    
5. Hirsch, M.D., 2012. Lack of Standardized HER Interface Delaying Interoperability.
   Direct Link
6. HSCIC (Health and Social Care Information Center), 2012. Quality of Dataset Report in Various Groups.
   Direct Link
7. Huser, V., S.P. Narus and R.A. Rocha, 2010. Evaluation of a flowchart-based EHR query system: A case study of RetroGuide. J. Biomed. Inform., 43: 41-50.
   CrossRef    PMid:19560553 PMCid:PMC2840619    
8. Jiaxin, W., 2010. WIVF: Web information visualization framework based on information architecture 2.0. Proceeding of the 2nd International Conference in Computer and Automation Engineering (ICCAE), pp: 734-738.
   CrossRef    
9. Krist, W., M. Monroe, C. Plaisant, B. Shneiderman, J. Millstein and S. Gold, 2012. Exploring point and interval event patterns: Display methods and interactive visual query.
   Direct Link
10. Kwon, B.C., B. Fisher and J.S. Yi, 2011. Visual analytic roadblocks for novice investigators. Proceeding of the IEEE Conference in Visual Analytics Science and Technology (VAST). RI, USA, pp: 3-11.
    CrossRef    
11. Maldonado, J.A., C.M. Costa, D. Moner, M.M. Tortosa, D. Bosca, J.A.M. Gimenez, J.T.F. Breis and M. Robles, 2012. Using the research EHR platform to facilitate the practical application of the EHR standards. J. Biomed. Inform., 45: 746-762.
    CrossRef    PMid:22142945    
12. Malik, M.S.A. and S. Sulaiman, 2012. An integrated modular approach for visual analytic systems in electronic health records. Int. J. Adv. Comput. Sci. Appl., 3: 246-250.
    
13. Malik, M.S.A. and S. Sulaiman, 2013a. Towards the development of an interface model for information visualization in multiple electronic health records. Proceeding of the IEEE International Conference on Computer Medical Applications (ICCMA), IEEE, pp: 1-5.
    
14. Malik, M. and S. Sulaiman, 2013b. Analytical Comparison of Factors Affecting EHR Visualization for Physicians in Public Health Care Units. In: Zaman, H., P. Robinson, P. Olivier, T. Shih and S. Velastin (Eds.), Advances in Visual Informatics. Springer International Publishing, Switzerland, 8237: 605-614.
    CrossRef    
15. Mane, K.K., C. Bizon, C. Schmitt, P. Owen, B. Burchett, R. Pietrobon and K. Gersing, 2012. Visual decision linc: A visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry. J. Biomed. Inform., 45: 101-106.
    CrossRef    PMid:21963813    
16. McGuinness, D.L., T. Lebo, A.R. Shaikh, R.P. Moser, L. Ding, J.P. McCusker, G.D. Morgan, Z. Tatalovich, G. Willis, B.W. Hesse, N. Contractor and P. Courtney. 2012. Towards semantically enabled next generation community health information portals: The PopSciGrid pilot. Proceeding of the 45th Hawaii International Conference in System Science (HICSS), pp: 2752-2760.
    CrossRef    
17. Nair, V., M. Kaduskar, P. Bhaskaran, S. Bhaumik and L. Hodong, 2011. Preserving narratives in electronic health records. Proceeding of the IEEE International Conference in Bioinformatics and Biomedicine (BIBM), pp: 418-421.
    CrossRef    
18. Schaefbauer, C.L. and K.A. Siek, 2011. Cautious, but optimistic: An ethnographic study on location and content of primary care providers using electronic medical records. Proceeding of the 5th International Conference in Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp: 63-70.
    CrossRef    
19. UK NHS (UK National Health Service), 2013. NHS Datamodeland Dictionary Service.
    Direct Link
20. Viitanen, J., H. Hypponen, T. Laaveri, J. Vanska, J. Reponen and I. Winblad, 2011. National questionnaire study on clinical ICT systems proofs: Physicians suffer from poor usability. Int. J. Med. Inform., 80: 708-725.
    CrossRef    PMid:21784701    
21. Wang, H.Q., J.S. Li, Y.F. Zhang, M. Suzuki and K. Araki, 2013. Creating personalised clinical pathways by semantic interoperability with electronic health records. J. Artif. Intell. Med., 58(2): 81-89.
    CrossRef    PMid:23466439    
22. Wang, T.D., K. Wongsuphasawat, C. Plaisant and B. Shneiderman, 2011a. Extracting insights from electronic health records: Case studies, a visual analytics process model and design recommendations. J. Med. Syst., 35(5): 1135-1152.
    CrossRef    PMid:21541691    
23. Wang, X., D. Wenwen, T. Butkiewicz, E.A. Bier and W. Ribarsky, 2011b. A two-stage framework for designing visual analytics system in organizational environments. Proceeding of the IEEE Conference on Visual Analytics and Technology (VAST). Providence, RI, pp: 251-260.
    CrossRef    
24. Ware, C., 2013. Information Visualization Perception for Design. 3rd Edn., Morgan Kaufmann Publishers, USA.
    
25. Wilcox, L., D. Morris, D. Tan and J. Gatewood, 2010b. Designing patient-centric information displays for hospitals. Proceedings of the 28th International Conference on Human Factors in Computing Systems. Atlanta, Georgia, USA.
    CrossRef    
26. Wilcox, L., J. Lu, J. Lai, S. Feiner and D. Jordan, 2010a. Physician-driven management of patient progress notes in an intensive care unit. Proceedings of the 28th International Conference on Human Factors in Computing Systems. Atlanta, Georgia, USA.
    CrossRef    
27. Wongsuphasawat, K. and B. Shneiderman, 2009. Finding comparable temporal categorical records: A similarity measure with an interactive visualization. Proceeding of the IEEE Symposium on Visual Analytics Science and Technology (VAST), pp: 27-34.
    CrossRef    
28. Zhang, J. and M.F. Waliji, 2011. TURF: Towar a unified framework of EHR usability. J. Biomed. Inform., 44(6): 1056-1067.
    CrossRef    PMid:21867774    
29. Zhang, R., S. Pakhomov and G.B. Melton, 2012. Automated identification of relevant new information in clinical narrative. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. Miami, Florida, USA.
    CrossRef    
30. Zhang, Z., B. Wang, F. Ahmed, I.V. Ramakrishnan, R. Zhao, A. Viccellio and K. Mueller, 2013. The five Ws for information visualization with application to healthcare informatics. IEEE T. Vis. Comput. Gr., 19(11): 1895-1910.
    CrossRef    PMid:24029909    

Competing interests

The authors have no competing interests.

Open Access Policy

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.

Copyright

The authors have no competing interests.