As the use of electronic health records (EHRs) spreads, large databases of EHR data are becoming available but are underused because there is no easy-to-use interfaces to understand what is available, specific complex temporal queries, review the results, compare groups of patients and rapidly and easily iterate this process. Visual and interactive solutions can dramatically increase the benefits of EHR databases, leading to improved clinical research and patient care. Research activities often require comparing treatments, drugs, patients with or without certain genes, etc. To assembling the groups of patients to be studied require queries that have a temporal component, e.g. """"""""Find patients whose onset of asthma followed within 3 months of treatment of pneumonia"""""""". Currently available systems make possible simple queries such as """"""""Find patients who have the diagnoses of asthma and pneumonia"""""""" leaving users with the burden of shuffling through large numbers of results in search for the useful data. Specifying useful but more complex temporal queries with SQL or other languages is impossible for most medical researchers, and data mining results are found questionable and hard to interpret as users cannot control the blind mining process and problems with """"""""dirty"""""""" data remain unseen and unaddressed. Novel interface designs are needed for 1) interactive query interfaces allowing researchers and clinicians to find data that show temporal patterns of interest in both numerical and categorical data 2) event history operators to align, rank, filter and group by the results visually, allowing researchers and clinicians to see patterns, exceptions, and possibly data quality problems in the data they retrieved 3) powerful comparison tools to explore alternatives (e.g. to conduct comparative effectiveness research), and annotation mechanisms to record findings and prepare reports. We believe that the future of user interfaces is in the direction of larger, information- abundant interactive displays that are easy to use and empower the user to make discoveries while being aware of the quality of the data used in the process. By bridging the worlds of data bases, user interface design and information visualization, the next generation of potent visual analytic tools and work environments can be developed. Visual and interactive solutions for specifying search and reviewing results can dramatically increase the benefits of EHR databases, leading to improved clinical research and patient care. Novel interface designs are needed for 1) interactive query interfaces allowing researchers and clinicians to find data that show temporal patterns of interest in both numerical and categorical data 2) event history operators to align, rank, filter and group by the results allowing researchers and clinicians to see patterns and exceptions in the data they retrieved 3) novel visual summaries of temporal categorical data.
Visual and interactive solutions for specifying search and reviewing results can dramatically increase the benefits of EHR databases, leading to improved clinical research and patient care. Novel interface designs are needed for 1) interactive query interfaces allowing researchers and clinicians to find data that show temporal patterns of interest in both numerical and categorical data 2) event history operators to align, rank, filter and group by the results allowing researchers and clinicians to see patterns and exceptions in the data they retrieved 3) novel visual summaries of temporal categorical data.
| Plaisant, Catherine (2018) Visualization of temporal patterns in patient record data. Fundam Clin Pharmacol 32:85-87 |
| Wongsuphasawat, Krist; Plaisant, Catherine; Taieb-Maimon, Meirav et al. (2012) Querying Event Sequences by Exact Match or Similarity Search: Design and Empirical Evaluation. Interact Comput 24:55-68 |
| Goldberg, Larry; Lide, Bettijoyce; Lowry, Svetlana et al. (2011) Usability and accessibility in consumer health informatics current trends and future challenges. Am J Prev Med 40:S187-97 |
| Wang, Taowei David; Wongsuphasawat, Krist; Plaisant, Catherine et al. (2011) Extracting insights from electronic health records: case studies, a visual analytics process model, and design recommendations. J Med Syst 35:1135-52 |
| Wang, Taowei David; Plaisant, Catherine; Shneiderman, Ben et al. (2009) Temporal summaries: supporting temporal categorical searching, aggregation and comparison. IEEE Trans Vis Comput Graph 15:1049-56 |
