Facilitating the Iterative Design of Informatics Tools to Advance the Science of Autism
Clinical research informatics (CRI) is a burgeoning discipline whose efforts are focused at the intersection of clinical research and biomedical informatics. CRI affords new opportunities to make tangible progress on longstanding, seemingly intractable clinical problems by leveraging new technologies for exploring very large data sets for prediction, visualization, and hypothesis generation. Autism spectrum disorder (ASD) is a heterogeneous syndrome characterized by a multitude of behavioral, social and communication problems. This paper describes two usability evaluation studies of first generation systems designed to retrieve phenotypic data from the large SFARI data set of 2000 families each of which has one child affected with ASD. The usability methods included a cognitive walkthrough and usability testing. In testing the first system, Data Dig, the subjects were able to learn to use the system without too much difficulty. However, we observed more than 50 usability problems of varying severity. The problems with the greatest frequency resulted from users being unable to understand variable meanings, filter categories correctly, use the Boolean filter, and correctly interpret the feedback provided by the system. Subjects had difficulty forming a mental model of the organizational system underlying the database. This precluded them from making informed navigation choices while formulating queries. The second system, Family Selector, was designed with many of the lessons learned from the usability evaluation. We also closely coordinated with the development team from Prometheus Research and conducted a user-center design study in an effort to further contribute to iterative design process. Clinical research informatics is a new and immensely promising discipline. However in its nascent stage, it lacks a stable interaction paradigm to support a range of users on pertinent tasks. This presents great opportunity for human-computer interaction researchers to further this science by harnessing the powers of user-centered iterative design.
Dave Kaufman is a Visiting Scholar at the New York Academy of Medicine. He has engaged in cognitive research in relation to informatics initiatives and evaluating a wide range of health information technologies developed for clinicians, patients, health consumers and most recently, biomedical scientists. Dr. Kaufman published several papers related to applying video-analytic cognitive science methods to the study of the productive use of health information technologies and devices. Since 1994, he has been involved in several human computer interaction projects pertaining to the cognitive evaluation of electronic health records, computer-provider order entry systems, mobile medical devices, database tools for biomedical scientists, language learning systems for medical professionals and a telemedicine system for patients with diabetes. Dr. Kaufman’s primary research interest these days is on clinical communication in critical care medicine and eHealth literacy. Prior to working at NYAM, he was an Associate Research Scientist at the Department of Biomedical Informatics at Columbia University. Dr. Kaufman was also a Lecturer at UC Berkeley in the Department of Cognition and Development in the Graduate School of Education. He received a PhD in Education Psychology from McGill University with a focus on applied cognitive science in healthcare.