The recent improvements in capabilities of desktop computers and communications networks give impetus for the development of clinical image repositories that can be used for patient care and medical education. A challenge in the use of these systems is the accurate indexing of images for retrieval performance acceptable to users. This paper describes a series of experiments aiming to adapt the SAPHIRE system, which matches text to concepts in the UMLS Metathesaurus, for the automated indexing of image reports. A series of enhancements to the baseline system resulted in a recall of 63% but a precision of only 30% in detecting concepts. At this level of performance, such a system might be problematic for users in a purely automated indexing environment. However, if the ability to retrieve images in repositories based on content in their reports is desired by clinical users, and no other current systems offer this functionality, then follow-up research questions include whether these imperfect results would be useful in a completely or partially automated indexing environment and/or whether other approaches can improve upon them.

We would like to thank all of our participants for their involvement and allowing us in their homes. We would also like to thank Patricia Flatley Brennan, PhD, RN for her input during the data analysis phase of this study. Finally, we would like to thank vizHOME for the data used in this secondary analysis. This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework.

No abstract