(Taken from application abstract): We propose to conduct research on appropriate architectures for systems of patient identification, to develop a toolkit of techniques and implementations that will allow, us to build a handful of demonstrable and testable such systems, to develop and study methods for de-identifying patient data without destroying its utility for research, and to evaluate our results against existing and proposed desired data for the usability, and protection of health data. The results of the proposed work will be useful to policy makers and information system architects to inform them of the range of possible solutions to the tasks of patient identification and de-identification. It will also provide a reference set of tools for implementors who are developing health information systems. The proposed research and evaluation plan is summarized in the following specific aims. 1. Develop the Health Information Identification and De-Identification Toolkit (HIIDIT), a toolkit that provides a range of solutions for patient identification and de-identification to meet various national and patient objectives in healthcare access, delivery, and research. 2. Apply HIIDIT to two different tasks: retrieving individual patient data for clinical care within a multi-institutional healthcare system and retrieving aggregate data for multi-institutional clinical research trial. 3. Evaluate the application of HIIDIT in terms of protection of confidentiality within the context of national healthcare delivery and research. 4. Develop new methods to de-identify data in databases that include both coded fields and narrative text, and develop formal criteria for evaluating success of de-identification methods. The HIIDIT proposal is narrowly defined to include only issues of identification and de-identification. It does not encompass the much larger agenda of creating a Master Patient Index (MPI).
