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First published January 31, 2005 as JAMIA PrePrint; doi:10.1197/jamia.M1689
Journal of the American Medical Informatics Association 2005;12(3):357-363
© 2005 American Medical Informatics Association

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Submitted on September 3, 2004
Accepted on November 25, 2004

Development of an Information Model for Storing Organ Donor Data within an Electronic Medical Record

Catherine J. Staes1*, Stanley M. Huff MD1, R. Scott Evans MS, PhD2, Scott P. Narus3, Cyndalynn Tilley4, and John B. Sorensen5

Affiliation of the authors: 1 Department of Medical Informatics, University of Utah, Salt Lake City, UT; Department of Medical Informatics, Intermountain Health Care, Salt Lake City, UT; 2 same plues Department of Medical Informatics, LDS Hospital, Salt Lake City, UT; 3 Department of Medical Informatics, University of Utah, Salt Lake City, UT; Department of Medical Informatics, Intermountain Health Care, Salt Lake City, UT; Department of Medical Informatics, LDS Hospital, Salt Lake City, UT; 4 Department of Medical Informatics, Intermountain Health Care, Salt Lake City, UT; 5 Department of Surgery, LDS Hospital, Salt Lake City, UT

* To whom correspondence should be addressed.

Objective To develop a model to store information in an electronic medical record (EMR) for the management of transplant patients. The model for storing donor information must be designed to allow clinicians to access donor information from the transplant patient's record, and to allow donor data to be stored without needlessly proliferating new Logical Observation Identifier Names and Codes (LOINC) codes for already-coded laboratory tests.

Design Information required to manage transplant patients requires the use of a donor's medical information while caring for the transplant patient. Three strategies were considered: 1) link the transplant patient's EMR to the donor's EMR; 2) use pre-coordinated observation identifiers (i.e., LOINC codes with *^DONOR specified in the system axes) to identify donor data stored in the transplant patient's EMR; and 3) use an information model that allows donor information to be stored in the transplant patient's record by allowing the `source' of the data (donor) and the `name' of the result (e.g., blood type) to be post-coordinated in the transplant patient's EMR.

Results We selected the third strategy and implemented a flexible post-coordinated information model. There was no need to create new LOINC codes for already-coded laboratory tests. The model required that the data structure in the EMR allow for the storage of the `subject' of the test.

Conclusion The selected strategy met our design requirements and provided an extendable information model to store donor data. This model can be used whenever it is necessary to refer to one patient’s data from another patient’s EMR.




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