JAMIA: EHRs uniqueness decreases over average admission time
EHRs should be designed to be clinically useful, practical and efficient, according to a recent study published in the January 2010 edition of the Journal of the American Medical Informatics Association (JAMIA).

In a study of 100 randomly selected patient admissions over a six-month period, Jesse O. Wrenn of the department of biomedical informatics at Columbia University in New York City and colleagues found that signout and progress notes contained an average of 78 percent and 54 percent information duplicated from previous documents, respectively.

Additionally, the uniqueness of average progress notes decreased over the course of an admission, according to the report.

The study implemented a retrospective design to gather all electronic admission, progress, resident signout and discharge summary notes written during the study’s duration from June 2006 to December 2006. The amount of unique information in a document was calculated as the number of words that did not align with previous documents divided by the lengths, in words, of the document.

Out of the 1,167 resident signout notes, the quantity of unique information retained in an average signout note was 22 percent. Of the 303 progress notes, 46 percent on average contained unique information.

The quantity of unique information declined over an average series of signout notes during the course of an admission. The first signout note was defined as fully unique and the final signout note was 7.3 percent unique on average.

Similarly, the first progress note of each admission was defined as fully unique, and the final progress note was 27.7 percent unique on average.

While the study’s authors acknowledged limitations studying documents exclusive to WebCIS--an electronic system used at its institution--they concluded that the WebCIS notes were “free-text” so the findings may be applicable to documents created in systems with similarly unstructured notes.

Further studies on EHR redundancies are needed, according to the study. “The findings...support the feasibility of our methods for studying redundancy,” the authors wrote.