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Abstrakt

How Well Does Patient Self-Reported Weight Agree with Values in the Electronic Medical Record?

Eugene Oddone, Maren Olsen, Linda Sandersa, Felicia McCant, MSSW, Sophia Hurley, Michael G Goldstein, Susan Raffa and Jane Kim

Objective: Accurate assessment of body weight is an important component of populational studies, interventional trials, and program evaluation. Increasingly electronic medical records (EMR) are being standardized making them potentially useful for future populational studies. However, it is unclear to what degree measures such as weight in these records agree with other assessments of weight like self-report.

Methods: We assessed agreement between EMR and patient self-reported weights from participants in a telephone lifestyle coaching program for U.S. veterans. We compared agreement at a baseline survey conducted at enrollment in the program and again at six-months after completion of the program.

Results: Five-thousand veterans participated in the coaching intervention and had both EMR and self-reported weight values at enrollment. Their mean age was 56 years and 83% were male. Reliability between EMR and selfreport weights was excellent (ICC=0.99). Agreement, assessed with Bland Altman plots, was also excellent. At baseline, self-reported values were an average of 1.0 pound lower compared to EMR values. At the six-month program completion survey reliability remained high (ICC=0.98); however, there was a 4.6 pound average lower selfreported weight compared to EMR values. Under-reported weight values were even larger for veterans who reported losing at least 5% of their baseline body weight by the end of the program; self-reported values for these veterans were 9.4 pounds lower than EMR values.

Conclusions: We believe that EMR weight values are both reliable and show low bias when compared to selfreport making them useful for both population and other studies where weight is of importance; however, selfreported values are not as reliable as EMR values for veterans who report losing weight.

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert.