Improving Gestational Weight Gain Counseling Through Meaningful Use of an Electronic Medical Record
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The purpose of this study was to test the effectiveness of an intervention to improve the consistency and accuracy of antenatal gestational weight gain counseling through introduction of a “best practice alert” into an electronic medical record (EMR) system. A best practice alert was designed and implemented in the EMR. Based on each patient’s pre-gravid body mass index (BMI), fetal number, and 2009 Institute of Medicine (IOM) guidelines, the alert provides an individualized total gestational weight gain goal, the weight gain goal per week of gestation, a template for scripted provider counseling and documentation, and a patient handout containing personalized gestational weight gain information. Retrospective chart reviews of 388 pre-intervention patients and 345 post-intervention patients were used to evaluate effectiveness. Introduction of a gestational weight gain best practice alert into the EMR improved the rate of antenatal gestational weight gain counseling that was consistent with current IOM guidelines (p < 0.001). Improvement in IOM-consistent gestational weight gain counseling was seen across all provider types, including obstetricians, family practice physicians, and certified nurse midwives. The intervention also resulted in significant improvement in documentation of pre-gravid weights and BMIs within the EMR. The EMR is an effective tool for improving the consistency and accuracy of antenatal gestational weight gain counseling in accord with 2009 IOM guidelines.
KeywordsPregnancy Obesity Gestational weight gain Prenatal counseling
This work was funded by the UW Health Ambulatory Care Innovation Grant Program, which is supported by the University of Wisconsin Medical Foundation and Physicians Plus Insurance Corporation. The work also was supported, in part, by grants T32HD049302 and K12HD055894 from the Eunice Kennedy Schriver National Institute of Child Health And Human Development and by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR000427. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations.
Conflict of interest
The authors have nothing to disclose.
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