Developing an electronic clinical decision support system to promote guideline adherence for healthy weight management and cardiovascular risk reduction in children: a progress update

Naureckas, S. M.; Zweigoron, R.; Haverkamp, K. S.; Kaleba, E. O.; Pohl, S. J.; Ariza, A. J.

Transl Behav Med. 2011 Mar 1; 1(1):103-7


Overweight and obesity are common challenges facing pediatric clinicians. Electronic health records (EHRs) can impact clinician behavior through the presentation of relevant, patient-specific information during clinical encounters, potentially improving clinician recognition and management of overweight/obesity in children. Little research has been published evaluating the impact of EHR-facilitated decision support on the treatment of obesity in children. The main objectives of our community clinician-led project are: 1) to build customized, evidence-based decision support into an EHR; 2) To evaluate the impact of decision support on the identification and treatment of overweight and obese children; and 3) to improve behavior around screening for obesity-related comorbidities. Through a clinician-led consensus process, we customized end user templates in the commercially-available EHR at an urban community health center with a known high prevalence of childhood overweight and obesity. Evidence based decision support was build into the screens to prompt clinicians to identify and address overweight and obesity, as well as for related comorbidities. Pre/post measures will be used to evaluate the impact of these tactics on clinician behavior. The customized EHR templates took longer than anticipated to develop, but are now being used by pediatric clinicians at the health center. Feedback to date suggests that clinicians find the evidence based decision support useful at the point of care, especially around ordering recommended screening tests. Clinicians must be active participants in the design of decision support in order for it to impact their behavior. Off-the-shelf EHR products do not automatically come with comprehensive functionality to support evidence-based interventions around clinician behavior. Modifications are needed to achieve the full promise of health information technology as it relates to delivering high quality, patient-centered, for underserved populations.

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