Background: Attention-deficit/hyperactivity disorder (ADHD) is the most common chronic childhood neurobehavioral disorder. Although portals have been developed for pediatricians to collect information from parents and teachers, we lack systems that share relevant information between families, pediatricians and teachers in order to overcome fragmented care that worsens outcomes. Our institution developed a Clinical Decision Support (CDS) system (Figures 1 & 2) to collect information from families and teachers by sending survey links by email following parental consent and presents this information to the pediatrician within the electronic health record (EHR). Information collected from parents included treatment preferences and goals and the Vanderbilt rating scales for ADHD symptoms, co-morbidities and performance (validated measures). Aims: To update this CDS to better address priorities of families and teachers including enabling information sharing of results between families, pediatricians, and teachers. Methods: We conducted a prospective technology development and implementation evaluation, engaging 8 parents, 11 pediatricians and 8 educators in the iterative process. From 9/2015 to 9/2016, we held 2 family advisor, 3 educator, 3 pediatrician and 2 joint parent-educator meetings that set priorities. We added features to support parent-directed sharing of results directly to teachers. T-tests and chi-square tests assessed the association of child symptoms, performance and co-morbidities with parents’ willingness to share. Results: The stakeholder-engaged design process prioritized the following features: (1) parents’ ability to control which survey components (goals, symptoms, performance, medication side-effects) were shared with teachers and (2) parents’ and teachers’ ability to receive information entered by each other and retain their own submitted information. These features were added in January, 2017. Supplemental questions on the ADHD parent surveys provided control of sharing and we utilized already in place software for secure emailing to control access to completed surveys. A total of 209 parents submitted survey responses within 28 days of the upgrade. Of these, 138 (66%) agreed to share information (114 (83%) sharing all information). Parents of children with greater hyperactivity (p=.03) as well as impaired performance (76% versus 46%, p < .001) were more likely to share than others. We observed a trend toward information sharing among parents of children with ADHD co-morbidities (oppositionality, anxiety, depression) (92% versus 71%, p=.2). Conclusion: A stakeholder-engaged process developed feasible and acceptable upgrades to an EHR-linked system that support parents’ information sharing with pediatricians and teachers for a common chronic condition. Results indicate that parents of children with greater symptomatology and impairments — those likely to benefit most — were most likely to share. This system provides a model for how patient-reported outcomes may be shared between families and interdisciplinary care teams.

Figure 1

Clinician's View of the ADHD Care Assistant

The Care Assistant presents the information collected from parents an teachers within the EHR. It also provides access to resources for parents and tools for clinicians.

Figure 1

Clinician's View of the ADHD Care Assistant

The Care Assistant presents the information collected from parents an teachers within the EHR. It also provides access to resources for parents and tools for clinicians.

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Figure 2

ADHD Care Assistant Backend

The ADHD Care Assistant uses REDCap to administer surveys to parents and teachers, which are displayed in the EHR. This view of the model demonstrates the relationship between the Care Assistant, REDCap events, and the underlying database structures.

Figure 2

ADHD Care Assistant Backend

The ADHD Care Assistant uses REDCap to administer surveys to parents and teachers, which are displayed in the EHR. This view of the model demonstrates the relationship between the Care Assistant, REDCap events, and the underlying database structures.

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