Human Centered Design of Clinical Decision Support to Prevent Sudden Unexpected Infant Death

From the 2022 HVPA National Conference

Steven Miller MBE, MD (Johns Hopkins School of Medicine, Department of Pediatrics, Division of Pediatric Gastroenterology, Hepatology, and Nutrition), Andrea Rosen MPH (Johns Hopkins Bloomberg School of Public Health), Barry Solomon MD, Eileen M. McDonald MS, Wendy Shields PHD, MPH, Elise Omaki MHS, Bilal Asim MBA, MPH, Niru Muralidharan MS

Background

Approximately 3,500 babies die in the U.S. each year from sudden unexpected infant death (SUID) because of how or where they are placed to sleep by their caretakers. In Baltimore City, African American infants represent a disproportionately high number of SUID deaths. Previous research conducted by our team identified that pediatric residents did not comprehensively assess or counsel parents about unsafe sleep practices. Additional strategies are needed to change provider behaviors. Health information technology (IT) has the potential to help reduce SUID risk by automating identification of sleep risks and guide counseling by pediatricians in the form of a clinical decision support (CDS) tool.

Objective

The study employs human centered design (HCD) methods to carry out the formative development of a CDS called the Infant Sleep Assessment (ISA), a tool that assesses parents’ infant sleep practices, shares results with the pediatrician, and offers motivational interviewing (MI) prompts to guide safe sleep counseling. HCD methods will allow for the creation of a successful workflow-integrated CDS tool through iterative rounds of testing and redesign.

Methods

This is a single institution study involving pediatric residents in Baltimore, MD who use Epic. Observations of baseline clinical workflows and semi-structured interviews of residents were conducted to identify opportunities for CDS integration. Formative usability testing of ISA prototypes was carried out using a “Think Aloud” protocol and survey tools including the System Usability Scale (SUS) and NASA Task Load Index (NASA-TLX).

Results

Twelve residents participated in the design and testing of the ISA. Direct observations revealed that all residents use pre-charted clinical notes to plan preventive counseling, while most (70%) used Epic embedded pediatric tools, and none used best practice alerts. Testing revealed the need for automated reminders to refresh the note to populate content, clinician preference for simplicity in data presentation, appreciation for integration of the tool into clinic notes, desire for flexibility in where to access CDS recommendations, and suggestions for optimizing visual presentation of ISA results. NASA-TLX scores revealed high temporal demand in early build and SUS scores of 76.

Conclusions

HCD methods contributed to the creation of a usable, useful, integrated CDS tool through iterative rounds of testing and redesign. Direct observation of care informed the integration of the ISA tool into clinical practice by incorporating ISA counseling recommendations into the clinic note, the main site of preventive counseling planning. Usability testing allowed for refinement of prototypes to optimize usefulness and efficiency.

Clinical Implications

Health IT CDS tools have the potential to scale the distribution of best practices in preventive counseling in high-risk communities, but integration into the clinical workflow is critical. This study revealed that pediatricians wanted safe sleep CDS to be integrated into their clinic notes, though prized flexibility in where to access results and counseling prompts, and further testing is needed to determine how to best implement CDS locally.

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