Clinical guidelines are evidence‐based clinician decision‐support tools that improve health outcomes, reduce patient harm, and decrease healthcare costs, but are often underused in emergency departments (EDs). This article describes a replicable, evidence‐based design‐thinking approach to developing best practices for guideline design that improves clinical satisfaction and usage. We used a 5‐step process to enhance guideline usability in our ED. First, we conducted end‐user interviews to identify barriers to guideline usage. Second, we reviewed the literature to identify key principles in guideline design. Third, we applied our findings to create a standardized guideline format, incorporating rapid cycle learning and iterative improvements. Fourth, we ensured the clinical validity of our updated guidelines by using a rigorous process for peer review. Lastly, we evaluated the impact of our guideline conversion process by tracking clinical guidelines access per day from October 2020 to January 2022. Our end‐user interviews and review of the design literature revealed several barriers to guideline use, including lack of readability, design inconsistencies, and guideline complexity. Although our previous clinical guideline system averaged 0.13 users per day, >43 users per day accessed the clinical guidelines on our new digital platform in January 2022, representing an increase in access and use exceeding 33,000%. Our replicable process using open‐access resources increased clinician access to and satisfaction with clinical guidelines in our ED. Design‐thinking and use of low‐cost technology can significantly improve clinical guideline visibility and has the potential to increase guideline use.

Introduction: Many patients have unaddressed social needs that significantly impact their health, yet navigating the landscape of available resources and eligibility requirements is complex for both patients and clinicians. Methods: Using an iterative design-thinking approach, our multidisciplinary team built, tested, and deployed a digital decision tool called “Discharge Navigator” (edrive.ucsf.edu/dcnav) that helps emergency clinicians identify targeted social resources for patients upon discharge from the acute care setting. The tool uses each patient’s clinical and demographic information to tailor recommended community resources, providing the clinician with action items, pandemic restrictions, and patient handouts for relevant resources in five languages. We implemented two modules at our urban, academic, Level I trauma center. Results: Over the 10-week period following product launch, between 4-81 on-shift emergency clinicians used our tool each week. Anonymously surveyed clinicians (n = 53) reported a significant increase in awareness of homelessness resources (33% pre to 70% post, P<0.0001) and substance use resources (17% to 65%, P<0.0001); confidence in accessing resources (22% to 74%, P<0.0001); knowledge of eligibility criteria (13% to 75%, P<0.0001); and ability to refer patients always or most of the time (11% to 43%, P<0.0001). The average likelihood to recommend the tool was 7.8 of 10. Conclusion: Our design process and low-cost tool may be replicated at other institutions to improve knowledge and referrals to local community resources.

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