JMIR Publications

ABSTRACT

Background:

Through our work, we have demonstrated how clinical decision support (CDS) tools integrated into the electronic health record (EHR) assist providers in adopting evidence-based practices. This requires confronting technical challenges that result from relying on using the EHR as the foundation for tool development.

Objective:

The objective of our research was to build the EvidencePoint platform and implement vendor-agnostic integrated CDS solutions.

Methods:

We developed EvidencePoint, a novel, cloud-based, EHR-agnostic CDS platform and we will describe the development of EvidencePoint and the deployment of its initial CDS tools, which include EHR-integrated applications for clinical use cases of COVID-19 patient hospitalization survival prediction, venous thromboembolism prophylaxis, and pulmonary embolism diagnosis.

Results:

Development of the EvidencePoint platform and vendor-agnostic CDS tools utilized a human-centered design approach, including formalized stakeholder interviews and focus groups, real-world workflow analysis, rapid prototyping, iterative usability testing, and trigger tuning based on utilization data. Behavioral economics principles were adopted during the design phase

Conclusions:

The EvidencePoint system successfully demonstrated that a flexible, user-friendly platform for hosting CDS tools outside of a specific EHR is feasible. The forthcoming results of our usage and outcomes analyses will demonstrate the adoption rate of EvidencePoint tools, as well as the impact of behavioral economics “nudges” on adoption rate. Due to the EHR-agnostic nature of EvidencePoint, the development process for additional forms of CDS will be simpler than traditional and cumbersome information technology integration approaches and will benefit from the capabilities provided by the core system of EvidencePoint.