JMIR Publications

ABSTRACT

Background:

Despite an ever-expanding number of analytics with the potential to impact clinical care, the field currently lacks point-of-care technological tools that allow clinicians to efficiently select disease-relevant data about their patient, algorithmically derive clinical indices (e.g. risk scores), and view them in straightforward graphical formats to inform real-time clinical decisions. Thus far, solutions to this problem have relied on either bottom-up approaches limited to a single clinic, or generic top-down approaches that do not address clinical users’ specific, setting- or disease-relevant needs.

Objective:

As a roadmap to develop similar platforms, we describe our experience with building a custom but institution-wide platform that enables economies of time, cost, and expertise.

Methods:

The BRIDGE platform was designed to be modular, scalable, and customized to data types relevant to given clinical contexts within a major university medical center. The development process occurred using a series of human-centered design phases with extensive, consistent stakeholder input.

Results:

This institution-wide approach yielded a unified, carefully regulated cross-specialty clinical research platform that launches from a patient’s Electronic Health Record (EHR) encounter. It pulls clinical data from the EHR (Epic) as well as other clinical and research sources in real time, analyzes the combined data to derive clinical indices, and displays them in simple clinician-designed visual formats targeted to each disorder and clinic.

Conclusions:

By integrating an application into the clinical workflow and allowing clinicians to access data sources that would otherwise be cumbersome to assemble, view and manipulate, institution-wide platforms represent an alternative approach to achieving the vision of true personalized medicine. Clinical Trial: N/A