Insights from the Front Lines of Medical Documentation

We explore the root causes of information chaos, designing for clarity, and the thoughtful application of AI in medicine.

Beyond Notes: Why It Is Time to Abandon an Outdated Documentation Paradigm
Research, Our Approach Jackson Steinkamp Research, Our Approach Jackson Steinkamp

Beyond Notes: Why It Is Time to Abandon an Outdated Documentation Paradigm

The medical chart—including notes, labs, and imaging results—should be reconceptualized as a dynamic, fully collaborative workspace organized by topic rather than time, writer, or data type. This will lead to better clinical outcomes and higher job satisfaction among clinicians, who will suffer less with decreased cognitive burden.

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A Web Application for Adrenal Incidentaloma Identification, Tracking, and Management Using Machine Learning
AI in Clinical Practice, Research Jackson Steinkamp AI in Clinical Practice, Research Jackson Steinkamp

A Web Application for Adrenal Incidentaloma Identification, Tracking, and Management Using Machine Learning

Incidental findings are a common medical problem that are prone to falling through the cracks of the medical system. Building safety net systems to identify, track, and to help manage these potentially dangerous findings can decrease the cognitive burden on physicians and lead to better outcomes for patients. In this manuscript, we present a software system designed to identify adrenal incidentalomas and track them over time.

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