Previously Healthy Patients with Sepsis: Shedding Light on a Unique Cohort and Opportunities for Enhanced Care (CE Session)

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Description: 

This session is part of Sepsis Alliance Summit 2025.

Sepsis is often associated with patients who have underlying chronic illnesses, but an important and often overlooked population includes those who were previously healthy. This session will explore the distinctive characteristics, clinical trajectories, and outcomes of sepsis in patients without pre-existing comorbidities. Through a comparative lens, we will examine how their presentation, management, and prognosis differ from those with chronic health conditions. Attendees will gain a deeper understanding of the nuanced challenges in recognizing sepsis early in this population and the critical importance of timely diagnosis and intervention. The session aims to elevate clinical awareness and improve strategies for identifying and managing sepsis in patients who may otherwise appear at low risk.

Learning Objectives:

At the end of this session, the learner should be able to:

  • Compare and contrast the baseline characteristics, management, and outcomes of previously healthy patients with sepsis versus those with significant comorbidities;
  • Demonstrate enhanced awareness for sepsis diagnosis and the critical need for timely intervention even in patients who appear relatively healthy.

Target Audience: 

Nurses, advanced practice providers, physicians, emergency responders, pharmacists, medical technologists, respiratory therapists, physical/occupational therapists, infection prevention specialists, data/quality specialists, and more.

Rachel K. Hechtman, MD

Clinical Lecturer, Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine

University of Michigan

Rachel K. Hechtman, MD, is a physician-scientist in the Department of Internal Medicine, Division of Pulmonary and Critical Care at the University of Michigan. Dr. Hechtman’s work has focused on improving the care of patients with sepsis through enhanced risk stratification and early detection. She has a strong research interest in understanding how clinicians respond to clinical decision support tools involving the intersection of behavioral science, human-computer interaction, and medical decision-making. 

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