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Date

May 28, 2021

Attendees

Andrea Toogood
Anne Johnson
Anthony Oliver
Anthony Seabrook
Atchut Kanthamani
Autumn Tarter
barbara.pecoraro@cms.hhs.gov
Belinda Rogers
brian
Brianna Smith
cathy wray
Danny Belmont
Darlene Shoemaker
Deb Campbell
Dorothy
Edward O'Connor
Eileen Ford
Elisabeth Wiethorn
Eric
fzyk2737
Gail Gresko
Gina Anderson
Heather Walters
Holly Roderick
Janie Gittleman
Jen Hurley
Jennifer Harris
Jennifer Suddeth
Jessica Toth
JHUTMAN
Kathleen Todd
kedson
Keisha Potter
Kelly Long
Kisha Coa
Kristen Ives
Laura Maka
Lee.Ashlin
Linda Hightower
Marvin Arjona
matthew noftsger
Mikayla Murphy
Mike Lin
naipok
pmiddaugh
Richard Gibney
Roberta Howard
Sarah.J.Sherbrook
Shane Perry
Sharon
shauna.brown
Syd Rahman
taffy.clark
Tammy Geltmaker
thad person
Thomas Workman (he/his)
Ti-Kuang Lee
tlabriado
William Frank

Topic

Leveraging Human-Centered Techniques in Root Cause Analysis: Tracing Cause Without Blame

Leveraging Human-Centered Techniques for Root Cause Analysis

Program

Many organizations—including government, business, and healthcare—use root cause analysis to identify the fundamental reasons for an incident or failure so that they can improve future outcomes. Within product management and development, root cause analysis can lead to the source of an issue, allowing teams to enact corrective measures. Root cause analysis often stops short at what and who instead of the systemic why, which can lead to a culture of blame without lasting improvement.

What if tools from human-centered design, engineering, and psychology can lead to an improved understanding of why incidents occur and identify optimal solutions?

Our guest presenters from ManTech’s Health Division — Edward O’Connor, Director, Architecture and Janie Gittleman, Ph.D., Executive Director, Global Health Innovation — shared real-life stories, reviewed outcomes from the analysis process, and discussed how human-centered techniques can lead to better results. The presentation included different root cause analysis techniques and additional concepts from cognitive science, epidemiology, and machine learning.

Resources

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