Appl Clin Inform 2019; 10(04): 610-614
DOI: 10.1055/s-0039-1694748
Letter to the Editor
Georg Thieme Verlag KG Stuttgart · New York

Using Cognitive Load Theory to Improve Posthospitalization Follow-Up Visits

Elizabeth M. Harry
1   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States
2   Harvard Medical School, Harvard University, Boston, Massachusetts, United States
,
Grace H. Shin
1   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States
,
Bridget A. Neville
1   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States
,
Stuart R. Lipsitz
1   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States
,
Gennady M. Gorbovitsky
3   Partners Healthcare Information Systems, Boston, Massachusetts, United States
,
David W. Bates
1   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States
2   Harvard Medical School, Harvard University, Boston, Massachusetts, United States
,
Jeffrey L. Schnipper
1   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, United States
2   Harvard Medical School, Harvard University, Boston, Massachusetts, United States
› Author Affiliations
Further Information

Publication History

04 April 2019

30 June 2019

Publication Date:
21 August 2019 (online)

Background and Significance

Cognitive load theory states humans have limited capacity for information processing via working memory.[1] [2] As health care complexity increases, processing each patient medical record is now a considerable challenge. Working memory can be overwhelmed and information can be lost, impacting patient safety. Wasting working memory on inefficient information presentation carries high risk. Providers experiencing high cognitive load are hypothesized to provide poorer care for patients and be at higher risk of providing care influenced by stereotypes and bias.[3] The period after hospital discharge is a particularly high-risk period for patients, and studies have shown deficiencies in documentation of hospitalizations, thus adding to the challenges of providers caring for these patients.[4] [5] Electronic health record (EHR) interfaces designed based on information needs of intensive care physicians demonstrated decreased task load, time to completion, and cognitive errors.[6] Strengthening this end user-based design by applying the science of cognitive load theory may further improve providers' ability to process information, reducing potential errors and fatigue.[6] [7] [8] [9]

Protection of Human and Animal Subjects

All human subject involvement of this study was approved by the local IRB.


 
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