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Leveraging diagnostic timeouts to foster interprofessional communication

  • James Bowen ORCID logo EMAIL logo , Brenda Demeritt , Anna J. Ipsaro , Amanda Combs , DeAnna Hawkins , Michaela Hoiles , Angela M. Statile and Michelle Parker
Published/Copyright: July 8, 2025
Diagnosis
From the journal Diagnosis

Abstract

Objectives

Diagnostic errors are a significant source of patient harm, often arising from cognitive biases and communication breakdowns. Diagnostic timeouts (DTOs) offer a structured opportunity to reassess diagnoses, but their implementation is inconsistent. This study aimed to evaluate a nurse-driven DTO framework designed to enhance interprofessional communication and diagnostic accuracy in a pediatric hospital setting.

Methods

A multidisciplinary committee developed and piloted a DTO framework on a 48-bed pediatric acute care unit. Bedside nurses received structured education on DTOs, and standardized prompts were integrated into nursing workflows to identify patients who may benefit from a DTO. Feasibility and acceptability were assessed through voluntary surveys, post-DTO documentation, and qualitative feedback.

Results

Among 90 surveyed nurses, 28 % reported that a DTO would have been beneficial for at least one patient in the eight weeks prior to the intervention period. Over six months, 13 nurse-initiated DTOs occurred, with nearly half (46 %) prompting additional workup. Two DTOs led to escalation of care. Qualitative feedback highlighted improved communication, increased psychological safety, and enhanced teamwork.

Conclusions

Pilot implementation of a formalized nurse-driven DTO framework was well-received, reinforcing its role in structured diagnostic reassessment. Future efforts will expand DTO implementation and evaluate its impact on psychological safety.


Corresponding author: James Bowen, MD, Clinical Fellow, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Avenue, MLC 9016, Cincinnati, OH 45229, USA, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Author James Bowen was primarily responsible for drafting the work, and all authors made substantial contributions in revising it critically.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: This work was not funded.

  7. Data availability: The data that support the findings of this study are available from the corresponding author, JB, upon reasonable request. The data (including patient-related data) is not shared publicly due to privacy restrictions.

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Received: 2025-03-14
Accepted: 2025-06-13
Published Online: 2025-07-08

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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