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Paquay M, Kolbe M, Klenkenberg S, Buléon C, Bertrand A, Simon R, Ghuysen A. Comparative analysis of routine clinical debriefings and incident reports: insights for patient safety and teamwork enhancement. Int J Qual Health Care 2025; 37:mzaf010. [PMID: 39891891 PMCID: PMC11833459 DOI: 10.1093/intqhc/mzaf010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2024] [Revised: 01/06/2025] [Accepted: 02/01/2025] [Indexed: 02/03/2025] Open
Abstract
BACKGROUND Routine clinical debriefings (RCDs) have been shown to improve communication, team reflexivity, and safety in clinical settings. When combined with incident reports (IRs), RCDs offer a potential tool for enhancing quality improvement frameworks. This study aimed to identify and compare healthcare safety-related information captured through RCDs and IRs in a Belgian emergency department operating across two distinct facilities. METHODS This study employed a quasi-mixed-method design with a monostrand conversion approach. Information was collected from 90 RCDs and 263 IRs. Data were analyzed using two frameworks: the World Health Organization's Incident Report Classification Grid and the Debriefing and Organizational Lessons Learned Grid. RESULTS The findings revealed significant differences in the types of information captured by RCDs and IRs. RCDs predominantly highlighted teamwork, internal organization, and procedural issues, while IRs focused more on care processes, patient concerns, and patient flow. These complementary insights demonstrate the value of integrating RCDs and IRs to create a comprehensive understanding of patient and clinician safety. CONCLUSIONS This study highlights the complementary nature of RCDs and IRs in addressing healthcare safety. RCDs foster team reflexivity and promote open discussions about systemic challenges, directly improving team cohesion, resilience, and learning. Combining RCDs and IRs provides actionable insights for enhancing safety and driving organizational improvements.
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Affiliation(s)
- Méryl Paquay
- Emergency Department, University Hospital of Liege, Avenue de l'hopital, 1, Liege 4000, Belgium
- Center for Medical Simulation of Liege, Public Health Department, University of Liege, Quartier Hôpital, Av. Hippocrate 13, CHU B23, Liege 4000, Belgium
| | - Michaela Kolbe
- Simulation Center, University Hospital Zurich, Huttenstrasse 46, Zurich 8091, Switzerland
| | - Sophie Klenkenberg
- Center for Medical Simulation of Liege, Public Health Department, University of Liege, Quartier Hôpital, Av. Hippocrate 13, CHU B23, Liege 4000, Belgium
| | - Clément Buléon
- Center for Medical Simulation of Liege, Public Health Department, University of Liege, Quartier Hôpital, Av. Hippocrate 13, CHU B23, Liege 4000, Belgium
- Emergency Department, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, United States
| | - Audrey Bertrand
- Center for Medical Simulation of Liege, Public Health Department, University of Liege, Quartier Hôpital, Av. Hippocrate 13, CHU B23, Liege 4000, Belgium
| | - Robert Simon
- Emergency Department, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, United States
| | - Alexandre Ghuysen
- Emergency Department, University Hospital of Liege, Avenue de l'hopital, 1, Liege 4000, Belgium
- Center for Medical Simulation of Liege, Public Health Department, University of Liege, Quartier Hôpital, Av. Hippocrate 13, CHU B23, Liege 4000, Belgium
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Paquay M, Dubois N, Diep AN, Graas G, Sassel T, Piazza J, Servotte JC, Ghuysen A. “Debriefing and Organizational Lessons Learned” (DOLL): A Qualitative Study to Develop a Classification Framework for Reporting Clinical Debriefing Results. Front Med (Lausanne) 2022; 9:882326. [PMID: 35814768 PMCID: PMC9263566 DOI: 10.3389/fmed.2022.882326] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe COVID-19 crisis has radically affected our healthcare institutions. Debriefings in clinical settings provide a time for the clinicians to reflect on the successes (pluses) and difficulties (deltas) encountered. Debriefings tend to be well-received if included in the broader management of the unit. The goal of this study was to develop a framework to categorize these debriefings and to assess its worthiness.MethodsA qualitative approach based on a grounded theory research method was adopted resulting in the “Debriefing and Organizational Lessons Learned” (DOLL) framework. Debriefings were conducted within two Emergency Departments of a Belgian University Hospital during an 8-week period. In the first step, three researchers used debriefing transcripts to inductively develop a tentative framework. During the second step, these three researchers conducted independent categorizations of the debriefings using the developed framework. In step 3, the team analyzed the data to understand the utility of the framework. Chi-square was conducted to examine the associations between the item types (pluses and deltas) and the framework's dimensions.ResultsThe DOLL is composed of seven dimensions and 13 subdimensions. Applied to 163 debriefings, the model identified 339 items, including 97 pluses and 242 deltas. Results revealed that there was an association between the frequency of pluses and deltas and the dimensions (p < 0.001). The deltas were mainly related to the work environment (equipment and maintenance) (p < 0.001) while the pluses identified tended to be related to the organization of the unit (communication and roles) (p < 0.001). With leadership's support and subsequent actions, clinicians were more enthusiastic about participating and the researchers anecdotally detected a switch toward a more positive organizational learning approach.ConclusionThe framework increases the potential value of clinical debriefings because it organizes results into actionable areas. Indeed, leadership found the DOLL to be a useful management tool. Further research is needed to investigate how DOLL may work in non-crisis circumstances and further apply the DOLL into incident reporting and risk management process of the unit.
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Affiliation(s)
- Méryl Paquay
- Department of Emergency, Quartier Hôpital, University Hospital of Liege, Liège, Belgium
- Center for Medical Simulation of Liege, Quartier Hôpital, University of Liege, Liège, Belgium
- *Correspondence: Méryl Paquay
| | - Nadège Dubois
- Center for Medical Simulation of Liege, Quartier Hôpital, University of Liege, Liège, Belgium
| | - Anh Nguyet Diep
- Biostatistics Unit, Quartier Hôpital, University of Liège, Liège, Belgium
| | - Gwennaëlle Graas
- Center for Medical Simulation of Liege, Quartier Hôpital, University of Liege, Liège, Belgium
| | - Tamara Sassel
- Center for Medical Simulation of Liege, Quartier Hôpital, University of Liege, Liège, Belgium
| | - Justine Piazza
- Department of Emergency, Quartier Hôpital, University Hospital of Liege, Liège, Belgium
- Center for Medical Simulation of Liege, Quartier Hôpital, University of Liege, Liège, Belgium
| | | | - Alexandre Ghuysen
- Department of Emergency, Quartier Hôpital, University Hospital of Liege, Liège, Belgium
- Center for Medical Simulation of Liege, Quartier Hôpital, University of Liege, Liège, Belgium
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Hobensack M, Ojo M, Barrón Y, Bowles KH, Cato K, Chae S, Kennedy E, McDonald MV, Rossetti SC, Song J, Sridharan S, Topaz M. Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians. J Am Med Inform Assoc 2022; 29:805-812. [PMID: 35196369 PMCID: PMC9006696 DOI: 10.1093/jamia/ocac023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 02/08/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE To identify the risk factors home healthcare (HHC) clinicians associate with patient deterioration and understand how clinicians respond to and document these risk factors. METHODS We interviewed multidisciplinary HHC clinicians from January to March of 2021. Risk factors were mapped to standardized terminologies (eg, Omaha System). We used directed content analysis to identify risk factors for deterioration. We used inductive thematic analysis to understand HHC clinicians' response to risk factors and documentation of risk factors. RESULTS Fifteen HHC clinicians identified a total of 79 risk factors that were mapped to standardized terminologies. HHC clinicians most frequently responded to risk factors by communicating with the prescribing provider (86.7% of clinicians) or following up with patients and caregivers (86.7%). HHC clinicians stated that a majority of risk factors can be found in clinical notes (ie, care coordination (53.3%) or visit (46.7%)). DISCUSSION Clinicians acknowledged that social factors play a role in deterioration risk; but these factors are infrequently studied in HHC. While a majority of risk factors were represented in the Omaha System, additional terminologies are needed to comprehensively capture risk. Since most risk factors are documented in clinical notes, methods such as natural language processing are needed to extract them. CONCLUSION This study engaged clinicians to understand risk for deterioration during HHC. The results of our study support the development of an early warning system by providing a comprehensive list of risk factors grounded in clinician expertize and mapped to standardized terminologies.
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Affiliation(s)
- Mollie Hobensack
- Columbia University School of Nursing, New York City, New York, USA
| | - Marietta Ojo
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
| | - Yolanda Barrón
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
| | - Kathryn H Bowles
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
- Department of Biobehavioral Health Sciences, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
| | - Kenrick Cato
- Columbia University School of Nursing, New York City, New York, USA
- Emergency Medicine, Columbia University Irving Medical Center, New York City, New York, USA
| | - Sena Chae
- College of Nursing, University of Iowa, Iowa City, Iowa, USA
| | - Erin Kennedy
- Department of Biobehavioral Health Sciences, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
| | - Margaret V McDonald
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
| | - Sarah Collins Rossetti
- Columbia University School of Nursing, New York City, New York, USA
- Department of Biomedical Informatics, Columbia University, New York City, New York, USA
| | - Jiyoun Song
- Columbia University School of Nursing, New York City, New York, USA
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
| | - Sridevi Sridharan
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
| | - Maxim Topaz
- Columbia University School of Nursing, New York City, New York, USA
- Center for Home Care Policy & Research, Visiting Nurse Service of New York, New York City, New York, USA
- Data Science Institute, Columbia University, New York City, New York, USA
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