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Clinical decision making in uncertainty; an ethnography of a complex intervention in the ambulatory emergency care setting

Clinical decision making in uncertainty; an ethnography of a complex intervention in the ambulatory emergency care setting
Clinical decision making in uncertainty; an ethnography of a complex intervention in the ambulatory emergency care setting
Clinical Decision Making in Uncertainty; An Ethnography of a Complex Intervention in the Ambulatory Emergency Care setting

Objectives:

AEC (Ambulatory Emergency Care) provides acute assessment and treatment in the community for acutely unwell complex older patients, with patients staying in their own homes overnight. The investigation aimed to understand the Clinical Decision-Making of the senior clinicians in the AEC environment as an example of working in Clinical Uncertainty.

Methods:

Three AEC sites were purposively sampled to recruit twelve clinicians with backgrounds in Geriatrics, General Practice, Emergency and Acute Medicine. This qualitative investigation used focused ethnography within a case study approach to understand the decision-making processes in the context of the AEC environment. Observation during an AEC shift was complemented by informant interviews. A framework approach to thematic analysis used “a priori” and data derived codes to develop explanatory themes. Ethnographic principles of constant comparison and Cognitive Task Analysis were used to evaluate the clinicians’ decision-making processes for index patient cases.

Findings:

The work of AEC is complex negotiated distributed team-based decision-making to deliver an individually tailored care plan for patients with urgent healthcare needs suitable for out-of-hospital management. Key decision-making stages included triage, diagnostic, management and prognostic decisions. Variation in the delivery of these components was achieved through negotiation and individual tailoring. The participating AEC clinicians had a diverse background training and were boundary spanning individuals with cognitive flexibility and contextual adroitness. Clinicians mitigated the cognitive load of working in urgent care settings by altering their tasks, referral thresholds and clinical behaviours. Effective team working was enhanced by team reflexivity. Team based decision-making was required to manage the complexity and uncertainty of working in the AEC environment.

Conclusions:

This critical example of AEC decision-making demonstrates how complexity, negotiation and teamwork affect clinicians working in urgent care environments with high clinical uncertainty and cognitive load. These findings could inform the development of medical training curricula, interdisciplinary working and health service design.
University of Oxford
Mckelvie, Sara
61c92fa0-fa9f-4d59-988d-6e669d8f8f32
Mckelvie, Sara
61c92fa0-fa9f-4d59-988d-6e669d8f8f32
Lasserson, Daniel S.
32bfac0a-20cb-4047-9443-3f9b1af8dca1
Reeve, Joanne
1bfcb8aa-5549-4c5b-81de-e52e3c7376fd
Glogowska, Margaret
4f45daa1-0b95-4752-a862-7eaff0cd857c

Mckelvie, Sara (2021) Clinical decision making in uncertainty; an ethnography of a complex intervention in the ambulatory emergency care setting. University of Oxford, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

Clinical Decision Making in Uncertainty; An Ethnography of a Complex Intervention in the Ambulatory Emergency Care setting

Objectives:

AEC (Ambulatory Emergency Care) provides acute assessment and treatment in the community for acutely unwell complex older patients, with patients staying in their own homes overnight. The investigation aimed to understand the Clinical Decision-Making of the senior clinicians in the AEC environment as an example of working in Clinical Uncertainty.

Methods:

Three AEC sites were purposively sampled to recruit twelve clinicians with backgrounds in Geriatrics, General Practice, Emergency and Acute Medicine. This qualitative investigation used focused ethnography within a case study approach to understand the decision-making processes in the context of the AEC environment. Observation during an AEC shift was complemented by informant interviews. A framework approach to thematic analysis used “a priori” and data derived codes to develop explanatory themes. Ethnographic principles of constant comparison and Cognitive Task Analysis were used to evaluate the clinicians’ decision-making processes for index patient cases.

Findings:

The work of AEC is complex negotiated distributed team-based decision-making to deliver an individually tailored care plan for patients with urgent healthcare needs suitable for out-of-hospital management. Key decision-making stages included triage, diagnostic, management and prognostic decisions. Variation in the delivery of these components was achieved through negotiation and individual tailoring. The participating AEC clinicians had a diverse background training and were boundary spanning individuals with cognitive flexibility and contextual adroitness. Clinicians mitigated the cognitive load of working in urgent care settings by altering their tasks, referral thresholds and clinical behaviours. Effective team working was enhanced by team reflexivity. Team based decision-making was required to manage the complexity and uncertainty of working in the AEC environment.

Conclusions:

This critical example of AEC decision-making demonstrates how complexity, negotiation and teamwork affect clinicians working in urgent care environments with high clinical uncertainty and cognitive load. These findings could inform the development of medical training curricula, interdisciplinary working and health service design.

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More information

Published date: 2021

Identifiers

Local EPrints ID: 482279
URI: http://eprints.soton.ac.uk/id/eprint/482279
PURE UUID: 11aac9e0-5a62-40f3-8afc-59f4b7d034b9
ORCID for Sara Mckelvie: ORCID iD orcid.org/0000-0003-3781-9813

Catalogue record

Date deposited: 25 Sep 2023 16:43
Last modified: 18 Mar 2024 03:58

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Contributors

Author: Sara Mckelvie ORCID iD
Thesis advisor: Daniel S. Lasserson
Thesis advisor: Joanne Reeve
Thesis advisor: Margaret Glogowska

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