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Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care

BACKGROUND: Successful application of Quality Improvement (QI) methods is challenging, and awareness of the role context plays has increased. Complexity science has been advocated as a way to inform change efforts. However, empirical support is scarce, and it is still difficult to grasp the practica...

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Autores principales: Storkholm, Marie Höjriis, Mazzocato, Pamela, Savage, Carl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6857274/
https://www.ncbi.nlm.nih.gov/pubmed/31727069
http://dx.doi.org/10.1186/s12913-019-4705-x
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author Storkholm, Marie Höjriis
Mazzocato, Pamela
Savage, Carl
author_facet Storkholm, Marie Höjriis
Mazzocato, Pamela
Savage, Carl
author_sort Storkholm, Marie Höjriis
collection PubMed
description BACKGROUND: Successful application of Quality Improvement (QI) methods is challenging, and awareness of the role context plays has increased. Complexity science has been advocated as a way to inform change efforts. However, empirical support is scarce, and it is still difficult to grasp the practical implications for QI interventions. The aim of this study was to use a complexity-based leadership framework to explain how managers in a clinical department addressed external requirements to cut costs without compromising patient outcomes and experience. METHODS: Explanatory case study design of a Danish OB/GYN department tasked to improve efficiency. Data came from documents, 30 interviews, and 250 h of observations over 3 years. A Complexity Analysis Framework that combined two complexity-based leadership frameworks was developed to analyze all changes implemented to reduce cost, while maintaining clinical quality. RESULTS: Managers reframed the efficiency requirement as an opportunity for quality improvement. Multiple simple, complicated, and complex situations were addressed with an adaptive approach to quality improvement. Changes were made to clinical pathways for individual conditions (n = 37), multiple conditions (n = 7), and at the organizational level (n = 9). At the organizational level, changes addressed referral practice, physical space in the department, flow and capacity, discharge speed, and managerial support. Managers shared responsibility with staff; together they took a “professional path” and systematically analyzed each clinical pathway through process mapping, attentive to patterns that emerged, before deciding on the next steps, such as a engaging in a complex process of probing – the iterative development and testing of new responses. CONCLUSIONS: Quality improvement efforts could benefit from an understanding of the importance of learning and sharing responsibility to deal with the co-existing degrees of contextual complexity in modern health care. By “making things complicated” through a systematic analysis that engages staff in an open and reflective dialog, clinical praxis and established organizational structures can be questioned and improved. The Complexity Analysis Framework could then help managers to identify improvement opportunities, know when to implement technical solutions, and when to keep abreast of emerging patterns and allow appropriate responses to complex challenges to evolve.
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spelling pubmed-68572742019-12-05 Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care Storkholm, Marie Höjriis Mazzocato, Pamela Savage, Carl BMC Health Serv Res Research Article BACKGROUND: Successful application of Quality Improvement (QI) methods is challenging, and awareness of the role context plays has increased. Complexity science has been advocated as a way to inform change efforts. However, empirical support is scarce, and it is still difficult to grasp the practical implications for QI interventions. The aim of this study was to use a complexity-based leadership framework to explain how managers in a clinical department addressed external requirements to cut costs without compromising patient outcomes and experience. METHODS: Explanatory case study design of a Danish OB/GYN department tasked to improve efficiency. Data came from documents, 30 interviews, and 250 h of observations over 3 years. A Complexity Analysis Framework that combined two complexity-based leadership frameworks was developed to analyze all changes implemented to reduce cost, while maintaining clinical quality. RESULTS: Managers reframed the efficiency requirement as an opportunity for quality improvement. Multiple simple, complicated, and complex situations were addressed with an adaptive approach to quality improvement. Changes were made to clinical pathways for individual conditions (n = 37), multiple conditions (n = 7), and at the organizational level (n = 9). At the organizational level, changes addressed referral practice, physical space in the department, flow and capacity, discharge speed, and managerial support. Managers shared responsibility with staff; together they took a “professional path” and systematically analyzed each clinical pathway through process mapping, attentive to patterns that emerged, before deciding on the next steps, such as a engaging in a complex process of probing – the iterative development and testing of new responses. CONCLUSIONS: Quality improvement efforts could benefit from an understanding of the importance of learning and sharing responsibility to deal with the co-existing degrees of contextual complexity in modern health care. By “making things complicated” through a systematic analysis that engages staff in an open and reflective dialog, clinical praxis and established organizational structures can be questioned and improved. The Complexity Analysis Framework could then help managers to identify improvement opportunities, know when to implement technical solutions, and when to keep abreast of emerging patterns and allow appropriate responses to complex challenges to evolve. BioMed Central 2019-11-14 /pmc/articles/PMC6857274/ /pubmed/31727069 http://dx.doi.org/10.1186/s12913-019-4705-x Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Storkholm, Marie Höjriis
Mazzocato, Pamela
Savage, Carl
Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
title Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
title_full Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
title_fullStr Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
title_full_unstemmed Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
title_short Make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
title_sort make it complicated: a qualitative study utilizing a complexity framework to explain improvement in health care
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6857274/
https://www.ncbi.nlm.nih.gov/pubmed/31727069
http://dx.doi.org/10.1186/s12913-019-4705-x
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