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Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox

BACKGROUND: Measuring and improving outcomes is a central element of value-based health care. However, selecting improvement interventions based on outcome measures is complex and tools to support the selection process are lacking. The goal was to present strategies for the systematic identification...

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Autores principales: Zipfel, Nina, Groenewoud, A. Stef, Rensing, Benno J. W. M., Daeter, Edgar J., Dijksman, Lea M., Dambrink, Jan-Henk E., van der Wees, Philip J., Westert, Gert P., van der Nat, Paul B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082899/
https://www.ncbi.nlm.nih.gov/pubmed/32192477
http://dx.doi.org/10.1186/s12913-020-05090-z
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author Zipfel, Nina
Groenewoud, A. Stef
Rensing, Benno J. W. M.
Daeter, Edgar J.
Dijksman, Lea M.
Dambrink, Jan-Henk E.
van der Wees, Philip J.
Westert, Gert P.
van der Nat, Paul B.
author_facet Zipfel, Nina
Groenewoud, A. Stef
Rensing, Benno J. W. M.
Daeter, Edgar J.
Dijksman, Lea M.
Dambrink, Jan-Henk E.
van der Wees, Philip J.
Westert, Gert P.
van der Nat, Paul B.
author_sort Zipfel, Nina
collection PubMed
description BACKGROUND: Measuring and improving outcomes is a central element of value-based health care. However, selecting improvement interventions based on outcome measures is complex and tools to support the selection process are lacking. The goal was to present strategies for the systematic identification and selection of improvement interventions applied to the case of aortic valve disease and to combine various methods of process and outcome assessment into one integrated approach for quality improvement. METHODS: For this case study a concept-driven mixed-method approach was applied for the identification of improvement intervention clusters including: (1) benchmarking outcomes, (2) data exploration, (3) care delivery process analysis, and (4) monitoring of ongoing improvements. The main outcome measures were long-term survival and 30-day mortality. For the selection of an improvement intervention, the causal relations between the potential improvement interventions and outcome measures were quantified followed by a team selection based on consensus from a multidisciplinary team of professionals. RESULTS: The study resulted in a toolbox: the Intervention Selection Toolbox (IST). The toolbox comprises two phases: (a) identifying potential for improvement, and (b) selecting an effective intervention from the four clusters expected to lead to the desired improvement in outcomes. The improvements identified for the case of aortic valve disease with impact on long-term survival in the context of the studied hospital in 2015 include: anticoagulation policy, increased attention to nutritional status of patients and determining frailty of patients before the treatment decision. CONCLUSIONS: Identifying potential for improvement and carefully selecting improvement interventions based on (clinical) outcome data demands a multifaceted approach. Our toolbox integrates both care delivery process analyses and outcome analyses. The toolbox is recommended for use in hospital care for the selection of high-impact improvement interventions.
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spelling pubmed-70828992020-03-23 Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox Zipfel, Nina Groenewoud, A. Stef Rensing, Benno J. W. M. Daeter, Edgar J. Dijksman, Lea M. Dambrink, Jan-Henk E. van der Wees, Philip J. Westert, Gert P. van der Nat, Paul B. BMC Health Serv Res Research Article BACKGROUND: Measuring and improving outcomes is a central element of value-based health care. However, selecting improvement interventions based on outcome measures is complex and tools to support the selection process are lacking. The goal was to present strategies for the systematic identification and selection of improvement interventions applied to the case of aortic valve disease and to combine various methods of process and outcome assessment into one integrated approach for quality improvement. METHODS: For this case study a concept-driven mixed-method approach was applied for the identification of improvement intervention clusters including: (1) benchmarking outcomes, (2) data exploration, (3) care delivery process analysis, and (4) monitoring of ongoing improvements. The main outcome measures were long-term survival and 30-day mortality. For the selection of an improvement intervention, the causal relations between the potential improvement interventions and outcome measures were quantified followed by a team selection based on consensus from a multidisciplinary team of professionals. RESULTS: The study resulted in a toolbox: the Intervention Selection Toolbox (IST). The toolbox comprises two phases: (a) identifying potential for improvement, and (b) selecting an effective intervention from the four clusters expected to lead to the desired improvement in outcomes. The improvements identified for the case of aortic valve disease with impact on long-term survival in the context of the studied hospital in 2015 include: anticoagulation policy, increased attention to nutritional status of patients and determining frailty of patients before the treatment decision. CONCLUSIONS: Identifying potential for improvement and carefully selecting improvement interventions based on (clinical) outcome data demands a multifaceted approach. Our toolbox integrates both care delivery process analyses and outcome analyses. The toolbox is recommended for use in hospital care for the selection of high-impact improvement interventions. BioMed Central 2020-03-19 /pmc/articles/PMC7082899/ /pubmed/32192477 http://dx.doi.org/10.1186/s12913-020-05090-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research Article
Zipfel, Nina
Groenewoud, A. Stef
Rensing, Benno J. W. M.
Daeter, Edgar J.
Dijksman, Lea M.
Dambrink, Jan-Henk E.
van der Wees, Philip J.
Westert, Gert P.
van der Nat, Paul B.
Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
title Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
title_full Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
title_fullStr Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
title_full_unstemmed Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
title_short Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
title_sort selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the intervention selection toolbox
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082899/
https://www.ncbi.nlm.nih.gov/pubmed/32192477
http://dx.doi.org/10.1186/s12913-020-05090-z
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