Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox
Abstract 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 identi...
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doaj-9ec5f424741c4e1e8d5cb6e43e5976c22020-11-25T02:25:36ZengBMCBMC Health Services Research1472-69632020-03-0120111310.1186/s12913-020-05090-zSelecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection ToolboxNina Zipfel0A. Stef Groenewoud1Benno J. W. M. Rensing2Edgar J. Daeter3Lea M. Dijksman4Jan-Henk E. Dambrink5Philip J. van der Wees6Gert P. Westert7Paul B. van der Nat8Department of Value-based Healthcare, St. Antonius HospitalRadboud university medical center, Radboud Institute for Health Sciences, Scientific Center for Quality of Healthcare (IQ healthcare)Department of Cardiology, St. Antonius HospitalDepartment of Cardiothoracic Surgery, St. Antonius HospitalDepartment of Value-based Healthcare, St. Antonius HospitalDepartment of Cardiology, Isala kliniekenRadboud university medical center, Radboud Institute for Health Sciences, Scientific Center for Quality of Healthcare (IQ healthcare)Radboud university medical center, Radboud Institute for Health Sciences, Scientific Center for Quality of Healthcare (IQ healthcare)Department of Value-based Healthcare, St. Antonius HospitalAbstract 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.http://link.springer.com/article/10.1186/s12913-020-05090-zQuality improvementPatient outcomesQuality managementValue-based healthcare |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nina Zipfel A. Stef Groenewoud Benno J. W. M. Rensing Edgar J. Daeter Lea M. Dijksman Jan-Henk E. Dambrink Philip J. van der Wees Gert P. Westert Paul B. van der Nat |
spellingShingle |
Nina Zipfel A. Stef Groenewoud Benno J. W. M. Rensing Edgar J. Daeter Lea M. Dijksman Jan-Henk E. Dambrink Philip J. van der Wees Gert P. Westert Paul B. van der Nat Selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the Intervention Selection Toolbox BMC Health Services Research Quality improvement Patient outcomes Quality management Value-based healthcare |
author_facet |
Nina Zipfel A. Stef Groenewoud Benno J. W. M. Rensing Edgar J. Daeter Lea M. Dijksman Jan-Henk E. Dambrink Philip J. van der Wees Gert P. Westert Paul B. van der Nat |
author_sort |
Nina Zipfel |
title |
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_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_sort |
selecting interventions to improve patient-relevant outcomes in health care for aortic valve disease – the intervention selection toolbox |
publisher |
BMC |
series |
BMC Health Services Research |
issn |
1472-6963 |
publishDate |
2020-03-01 |
description |
Abstract 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. |
topic |
Quality improvement Patient outcomes Quality management Value-based healthcare |
url |
http://link.springer.com/article/10.1186/s12913-020-05090-z |
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