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The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology
BACKGROUND: The NHS is facing substantial pressures to recover from the COVID-19 pandemic. Optimising workforce modelling is a fundamental component of the recovery plan. The Clinically Lead workforcE and Activity Redesign (CLEAR) programme is a unique methodology that trains clinicians to redesign...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933657/ https://www.ncbi.nlm.nih.gov/pubmed/35305625 http://dx.doi.org/10.1186/s12913-022-07757-1 |
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author | Corner, Evelyn J. Camilleri, Matthew Dholakia, Shruti Gredal, Charlotte Hansen, Tina Jeans, John LeNovere, Marie Mallender, Jacqueline Monkhouse, Alex Purkiss, Claire Ting, Tai Ken Vindrola-Padros, Cecilia Welfare, Stephen Wood, Danny Wood, James |
author_facet | Corner, Evelyn J. Camilleri, Matthew Dholakia, Shruti Gredal, Charlotte Hansen, Tina Jeans, John LeNovere, Marie Mallender, Jacqueline Monkhouse, Alex Purkiss, Claire Ting, Tai Ken Vindrola-Padros, Cecilia Welfare, Stephen Wood, Danny Wood, James |
author_sort | Corner, Evelyn J. |
collection | PubMed |
description | BACKGROUND: The NHS is facing substantial pressures to recover from the COVID-19 pandemic. Optimising workforce modelling is a fundamental component of the recovery plan. The Clinically Lead workforcE and Activity Redesign (CLEAR) programme is a unique methodology that trains clinicians to redesign services, building intrinsic capacity and capability, optimising patient care and minimising the need for costly external consultancy. This paper describes the CLEAR methodology and the evaluation of previous CLEAR projects, including the return on investment. METHODS: CLEAR is a work-based learning programme that combines qualitative techniques with data analytics to build innovations and new models of care. It has four unique stages: (1) Clinical engagement- used to gather rich insights from stakeholders and clinicians. (2) Data interrogation- utilising clinical and workforce data for cohort analysis. (3) Innovation- using structured innovation methods to develop new models of care. (4) Recommendations- report writing, impact assessment and presentation of key findings to executive boards. A mixed-methods formative evaluation was carried out on completed projects, which included semi-structured interviews and surveys with CLEAR associates and stakeholders, and a health economic logic model that was developed to link the inputs, processes, outputs and the outcome of CLEAR as well as the potential impacts of the changes identified from the projects. RESULTS: CLEAR provides a more cost-effective delivery of complex change programmes than the alternatives – resulting in a cost saving of £1.90 for every £1 spent independent of implementation success. Results suggest that CLEAR recommendations are more likely to be implemented compared to other complex healthcare interventions because of the levels of clinical engagement and have a potential return on investment of up to £14 over 5 years for every £1 invested. CLEAR appears to have a positive impact on staff retention and wellbeing, the cost of a CLEAR project is covered if one medical consultant remains in post for a year. CONCLUSIONS: The unique CLEAR methodology is a clinically effective and cost-effective complex healthcare innovation that optimises workforce and activity design, as well as improving staff retention. Embedding CLEAR methodology in the NHS could have substantial impact on patient care, staff well-being and service provision. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-07757-1. |
format | Online Article Text |
id | pubmed-8933657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89336572022-03-21 The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology Corner, Evelyn J. Camilleri, Matthew Dholakia, Shruti Gredal, Charlotte Hansen, Tina Jeans, John LeNovere, Marie Mallender, Jacqueline Monkhouse, Alex Purkiss, Claire Ting, Tai Ken Vindrola-Padros, Cecilia Welfare, Stephen Wood, Danny Wood, James BMC Health Serv Res Research BACKGROUND: The NHS is facing substantial pressures to recover from the COVID-19 pandemic. Optimising workforce modelling is a fundamental component of the recovery plan. The Clinically Lead workforcE and Activity Redesign (CLEAR) programme is a unique methodology that trains clinicians to redesign services, building intrinsic capacity and capability, optimising patient care and minimising the need for costly external consultancy. This paper describes the CLEAR methodology and the evaluation of previous CLEAR projects, including the return on investment. METHODS: CLEAR is a work-based learning programme that combines qualitative techniques with data analytics to build innovations and new models of care. It has four unique stages: (1) Clinical engagement- used to gather rich insights from stakeholders and clinicians. (2) Data interrogation- utilising clinical and workforce data for cohort analysis. (3) Innovation- using structured innovation methods to develop new models of care. (4) Recommendations- report writing, impact assessment and presentation of key findings to executive boards. A mixed-methods formative evaluation was carried out on completed projects, which included semi-structured interviews and surveys with CLEAR associates and stakeholders, and a health economic logic model that was developed to link the inputs, processes, outputs and the outcome of CLEAR as well as the potential impacts of the changes identified from the projects. RESULTS: CLEAR provides a more cost-effective delivery of complex change programmes than the alternatives – resulting in a cost saving of £1.90 for every £1 spent independent of implementation success. Results suggest that CLEAR recommendations are more likely to be implemented compared to other complex healthcare interventions because of the levels of clinical engagement and have a potential return on investment of up to £14 over 5 years for every £1 invested. CLEAR appears to have a positive impact on staff retention and wellbeing, the cost of a CLEAR project is covered if one medical consultant remains in post for a year. CONCLUSIONS: The unique CLEAR methodology is a clinically effective and cost-effective complex healthcare innovation that optimises workforce and activity design, as well as improving staff retention. Embedding CLEAR methodology in the NHS could have substantial impact on patient care, staff well-being and service provision. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-07757-1. BioMed Central 2022-03-19 /pmc/articles/PMC8933657/ /pubmed/35305625 http://dx.doi.org/10.1186/s12913-022-07757-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Corner, Evelyn J. Camilleri, Matthew Dholakia, Shruti Gredal, Charlotte Hansen, Tina Jeans, John LeNovere, Marie Mallender, Jacqueline Monkhouse, Alex Purkiss, Claire Ting, Tai Ken Vindrola-Padros, Cecilia Welfare, Stephen Wood, Danny Wood, James The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology |
title | The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology |
title_full | The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology |
title_fullStr | The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology |
title_full_unstemmed | The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology |
title_short | The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology |
title_sort | clinically led worforce and activity redesign (clear) programme: a novel data-driven healthcare improvement methodology |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933657/ https://www.ncbi.nlm.nih.gov/pubmed/35305625 http://dx.doi.org/10.1186/s12913-022-07757-1 |
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