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Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship
Background. The complexity of decision science models may prevent their use to assist in decision making. User-centered design (UCD) principles provide an opportunity to engage end users in model development and refinement, potentially reducing complexity and increasing model utilization in a practi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926380/ https://www.ncbi.nlm.nih.gov/pubmed/36798090 http://dx.doi.org/10.1177/23814683231153378 |
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author | Rivers, Zachary Roth, Joshua A. Wright, Winona Rim, Sun Hee Richardson, Lisa C. Thomas, Cheryll C. Townsend, Julie S. Ramsey, Scott D. |
author_facet | Rivers, Zachary Roth, Joshua A. Wright, Winona Rim, Sun Hee Richardson, Lisa C. Thomas, Cheryll C. Townsend, Julie S. Ramsey, Scott D. |
author_sort | Rivers, Zachary |
collection | PubMed |
description | Background. The complexity of decision science models may prevent their use to assist in decision making. User-centered design (UCD) principles provide an opportunity to engage end users in model development and refinement, potentially reducing complexity and increasing model utilization in a practical setting. We report our experiences with UCD to develop a modeling tool for cancer control planners evaluating cancer survivorship interventions. Design. Using UCD principles (described in the article), we developed a dynamic cohort model of cancer survivorship for individuals with female breast, colorectal, lung, and prostate cancer over 10 y. Parameters were obtained from the National Program of Cancer Registries and peer-reviewed literature, with model outcomes captured in quality-adjusted life-years and net monetary benefit. Prototyping and iteration were conducted with structured focus groups involving state cancer control planners and staff from the Centers for Disease Control and Prevention and the American Public Health Association. Results. Initial feedback highlighted model complexity and unclear purpose as barriers to end user uptake. Revisions addressed complexity by simplifying model input requirements, providing clear examples of input types, and reducing complex language. Wording was added to the results page to explain the interpretation of results. After these updates, feedback demonstrated that end users more clearly understood how to use and apply the model for cancer survivorship resource allocation tasks. Conclusions. A UCD approach identified challenges faced by end users in integrating a decision aid into their workflow. This approach created collaboration between modelers and end users, tailoring revisions to meet the needs of the users. Future models developed for individuals without a decision science background could leverage UCD to ensure the model meets the needs of the intended audience. HIGHLIGHTS: Model complexity and unclear purpose are 2 barriers that prevent lay users from integrating decision science tools into their workflow. Modelers could integrate the user-centered design framework when developing a model for lay users to reduce complexity and ensure the model meets the needs of the users. |
format | Online Article Text |
id | pubmed-9926380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-99263802023-02-15 Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship Rivers, Zachary Roth, Joshua A. Wright, Winona Rim, Sun Hee Richardson, Lisa C. Thomas, Cheryll C. Townsend, Julie S. Ramsey, Scott D. MDM Policy Pract Original Research Article Background. The complexity of decision science models may prevent their use to assist in decision making. User-centered design (UCD) principles provide an opportunity to engage end users in model development and refinement, potentially reducing complexity and increasing model utilization in a practical setting. We report our experiences with UCD to develop a modeling tool for cancer control planners evaluating cancer survivorship interventions. Design. Using UCD principles (described in the article), we developed a dynamic cohort model of cancer survivorship for individuals with female breast, colorectal, lung, and prostate cancer over 10 y. Parameters were obtained from the National Program of Cancer Registries and peer-reviewed literature, with model outcomes captured in quality-adjusted life-years and net monetary benefit. Prototyping and iteration were conducted with structured focus groups involving state cancer control planners and staff from the Centers for Disease Control and Prevention and the American Public Health Association. Results. Initial feedback highlighted model complexity and unclear purpose as barriers to end user uptake. Revisions addressed complexity by simplifying model input requirements, providing clear examples of input types, and reducing complex language. Wording was added to the results page to explain the interpretation of results. After these updates, feedback demonstrated that end users more clearly understood how to use and apply the model for cancer survivorship resource allocation tasks. Conclusions. A UCD approach identified challenges faced by end users in integrating a decision aid into their workflow. This approach created collaboration between modelers and end users, tailoring revisions to meet the needs of the users. Future models developed for individuals without a decision science background could leverage UCD to ensure the model meets the needs of the intended audience. HIGHLIGHTS: Model complexity and unclear purpose are 2 barriers that prevent lay users from integrating decision science tools into their workflow. Modelers could integrate the user-centered design framework when developing a model for lay users to reduce complexity and ensure the model meets the needs of the users. SAGE Publications 2023-02-09 /pmc/articles/PMC9926380/ /pubmed/36798090 http://dx.doi.org/10.1177/23814683231153378 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Article Rivers, Zachary Roth, Joshua A. Wright, Winona Rim, Sun Hee Richardson, Lisa C. Thomas, Cheryll C. Townsend, Julie S. Ramsey, Scott D. Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship |
title | Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship |
title_full | Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship |
title_fullStr | Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship |
title_full_unstemmed | Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship |
title_short | Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship |
title_sort | translating an economic analysis into a tool for public health resource allocation in cancer survivorship |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926380/ https://www.ncbi.nlm.nih.gov/pubmed/36798090 http://dx.doi.org/10.1177/23814683231153378 |
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