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IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY

Ensuring a quality personal care aide (PCA) workforce is critical to meeting the needs of an aging population. The Integrated Model for Personal Assistant Research and Training (IMPART) program is a PCA training and advocacy model designed to increase the number of qualified PCAs. A core component i...

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Autores principales: Abujarad, Fuad, Swierenga, Sarah J, Luz, Clare, Hanson, Katherine, Curtin, Chris, Luo, Zhehui, Swanson-Aprill, Lauren A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6841470/
http://dx.doi.org/10.1093/geroni/igz038.2467
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author Abujarad, Fuad
Swierenga, Sarah J
Luz, Clare
Hanson, Katherine
Curtin, Chris
Luo, Zhehui
Swanson-Aprill, Lauren A
author_facet Abujarad, Fuad
Swierenga, Sarah J
Luz, Clare
Hanson, Katherine
Curtin, Chris
Luo, Zhehui
Swanson-Aprill, Lauren A
author_sort Abujarad, Fuad
collection PubMed
description Ensuring a quality personal care aide (PCA) workforce is critical to meeting the needs of an aging population. The Integrated Model for Personal Assistant Research and Training (IMPART) program is a PCA training and advocacy model designed to increase the number of qualified PCAs. A core component is an evidence-based, comprehensive PCA training program, Building Training…Building QualityTM (BTBQTM), supported by a robust data platform. This online system was designed to register, train and certify PCAs and Trainers, maintain a qualified PCA workforce database, and enhance the capacity to track IMPART process, performance, and impact measures. This innovative system was developed using a User-Centered Design approach, which includes four main user interfaces: Administrator, PCA, Trainer, and Public. It automates central administration functions, tracking, and reporting of training events, and standardizes and consolidates all training activities on a scalable and usable web-based technology platform. User acceptance testing of the tool and a usability evaluation with representative PCAs and trainers has been completed. Over 50 PCAs have completed BTBQTM modules and 22 new trainers have completed a new BTBQTM Trainer Certificate program during the tool development phase. The PCAs are already reporting substantially higher wages. Launching the new web-based data platform in April 2019 will make it possible for these programs to scale up for wide distribution. As more PCAs and trainers graduate, the number of qualified PCAs will increase exponentially. The data collected with this technology can inform responsible fiscal and policy decisions about resource allocation to support a stronger PCA workforce.
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spelling pubmed-68414702019-11-15 IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY Abujarad, Fuad Swierenga, Sarah J Luz, Clare Hanson, Katherine Curtin, Chris Luo, Zhehui Swanson-Aprill, Lauren A Innov Aging Session 3300 (Poster) Ensuring a quality personal care aide (PCA) workforce is critical to meeting the needs of an aging population. The Integrated Model for Personal Assistant Research and Training (IMPART) program is a PCA training and advocacy model designed to increase the number of qualified PCAs. A core component is an evidence-based, comprehensive PCA training program, Building Training…Building QualityTM (BTBQTM), supported by a robust data platform. This online system was designed to register, train and certify PCAs and Trainers, maintain a qualified PCA workforce database, and enhance the capacity to track IMPART process, performance, and impact measures. This innovative system was developed using a User-Centered Design approach, which includes four main user interfaces: Administrator, PCA, Trainer, and Public. It automates central administration functions, tracking, and reporting of training events, and standardizes and consolidates all training activities on a scalable and usable web-based technology platform. User acceptance testing of the tool and a usability evaluation with representative PCAs and trainers has been completed. Over 50 PCAs have completed BTBQTM modules and 22 new trainers have completed a new BTBQTM Trainer Certificate program during the tool development phase. The PCAs are already reporting substantially higher wages. Launching the new web-based data platform in April 2019 will make it possible for these programs to scale up for wide distribution. As more PCAs and trainers graduate, the number of qualified PCAs will increase exponentially. The data collected with this technology can inform responsible fiscal and policy decisions about resource allocation to support a stronger PCA workforce. Oxford University Press 2019-11-08 /pmc/articles/PMC6841470/ http://dx.doi.org/10.1093/geroni/igz038.2467 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Session 3300 (Poster)
Abujarad, Fuad
Swierenga, Sarah J
Luz, Clare
Hanson, Katherine
Curtin, Chris
Luo, Zhehui
Swanson-Aprill, Lauren A
IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY
title IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY
title_full IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY
title_fullStr IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY
title_full_unstemmed IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY
title_short IMPROVING THE PERSONAL CARE ASSISTANT WORKFORCE THROUGH TRAINING, DATA, AND TECHNOLOGY
title_sort improving the personal care assistant workforce through training, data, and technology
topic Session 3300 (Poster)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6841470/
http://dx.doi.org/10.1093/geroni/igz038.2467
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