Cargando…
Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection
Support surfaces are an integral component of pressure ulcer prevention and treatment, but there is insufficient evidence to guide clinical decision making in this area. In an effort to provide clinical guidance for selecting support surfaces based on individual patient needs, the Wound, Ostomy and...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845766/ https://www.ncbi.nlm.nih.gov/pubmed/25549306 http://dx.doi.org/10.1097/WON.0000000000000103 |
_version_ | 1782428993313570816 |
---|---|
author | McNichol, Laurie Watts, Carolyn Mackey, Dianne Beitz, Janice M. Gray, Mikel |
author_facet | McNichol, Laurie Watts, Carolyn Mackey, Dianne Beitz, Janice M. Gray, Mikel |
author_sort | McNichol, Laurie |
collection | PubMed |
description | Support surfaces are an integral component of pressure ulcer prevention and treatment, but there is insufficient evidence to guide clinical decision making in this area. In an effort to provide clinical guidance for selecting support surfaces based on individual patient needs, the Wound, Ostomy and Continence Nurses Society (WOCN®) set out to develop an evidence- and consensus-based algorithm. A Task Force of clinical experts was identified who: 1) reviewed the literature and identified evidence for support surface use in the prevention and treatment of pressure ulcers; 2) developed supporting statements for essential components for the algorithm, 3) developed a draft algorithm for support surface selection; and 4) determined its face validity. A consensus panel of 20 key opinion leaders was then convened that: 1.) reviewed the draft algorithm and supporting statements, 2.) reached consensus on statements lacking robust supporting evidence, 3.) modified the draft algorithm and evaluated its content validity. The Content Validity Index (CVI) for the algorithm was strong (0.95 out of 1.0) with an overall mean score of 3.72 (out of 1 to 4), suggesting that the steps were appropriate to the purpose of the algorithm. To our knowledge, this is the first evidence and consensus based algorithm for support surface selection that has undergone content validation. |
format | Online Article Text |
id | pubmed-4845766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-48457662016-05-11 Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection McNichol, Laurie Watts, Carolyn Mackey, Dianne Beitz, Janice M. Gray, Mikel J Wound Ostomy Continence Nurs Wound Care Support surfaces are an integral component of pressure ulcer prevention and treatment, but there is insufficient evidence to guide clinical decision making in this area. In an effort to provide clinical guidance for selecting support surfaces based on individual patient needs, the Wound, Ostomy and Continence Nurses Society (WOCN®) set out to develop an evidence- and consensus-based algorithm. A Task Force of clinical experts was identified who: 1) reviewed the literature and identified evidence for support surface use in the prevention and treatment of pressure ulcers; 2) developed supporting statements for essential components for the algorithm, 3) developed a draft algorithm for support surface selection; and 4) determined its face validity. A consensus panel of 20 key opinion leaders was then convened that: 1.) reviewed the draft algorithm and supporting statements, 2.) reached consensus on statements lacking robust supporting evidence, 3.) modified the draft algorithm and evaluated its content validity. The Content Validity Index (CVI) for the algorithm was strong (0.95 out of 1.0) with an overall mean score of 3.72 (out of 1 to 4), suggesting that the steps were appropriate to the purpose of the algorithm. To our knowledge, this is the first evidence and consensus based algorithm for support surface selection that has undergone content validation. Lippincott Williams & Wilkins 2015-01 2015-01-13 /pmc/articles/PMC4845766/ /pubmed/25549306 http://dx.doi.org/10.1097/WON.0000000000000103 Text en © 2015 by the Wound, Ostomy and Continence Nurses Society |
spellingShingle | Wound Care McNichol, Laurie Watts, Carolyn Mackey, Dianne Beitz, Janice M. Gray, Mikel Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection |
title | Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection |
title_full | Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection |
title_fullStr | Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection |
title_full_unstemmed | Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection |
title_short | Identifying the Right Surface for the Right Patient at the Right Time: Generation and Content Validation of an Algorithm for Support Surface Selection |
title_sort | identifying the right surface for the right patient at the right time: generation and content validation of an algorithm for support surface selection |
topic | Wound Care |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845766/ https://www.ncbi.nlm.nih.gov/pubmed/25549306 http://dx.doi.org/10.1097/WON.0000000000000103 |
work_keys_str_mv | AT mcnichollaurie identifyingtherightsurfacefortherightpatientattherighttimegenerationandcontentvalidationofanalgorithmforsupportsurfaceselection AT wattscarolyn identifyingtherightsurfacefortherightpatientattherighttimegenerationandcontentvalidationofanalgorithmforsupportsurfaceselection AT mackeydianne identifyingtherightsurfacefortherightpatientattherighttimegenerationandcontentvalidationofanalgorithmforsupportsurfaceselection AT beitzjanicem identifyingtherightsurfacefortherightpatientattherighttimegenerationandcontentvalidationofanalgorithmforsupportsurfaceselection AT graymikel identifyingtherightsurfacefortherightpatientattherighttimegenerationandcontentvalidationofanalgorithmforsupportsurfaceselection |