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An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study
BACKGROUND: Primary care health professionals, especially family physicians, see a variety of wounds, and yet—despite the frequency of providing wound care—many family physicians do not feel confident in wound care management. This is partly due to a lack of formal wound education in Family Medicine...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5941095/ https://www.ncbi.nlm.nih.gov/pubmed/29691213 http://dx.doi.org/10.2196/resprot.9116 |
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author | Jordan, Scott McSwiggan, Jane Parker, Joanne Halas, Gayle A Friesen, Marcia |
author_facet | Jordan, Scott McSwiggan, Jane Parker, Joanne Halas, Gayle A Friesen, Marcia |
author_sort | Jordan, Scott |
collection | PubMed |
description | BACKGROUND: Primary care health professionals, especially family physicians, see a variety of wounds, and yet—despite the frequency of providing wound care—many family physicians do not feel confident in wound care management. This is partly due to a lack of formal wound education in Family Medicine programs. While there are numerous electronic wound care resources available in the UK and North America, none were identified that address the specific need in supporting clinical decision-making in wound dressing selection. At the same time, healthcare providers are increasingly using technology in personal and professional contexts, and a logical extension is to use technology for knowledge translation strategies. OBJECTIVE: This work developed a prototype mobile health software application named WounDS, designed to support clinical decision-making in selecting wound dressings. This article presents the development and evaluation plan for the WounDS app. METHODS: WounDS has been developed on the iOS platform. The primary specification included ease of use, in that one of the primary influences in user adoption would be the ability to receive a wound dressing recommendation in under 30 seconds and under 5 taps on the screen. The WounDS app guides users through a series of binary decisions for assessing the wound and provides a wound dressing recommendation. The selection algorithm is based in best practices using the Wound Bed Preparation Paradigm. RESULTS: Current work is underway to examine the implementation needs for WounDS to be most effectively utilized and to pilot test its feasibility and use in clinical care. Data will be collected through user trials, focus groups, and user metadata will be collected within the app. Optimizing these preconditions will enable a subsequent phase of study to determine effects on clinical decision-making and clinical outcomes. CONCLUSIONS: WounDS is designed for knowledge translation, use of technology in clinical decision-making, and continuity of care. The benefits of WounDS include the potential to improve healthcare providers’ competency in wound management and to improve wound healing through better alignment with evidence-based best practices in wound dressing selection, consistency in care from primary to community care, and subsequent downstream impacts in quality of life for patients. |
format | Online Article Text |
id | pubmed-5941095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-59410952018-05-09 An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study Jordan, Scott McSwiggan, Jane Parker, Joanne Halas, Gayle A Friesen, Marcia JMIR Res Protoc Protocol BACKGROUND: Primary care health professionals, especially family physicians, see a variety of wounds, and yet—despite the frequency of providing wound care—many family physicians do not feel confident in wound care management. This is partly due to a lack of formal wound education in Family Medicine programs. While there are numerous electronic wound care resources available in the UK and North America, none were identified that address the specific need in supporting clinical decision-making in wound dressing selection. At the same time, healthcare providers are increasingly using technology in personal and professional contexts, and a logical extension is to use technology for knowledge translation strategies. OBJECTIVE: This work developed a prototype mobile health software application named WounDS, designed to support clinical decision-making in selecting wound dressings. This article presents the development and evaluation plan for the WounDS app. METHODS: WounDS has been developed on the iOS platform. The primary specification included ease of use, in that one of the primary influences in user adoption would be the ability to receive a wound dressing recommendation in under 30 seconds and under 5 taps on the screen. The WounDS app guides users through a series of binary decisions for assessing the wound and provides a wound dressing recommendation. The selection algorithm is based in best practices using the Wound Bed Preparation Paradigm. RESULTS: Current work is underway to examine the implementation needs for WounDS to be most effectively utilized and to pilot test its feasibility and use in clinical care. Data will be collected through user trials, focus groups, and user metadata will be collected within the app. Optimizing these preconditions will enable a subsequent phase of study to determine effects on clinical decision-making and clinical outcomes. CONCLUSIONS: WounDS is designed for knowledge translation, use of technology in clinical decision-making, and continuity of care. The benefits of WounDS include the potential to improve healthcare providers’ competency in wound management and to improve wound healing through better alignment with evidence-based best practices in wound dressing selection, consistency in care from primary to community care, and subsequent downstream impacts in quality of life for patients. JMIR Publications 2018-04-24 /pmc/articles/PMC5941095/ /pubmed/29691213 http://dx.doi.org/10.2196/resprot.9116 Text en ©Scott Jordan, Jane McSwiggan, Joanne Parker, Gayle A. Halas, Marcia Friesen. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 24.04.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included. |
spellingShingle | Protocol Jordan, Scott McSwiggan, Jane Parker, Joanne Halas, Gayle A Friesen, Marcia An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study |
title | An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study |
title_full | An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study |
title_fullStr | An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study |
title_full_unstemmed | An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study |
title_short | An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study |
title_sort | mhealth app for decision-making support in wound dressing selection (wounds): protocol for a user-centered feasibility study |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5941095/ https://www.ncbi.nlm.nih.gov/pubmed/29691213 http://dx.doi.org/10.2196/resprot.9116 |
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