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Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing
BACKGROUND: It is essential that cancer patients understand anticipated symptoms, how to self-manage these symptoms, and when to call their clinicians. However, patients are often ill-prepared to manage symptoms at home. Clinical decision support (CDS) is a potentially innovative way to provide info...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5975425/ https://www.ncbi.nlm.nih.gov/pubmed/29843767 http://dx.doi.org/10.1186/s12911-018-0608-8 |
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author | Cooley, Mary E. Abrahm, Janet L. Berry, Donna L. Rabin, Michael S. Braun, Ilana M. Paladino, Joanna Nayak, Manan M. Lobach, David F. |
author_facet | Cooley, Mary E. Abrahm, Janet L. Berry, Donna L. Rabin, Michael S. Braun, Ilana M. Paladino, Joanna Nayak, Manan M. Lobach, David F. |
author_sort | Cooley, Mary E. |
collection | PubMed |
description | BACKGROUND: It is essential that cancer patients understand anticipated symptoms, how to self-manage these symptoms, and when to call their clinicians. However, patients are often ill-prepared to manage symptoms at home. Clinical decision support (CDS) is a potentially innovative way to provide information to patients where and when they need it. The purpose of this project was to design and evaluate a simulated model of an algorithm-based CDS program for self-management of cancer symptoms. METHODS: This study consisted of three phases; development of computable algorithms for self-management of cancer symptoms using a modified ADAPTE process, evaluation of a simulated model of the CDS program, and identification of design objectives and lessons learned from the evaluation of patient-centered CDS. In phase 1, algorithms for pain, constipation and nausea/vomiting were developed by an expert panel. In phase 2, we conducted usability testing of a simulated symptom assessment and management intervention for self-care (SAMI-Self-Care) CDS program involving focus groups, interviews and surveys with cancer patients, their caregivers and clinicians. The Acceptability E-scale measured acceptability of the program. In phase 3, we developed design objectives and identified barriers to uptake of patient-centered CDS based on the data gathered from stakeholders. RESULTS: In phase 1, algorithms were reviewed and approved through a consensus meeting and majority vote. In phase 2, 24 patients & caregivers and 13 clinicians participated in the formative evaluation. Iterative changes were made in a simulated SAMI-Self-Care CDS program. Acceptability scores were high among patients, caregivers and clinicians. In phase 3, we formulated CDS design objectives, which included: 1) ensure patient safety, 2) communicate clinical concepts effectively, 3) promote communication with clinicians, 4) support patient activation, and 5) facilitate navigation and use. We identified patient barriers and clinician concerns to using CDS for symptom self-management, which were consistent with the chronic care model, a theoretical framework used to enhance patient-clinician communication and patient self-management. CONCLUSION: Patient safety and tool navigation were critical features of CDS for patient self-management. Insights gleaned from this study may be used to inform the development of CDS resources for symptom self-management in patients with other chronic conditions. |
format | Online Article Text |
id | pubmed-5975425 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59754252018-05-31 Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing Cooley, Mary E. Abrahm, Janet L. Berry, Donna L. Rabin, Michael S. Braun, Ilana M. Paladino, Joanna Nayak, Manan M. Lobach, David F. BMC Med Inform Decis Mak Research Article BACKGROUND: It is essential that cancer patients understand anticipated symptoms, how to self-manage these symptoms, and when to call their clinicians. However, patients are often ill-prepared to manage symptoms at home. Clinical decision support (CDS) is a potentially innovative way to provide information to patients where and when they need it. The purpose of this project was to design and evaluate a simulated model of an algorithm-based CDS program for self-management of cancer symptoms. METHODS: This study consisted of three phases; development of computable algorithms for self-management of cancer symptoms using a modified ADAPTE process, evaluation of a simulated model of the CDS program, and identification of design objectives and lessons learned from the evaluation of patient-centered CDS. In phase 1, algorithms for pain, constipation and nausea/vomiting were developed by an expert panel. In phase 2, we conducted usability testing of a simulated symptom assessment and management intervention for self-care (SAMI-Self-Care) CDS program involving focus groups, interviews and surveys with cancer patients, their caregivers and clinicians. The Acceptability E-scale measured acceptability of the program. In phase 3, we developed design objectives and identified barriers to uptake of patient-centered CDS based on the data gathered from stakeholders. RESULTS: In phase 1, algorithms were reviewed and approved through a consensus meeting and majority vote. In phase 2, 24 patients & caregivers and 13 clinicians participated in the formative evaluation. Iterative changes were made in a simulated SAMI-Self-Care CDS program. Acceptability scores were high among patients, caregivers and clinicians. In phase 3, we formulated CDS design objectives, which included: 1) ensure patient safety, 2) communicate clinical concepts effectively, 3) promote communication with clinicians, 4) support patient activation, and 5) facilitate navigation and use. We identified patient barriers and clinician concerns to using CDS for symptom self-management, which were consistent with the chronic care model, a theoretical framework used to enhance patient-clinician communication and patient self-management. CONCLUSION: Patient safety and tool navigation were critical features of CDS for patient self-management. Insights gleaned from this study may be used to inform the development of CDS resources for symptom self-management in patients with other chronic conditions. BioMed Central 2018-05-29 /pmc/articles/PMC5975425/ /pubmed/29843767 http://dx.doi.org/10.1186/s12911-018-0608-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Cooley, Mary E. Abrahm, Janet L. Berry, Donna L. Rabin, Michael S. Braun, Ilana M. Paladino, Joanna Nayak, Manan M. Lobach, David F. Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing |
title | Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing |
title_full | Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing |
title_fullStr | Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing |
title_full_unstemmed | Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing |
title_short | Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing |
title_sort | algorithm-based decision support for symptom self-management among adults with cancer: results of usability testing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5975425/ https://www.ncbi.nlm.nih.gov/pubmed/29843767 http://dx.doi.org/10.1186/s12911-018-0608-8 |
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