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Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer
PURPOSE: Remote symptom monitoring (RSM) using electronic patient-reported outcomes enables patients with cancer to communicate symptoms between in-person visits. A better understanding of key RSM implementation outcomes is crucial to optimize efficiency and guide implementation efforts. This analys...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530733/ https://www.ncbi.nlm.nih.gov/pubmed/37279409 http://dx.doi.org/10.1200/CCI.23.00015 |
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author | Caston, Nicole E. Franks, Jeffrey A. Balas, Nora Eltoum, Noon Thigpen, Haley Patterson, Megan Azuero, Andres Ojesina, Akinyemi I. Dent, D'Ambra N. Hildreth, Keyonsis Lalor, Fallon R. McGowen, Chelsea Huang, Chao-Hui S. Dionne-Odom, J. Nicholas Weiner, Bryan J. Jackson, Bradford E. Basch, Ethan M. Stover, Angela M. Howell, Doris Pierce, Jennifer Y. Rocque, Gabrielle B. |
author_facet | Caston, Nicole E. Franks, Jeffrey A. Balas, Nora Eltoum, Noon Thigpen, Haley Patterson, Megan Azuero, Andres Ojesina, Akinyemi I. Dent, D'Ambra N. Hildreth, Keyonsis Lalor, Fallon R. McGowen, Chelsea Huang, Chao-Hui S. Dionne-Odom, J. Nicholas Weiner, Bryan J. Jackson, Bradford E. Basch, Ethan M. Stover, Angela M. Howell, Doris Pierce, Jennifer Y. Rocque, Gabrielle B. |
author_sort | Caston, Nicole E. |
collection | PubMed |
description | PURPOSE: Remote symptom monitoring (RSM) using electronic patient-reported outcomes enables patients with cancer to communicate symptoms between in-person visits. A better understanding of key RSM implementation outcomes is crucial to optimize efficiency and guide implementation efforts. This analysis evaluated the association between the severity of patient-reported symptom alerts and time to response by the health care team. METHODS: This secondary analysis included women with stage I-IV breast cancer who received care at a large academic medical center in the Southeastern United States (October 2020-September 2022). Symptom surveys with at least one severe symptom alert were categorized as severe. Response time was categorized as optimal if the alert was closed by a health care team member within 48 hours. Odds ratios (ORs), predicted probabilities, and 95% CIs were estimated using a patient-nested logistic regression model. RESULTS: Of 178 patients with breast cancer included in this analysis, 63% of patients identified as White and 85% of patients had a stage I-III or early-stage cancer. The median age at diagnosis was 55 years (IQR, 42-65). Of 1,087 surveys included, 36% reported at least one severe symptom alert and 77% had an optimal response time by the health care team. When compared with surveys that had no severe symptom alerts, surveys with at least one severe symptom alert had similar odds of having an optimal response time (OR, 0.97; 95% CI, 0.68 to 1.38). The results were similar when stratified by cancer stage. CONCLUSION: Response times to symptom alerts were similar for alerts with at least one severe symptom compared with alerts with no severe symptoms. This suggests that alert management is being incorporated into routine workflows and not prioritized based on disease or symptom alert severity. |
format | Online Article Text |
id | pubmed-10530733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-105307332023-09-28 Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer Caston, Nicole E. Franks, Jeffrey A. Balas, Nora Eltoum, Noon Thigpen, Haley Patterson, Megan Azuero, Andres Ojesina, Akinyemi I. Dent, D'Ambra N. Hildreth, Keyonsis Lalor, Fallon R. McGowen, Chelsea Huang, Chao-Hui S. Dionne-Odom, J. Nicholas Weiner, Bryan J. Jackson, Bradford E. Basch, Ethan M. Stover, Angela M. Howell, Doris Pierce, Jennifer Y. Rocque, Gabrielle B. JCO Clin Cancer Inform ORIGINAL REPORTS PURPOSE: Remote symptom monitoring (RSM) using electronic patient-reported outcomes enables patients with cancer to communicate symptoms between in-person visits. A better understanding of key RSM implementation outcomes is crucial to optimize efficiency and guide implementation efforts. This analysis evaluated the association between the severity of patient-reported symptom alerts and time to response by the health care team. METHODS: This secondary analysis included women with stage I-IV breast cancer who received care at a large academic medical center in the Southeastern United States (October 2020-September 2022). Symptom surveys with at least one severe symptom alert were categorized as severe. Response time was categorized as optimal if the alert was closed by a health care team member within 48 hours. Odds ratios (ORs), predicted probabilities, and 95% CIs were estimated using a patient-nested logistic regression model. RESULTS: Of 178 patients with breast cancer included in this analysis, 63% of patients identified as White and 85% of patients had a stage I-III or early-stage cancer. The median age at diagnosis was 55 years (IQR, 42-65). Of 1,087 surveys included, 36% reported at least one severe symptom alert and 77% had an optimal response time by the health care team. When compared with surveys that had no severe symptom alerts, surveys with at least one severe symptom alert had similar odds of having an optimal response time (OR, 0.97; 95% CI, 0.68 to 1.38). The results were similar when stratified by cancer stage. CONCLUSION: Response times to symptom alerts were similar for alerts with at least one severe symptom compared with alerts with no severe symptoms. This suggests that alert management is being incorporated into routine workflows and not prioritized based on disease or symptom alert severity. Wolters Kluwer Health 2023-06-06 /pmc/articles/PMC10530733/ /pubmed/37279409 http://dx.doi.org/10.1200/CCI.23.00015 Text en © 2023 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | ORIGINAL REPORTS Caston, Nicole E. Franks, Jeffrey A. Balas, Nora Eltoum, Noon Thigpen, Haley Patterson, Megan Azuero, Andres Ojesina, Akinyemi I. Dent, D'Ambra N. Hildreth, Keyonsis Lalor, Fallon R. McGowen, Chelsea Huang, Chao-Hui S. Dionne-Odom, J. Nicholas Weiner, Bryan J. Jackson, Bradford E. Basch, Ethan M. Stover, Angela M. Howell, Doris Pierce, Jennifer Y. Rocque, Gabrielle B. Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer |
title | Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer |
title_full | Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer |
title_fullStr | Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer |
title_full_unstemmed | Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer |
title_short | Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer |
title_sort | evaluating nurses' time to response by severity and cancer stage in a remote symptom monitoring program for patients with breast cancer |
topic | ORIGINAL REPORTS |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530733/ https://www.ncbi.nlm.nih.gov/pubmed/37279409 http://dx.doi.org/10.1200/CCI.23.00015 |
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