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21-05-2024

Optimization of alert notifications in electronic patient-reported outcome (ePRO) remote symptom monitoring systems (AFT-39)

Auteurs: Gina L. Mazza, Amylou C. Dueck, Brenda Ginos, Jennifer Jansen, Allison M. Deal, Philip Carr, Victoria S. Blinder, Gita Thanarajasingam, Mattias Jonsson, Minji K. Lee, Lauren J. Rogak, Gita N. Mody, Deborah Schrag, Ethan Basch

Gepubliceerd in: Quality of Life Research | Uitgave 7/2024

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Abstract

Purpose

Clinical benefits result from electronic patient-reported outcome (ePRO) systems that enable remote symptom monitoring. Although clinically useful, real-time alert notifications for severe or worsening symptoms can overburden nurses. Thus, we aimed to algorithmically identify likely non-urgent alerts that could be suppressed.

Methods

We evaluated alerts from the PRO-TECT trial (Alliance AFT-39) in which oncology practices implemented remote symptom monitoring. Patients completed weekly at-home ePRO symptom surveys, and nurses received real-time alert notifications for severe or worsening symptoms. During parts of the trial, patients and nurses each indicated whether alerts were urgent or could wait until the next visit. We developed an algorithm for suppressing alerts based on patient assessment of urgency and model-based predictions of nurse assessment of urgency.

Results

593 patients participated (median age = 64 years, 61% female, 80% white, 10% reported never using computers/tablets/smartphones). Patients completed 91% of expected weekly surveys. 34% of surveys generated an alert, and 59% of alerts prompted immediate nurse actions. Patients considered 10% of alerts urgent. Of the remaining cases, nurses considered alerts urgent more often when patients reported any worsening symptom compared to the prior week (33% of alerts with versus 26% without any worsening symptom, p = 0.009). The algorithm identified 38% of alerts as likely non-urgent that could be suppressed with acceptable discrimination (sensitivity = 80%, 95% CI [76%, 84%]; specificity = 52%, 95% CI [49%, 55%]).

Conclusion

An algorithm can identify remote symptom monitoring alerts likely to be considered non-urgent by nurses, and may assist in fostering nurse acceptance and implementation feasibility of ePRO systems.
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Literatuur
1.
go back to reference Cleeland, C. S., Zhao, F., Chang, V. T., et al. (2013). The symptom burden of cancer: Evidence for a core set of cancer-related and treatment-related symptoms from the Eastern Cooperative Oncology Group Symptom Outcomes and Practice Patterns study. Cancer, 119(24), 4333–4340.CrossRefPubMed Cleeland, C. S., Zhao, F., Chang, V. T., et al. (2013). The symptom burden of cancer: Evidence for a core set of cancer-related and treatment-related symptoms from the Eastern Cooperative Oncology Group Symptom Outcomes and Practice Patterns study. Cancer, 119(24), 4333–4340.CrossRefPubMed
2.
go back to reference Reilly, C. M., Bruner, D. W., Mitchell, S. A., et al. (2013). A literature synthesis of symptom prevalence and severity in persons receiving active cancer treatment. Supportive Care in Cancer, 21(6), 1525–1550.CrossRefPubMedPubMedCentral Reilly, C. M., Bruner, D. W., Mitchell, S. A., et al. (2013). A literature synthesis of symptom prevalence and severity in persons receiving active cancer treatment. Supportive Care in Cancer, 21(6), 1525–1550.CrossRefPubMedPubMedCentral
3.
go back to reference Panattoni, L., Fedorenko, C., Greenwood-Hickman, M. A., et al. (2018). Characterizing potentially preventable cancer- and chronic disease-related emergency department use in the year after treatment initiation: A regional study. Journal of Oncology Practice/American Society of Clinical Oncology, 14(3), e176–e185.CrossRef Panattoni, L., Fedorenko, C., Greenwood-Hickman, M. A., et al. (2018). Characterizing potentially preventable cancer- and chronic disease-related emergency department use in the year after treatment initiation: A regional study. Journal of Oncology Practice/American Society of Clinical Oncology, 14(3), e176–e185.CrossRef
4.
go back to reference Henry, D. H., Viswanathan, H. N., Elkin, E. P., et al. (2008). Symptoms and treatment burden associated with cancer treatment: Results from a cross-sectional national survey in the US. Supportive Care in Cancer, 16(7), 791–801.CrossRefPubMed Henry, D. H., Viswanathan, H. N., Elkin, E. P., et al. (2008). Symptoms and treatment burden associated with cancer treatment: Results from a cross-sectional national survey in the US. Supportive Care in Cancer, 16(7), 791–801.CrossRefPubMed
5.
go back to reference Schmidt, T., Valuck, T., Perkins, B., et al. (2021). Improving patient-reported measures in oncology: A payer call to action. Journal of Managed Care and Specialty Pharmacy, 27(1), 118–126.CrossRefPubMed Schmidt, T., Valuck, T., Perkins, B., et al. (2021). Improving patient-reported measures in oncology: A payer call to action. Journal of Managed Care and Specialty Pharmacy, 27(1), 118–126.CrossRefPubMed
7.
go back to reference Basch, E., Schrag, D., Henson, S., et al. (2022). Effect of electronic symptom monitoring on patient-reported outcomes among patients with metastatic cancer: A randomized clinical trial. JAMA, 327(24), 2413–2422.CrossRefPubMedPubMedCentral Basch, E., Schrag, D., Henson, S., et al. (2022). Effect of electronic symptom monitoring on patient-reported outcomes among patients with metastatic cancer: A randomized clinical trial. JAMA, 327(24), 2413–2422.CrossRefPubMedPubMedCentral
9.
go back to reference Dueck, A. C., Mendoza, T. R., Mitchell, S. A., et al. (2015). Validity and reliability of the US National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). JAMA Oncology, 1(8), 1051–1059.CrossRefPubMedPubMedCentral Dueck, A. C., Mendoza, T. R., Mitchell, S. A., et al. (2015). Validity and reliability of the US National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). JAMA Oncology, 1(8), 1051–1059.CrossRefPubMedPubMedCentral
10.
go back to reference Al-Rashdan, A., Sutradhar, R., Nazeri-Rad, N., et al. (2021). Comparing the ability of physician-reported versus patient-reported performance status to predict survival in a population-based cohort of newly diagnosed cancer patients. Clinical Oncology (Royal College of Radiologists), 33(7), 476–482.CrossRef Al-Rashdan, A., Sutradhar, R., Nazeri-Rad, N., et al. (2021). Comparing the ability of physician-reported versus patient-reported performance status to predict survival in a population-based cohort of newly diagnosed cancer patients. Clinical Oncology (Royal College of Radiologists), 33(7), 476–482.CrossRef
11.
go back to reference Stover, A. M., Tompkins Stricker, C., Hammelef, K., et al. (2019). Using stakeholder engagement to overcome barriers to implementing patient-reported outcomes (PROs) in cancer care delivery: Approaches from 3 prospective studies. Medical Care, 57(5), S92–S99.CrossRefPubMed Stover, A. M., Tompkins Stricker, C., Hammelef, K., et al. (2019). Using stakeholder engagement to overcome barriers to implementing patient-reported outcomes (PROs) in cancer care delivery: Approaches from 3 prospective studies. Medical Care, 57(5), S92–S99.CrossRefPubMed
12.
go back to reference Kiernan, K. (2018). Insights into using the GLIMMIX procedure to model categorical outcomes with random effects. SAS Technical Papers, 2018, 1–23. Kiernan, K. (2018). Insights into using the GLIMMIX procedure to model categorical outcomes with random effects. SAS Technical Papers, 2018, 1–23.
13.
go back to reference Basch, E., Stover, A. M., Schrag, D., et al. (2020). Clinical utility and user perceptions of a digital system for electronic patient-reported symptom monitoring during routine cancer care: Findings from the PRO-TECT trial. JCO Clinical Cancer Informatics, 4, 947–957.CrossRefPubMed Basch, E., Stover, A. M., Schrag, D., et al. (2020). Clinical utility and user perceptions of a digital system for electronic patient-reported symptom monitoring during routine cancer care: Findings from the PRO-TECT trial. JCO Clinical Cancer Informatics, 4, 947–957.CrossRefPubMed
14.
go back to reference Mandrekar, J. N. (2010). Receiver operating characteristic curve in diagnostic test assessment. Journal of Thoracic Oncology, 5(9), 1315–1316.CrossRefPubMed Mandrekar, J. N. (2010). Receiver operating characteristic curve in diagnostic test assessment. Journal of Thoracic Oncology, 5(9), 1315–1316.CrossRefPubMed
Metagegevens
Titel
Optimization of alert notifications in electronic patient-reported outcome (ePRO) remote symptom monitoring systems (AFT-39)
Auteurs
Gina L. Mazza
Amylou C. Dueck
Brenda Ginos
Jennifer Jansen
Allison M. Deal
Philip Carr
Victoria S. Blinder
Gita Thanarajasingam
Mattias Jonsson
Minji K. Lee
Lauren J. Rogak
Gita N. Mody
Deborah Schrag
Ethan Basch
Publicatiedatum
21-05-2024
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 7/2024
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-024-03675-3