Exploring the Nurses' Perspective on Using Remote Electronic Symptom Monitoring in Clinical Decision-Making Among Patients With Metastatic Lung Cancer
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Objectives
Patient-reported outcome (PRO) measures are commonly used in clinical practice, and an important aspect is how healthcare professionals use these measures to make clinical decisions. This study aimed 1) to understand how remote electronic symptom monitoring using PRO measures can support oncology nurses' clinical decision-making in patients with metastatic lung cancer and 2) to explore factors that potentially can influence how remote symptom monitoring supports clinical decision-making.
Data Sources
A qualitative approach using semistructured interviews was conducted with 18 registered nurses working with remote symptom monitoring at oncology departments at eight Danish hospitals.
Conclusion
Nurses reported that remote symptom monitoring supports clinical decision-making because it assisted in identifying relevant problems, monitoring relevant changes over time, and prompting relevant clinical actions. Factors that affected how remote symptom monitoring could support clinical decision-making were access to supplemental information, the trustworthiness of PRO data, nursing competencies and responsibilities, working conditions, and care at a distance.
Implication for Nursing Practice
The use of PRO data in the clinical decision-making process is highly dependent on the nurses' professional competencies, the organizational structure, and the trustworthiness of PRO data. Thus, we recommend considering these factors before implementing PRO data in routine care. For example, train clinical staff in using PRO data in their clinical decision-making, develop guidance for how to use PRO data with other forms of data to make sound clinical actions, and ensure that organizational resources are sufficient.
Patient-reported outcome (PRO) measures are commonly used in clinical practice, and an important aspect is how healthcare professionals use these measures to make clinical decisions. This study aimed 1) to understand how remote electronic symptom monitoring using PRO measures can support oncology nurses' clinical decision-making in patients with metastatic lung cancer and 2) to explore factors that potentially can influence how remote symptom monitoring supports clinical decision-making.
Data Sources
A qualitative approach using semistructured interviews was conducted with 18 registered nurses working with remote symptom monitoring at oncology departments at eight Danish hospitals.
Conclusion
Nurses reported that remote symptom monitoring supports clinical decision-making because it assisted in identifying relevant problems, monitoring relevant changes over time, and prompting relevant clinical actions. Factors that affected how remote symptom monitoring could support clinical decision-making were access to supplemental information, the trustworthiness of PRO data, nursing competencies and responsibilities, working conditions, and care at a distance.
Implication for Nursing Practice
The use of PRO data in the clinical decision-making process is highly dependent on the nurses' professional competencies, the organizational structure, and the trustworthiness of PRO data. Thus, we recommend considering these factors before implementing PRO data in routine care. For example, train clinical staff in using PRO data in their clinical decision-making, develop guidance for how to use PRO data with other forms of data to make sound clinical actions, and ensure that organizational resources are sufficient.
Originalsprog | Engelsk |
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Artikelnummer | 151517 |
Tidsskrift | Seminars in Oncology Nursing |
Vol/bind | 39 |
Udgave nummer | 6 |
Antal sider | 9 |
ISSN | 0749-2081 |
DOI | |
Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
This work was supported by the Danish Cancer Society (grant No. R184-A11805 ) and Danish Research Center for Lung Cancer (grant No. R198-A14299 Rp 2043 ).
Publisher Copyright:
© 2023 Elsevier Inc.
ID: 379033964