Opportunities for computational tools in palliative care: Supporting patient needs and lowering burden

Durieux, Brigitte N.; Tarbi, Elise

doi:10.1177/02692163221122261

Cited by 5 publications

(3 citation statements)

References 9 publications

(9 reference statements)

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“…present opportunities to glean symptom information from a variety of data sources in a rapid, low-burden manner, which may support efforts to detect symptoms and improve care. 37 Keyword libraries, used alongside NLP, are dictionaries of language which can be used to detect constructs of interest. These tools can be used on their own or to supplement the development and validation of more sophisticated AI models.…”

Section: Background and Significancementioning

confidence: 99%

“…A library of this sort could help researchers detect symptoms from the rich, encompassing data source of audio-recorded clinical encounters, which are increasingly available with the rise of Telehealth and offer a high-impact setting for computational tools to record and summarize symptoms both in-the-moment and longitudinally. 37 …”

Section: Background and Significancementioning

confidence: 99%

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Development of a keyword library for capturing PRO-CTCAE-focused “symptom talk” in oncology conversations

et al. 2023

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Objectives As computational methods for detecting symptoms can help us better attend to patient suffering, the objectives of this study were to develop and evaluate the performance of a natural language processing keyword library for detecting symptom talk, and to describe symptom communication within our dataset to generate insights for future model building. Materials and Methods This was a secondary analysis of 121 transcribed outpatient oncology conversations from the Communication in Oncologist-Patient Encounters trial. Through an iterative process of identifying symptom expressions via inductive and deductive techniques, we generated a library of keywords relevant to the Patient-Reported Outcome version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) framework from 90 conversations, and tested the library on 31 additional transcripts. To contextualize symptom expressions and the nature of misclassifications, we qualitatively analyzed 450 mislabeled and properly labeled symptom-positive turns. Results The final library, comprising 1320 terms, identified symptom talk among conversation turns with an F1 of 0.82 against a PRO-CTCAE-focused gold standard, and an F1 of 0.61 against a broad gold standard. Qualitative observations suggest that physical symptoms are more easily detected than psychological symptoms (eg, anxiety), and ambiguity persists throughout symptom communication. Discussion This rudimentary keyword library captures most PRO-CTCAE-focused symptom talk, but the ambiguity of symptom speech limits the utility of rule-based methods alone, and limits to generalizability must be considered. Conclusion Our findings highlight opportunities for more advanced computational models to detect symptom expressions from transcribed clinical conversations. Future improvements in speech-to-text could enable real-time detection at scale.

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Section: Background and Significancementioning

confidence: 99%

Section: Background and Significancementioning

confidence: 99%

Development of a keyword library for capturing PRO-CTCAE-focused “symptom talk” in oncology conversations

et al. 2023

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show abstract

“…From a service level, telehealth could help organisations to support staff coordination, education and pastoral care. Finally, novel data technologies provide new possibilities to innovate care through its incorporation with telehealth, 17 for example artificial intelligence (e.g., natural language processing of free text notes), audio (e.g., speech pattern analysis) and visual (e.g., facial gestures analysis), which could potentially provide the clinician with data that adds value to the consultation.…”

Section: Potential Opportunities For Palliative Care Telehealthmentioning

confidence: 99%

Telehealth requires improved evidence to achieve its full potential in palliative care

Nwosu

2023

Palliat Med

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Big Data in Oncology Nursing Research: State of the Science

Harris¹,

Pozzar²,

Conley³

et al. 2023

Seminars in Oncology Nursing

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Opportunities for computational tools in palliative care: Supporting patient needs and lowering burden

Cited by 5 publications

References 9 publications

Development of a keyword library for capturing PRO-CTCAE-focused “symptom talk” in oncology conversations

Development of a keyword library for capturing PRO-CTCAE-focused “symptom talk” in oncology conversations

Telehealth requires improved evidence to achieve its full potential in palliative care

Big Data in Oncology Nursing Research: State of the Science

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