Assessing Patient Perspectives and the Health Equity of a Digital Cancer Symptom Remote Monitoring and Management System.


Journal

JCO clinical cancer informatics
ISSN: 2473-4276
Titre abrégé: JCO Clin Cancer Inform
Pays: United States
ID NLM: 101708809

Informations de publication

Date de publication:
Jul 2024
Historique:
medline: 23 7 2024
pubmed: 23 7 2024
entrez: 23 7 2024
Statut: ppublish

Résumé

People with cancer experience poorly controlled symptoms that persist between treatment visits. Automated digital technology can remotely monitor and facilitate symptom management at home. Essential to digital interventions is patient engagement, user satisfaction, and intervention benefits that are distributed across patient populations so as not to perpetuate inequities. We evaluated Symptom Care at Home (SCH), an automated digital platform, to determine patient engagement, satisfaction, and whether intervention subgroups gained similar symptom reduction benefits. 358 patients with cancer receiving a course of chemotherapy were randomly assigned to SCH or usual care (UC). Both groups reported daily on 11 symptoms and completed the SF36 (Short Form Health Survey) monthly. SCH participants received immediate automated self-care coaching on reported symptoms. As needed, nurse practitioners followed up for poorly controlled symptoms. The average participant was White (83%), female (75%), and urban-dwelling (78.6%). Daily call adherence was 90% of expected days. Participants reported high user satisfaction. SCH participants had lower symptom burden than UC in all subgroups: age, sex, race, income, residence type, diagnosis, and stage (all Participants were highly satisfied and consistently engaged the SCH platform. SCH men gained large MH improvements, perhaps from increased comfort in sharing concerns through automated interactions. Although all intervention subgroups benefited, non-White participants and those with lower income gained higher symptom reduction benefit, suggesting that systematic care through digital tools can overcome existing disparities in symptom care outcomes.

Identifiants

pubmed: 39042843
doi: 10.1200/CCI.23.00243
doi:

Banques de données

ClinicalTrials.gov
['NCT01973946']

Types de publication

Journal Article Randomized Controlled Trial

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2300243

Auteurs

Kathi Mooney (K)

College of Nursing, University of Utah, Salt Lake City, UT.
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.

Susan L Beck (SL)

College of Nursing, University of Utah, Salt Lake City, UT.
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.

Christina Wilson (C)

School of Nursing, University of Alabama at Birmingham, Birmingham, AL.

Lorinda Coombs (L)

School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC.

Meagan Whisenant (M)

Department of Behavioral Science, University of Texas MD Anderson Cancer Center, Houston, TX.

Ann Marie Moraitis (AM)

Department of Pediatric Oncology, Dana Farber Cancer Institute, Boston, MA.

Elizabeth A Sloss (EA)

College of Nursing, University of Utah, Salt Lake City, UT.

Natalya Alekhina (N)

College of Nursing, University of Utah, Salt Lake City, UT.

Jennifer Lloyd (J)

College of Nursing, University of Utah, Salt Lake City, UT.
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.

Mary Steinbach (M)

College of Nursing, University of Utah, Salt Lake City, UT.
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.

Bridget Nicholson (B)

College of Nursing, University of Utah, Salt Lake City, UT.

Eli Iacob (E)

College of Nursing, University of Utah, Salt Lake City, UT.

Gary Donaldson (G)

College of Nursing, University of Utah, Salt Lake City, UT.
School of Medicine, University of Utah, Salt Lake City, UT.

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Classifications MeSH