SymptomCare@Home

Beck, Susan L.; Eaton, Linda H.; Echeverria, Christina; Mooney, Kathi

doi:10.1097/cin.0000000000000364

Cited by 46 publications

(24 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, a mobile phone–based system for the remote monitoring and management of chemotherapy-related side effects was evaluated in Canadian patients with cancer; however, its impact on health-related quality of life has not yet been tested [ 11 ]. Several randomized controlled trials evaluating remote electronic monitoring and symptom management are still ongoing [ 14 - 16 ].…”

Section: Discussionmentioning

confidence: 99%

“…If the alert contained any severe symptoms, it would be labelled as urgent and an appointed research nurse would be trained to react in accordance with the prespecified medical algorithms. Such algorithms are also incorporated in recently reported proposals of studies [ 14 - 16 ] to assess symptom burden, quality of life, supportive care needs, anxiety, self-care, self-efficacy, work limitations, and cost effectiveness.…”

Section: Discussionmentioning

confidence: 99%

“…Integration of the patient-reported outcome into routine care was even shown to prolong overall survival in patients with advanced solid tumors by 5 months [ 13 ]. With increased patient willingness to use technology, there are possibilities for expansion of patient-centered medicine [ 14 - 16 ]. At present, few apps are used for the self-management of symptoms [ 7 , 9 - 11 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study

Kuhar¹,

Cepeda²,

Kovač³

et al. 2020

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

Background Providing patients with cancer who are undergoing systemic therapy with useful information about symptom management is essential to prevent unnecessary deterioration of quality of life. Objective The aim was to evaluate whether use of an app for symptom management was associated with any change in patient quality of life or use of health resources. Methods Outpatients with early stage breast cancer receiving systemic therapy were recruited at the Institute of Oncology in Ljubljana, Slovenia. Patients who received systemic therapy between December 2017 and March 2018 (control group) and between April 2018 and September 2018 (intervention group) were eligible. All patients received standard care, but only those in the intervention group were asked to use mPRO Mamma, an Android-based smartphone app, in addition. The app supported daily tracking of 50 symptoms, allowed users to grade their symptom severity (as mild, moderate, or severe), and also provided in-depth descriptions and recommendations based on reported symptom level. Patient-reported outcomes in both groups were assessed through the European Organisation for Research and Treatment of Cancer (EORTC) core (C-30) and breast cancer (BR-23) questionnaires, as well as a questionnaire about health resources use. The primary outcomes were the difference in the global quality of life between groups and the difference in summary score of the EORTC C-30 questionnaire between groups after 3 time periods (the first week of treatment, the first treatment cycle, and the entire treatment). The secondary outcome was the use of health resources (doctor visits and hospitalizations) in each time period. Other scales were used for exploratory analysis. Results The mean difference between the intervention group (n=46) and the control group (n=45) in global quality of life (adjusted for baseline and type of surgery) after the first week was 10.1 (95% CI 1.8 to 18.5, P=.02). The intervention group summary scores were significantly higher than those of the control group after the first week (adjusted mean difference: 8.9, 95% CI 3.1 to 14.7, P=.003) and at the end of treatment (adjusted mean difference: 10.6, 95% CI 3.9 to 17.3, P=.002). Use of health resources was not statistically significant between the groups in either the first week (P=.12) or the first treatment cycle (P=.13). Exploratory analysis findings demonstrated clinically important improvements (indicated by EORTC C-30 or BR-23 scale scores)—social, physical, role, and cognitive function were improved while pain, appetite loss, and systemic therapy side effects were reduced. Conclusions Use of the app enabled patients undergoing systemic therapy for early stage breast cancer to better cope with symptoms which was demonstrated by a better global quality of life and summary score after the first week and by a better summary score at the end of treatment in the intervention group compared to those of the control group, but no change in the use of health resources was demonstrated.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study

Kuhar¹,

Cepeda²,

Kovač³

et al. 2020

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…The last group of papers focuses on efficacy (improved skills) for handling problems associated with disease and its symptoms [97,98]. Wiklander et al [97] describe the web app developed as part of the Fex-Can (Fertility and Sexuality Following Cancer) project aimed at adolescent and young adults.…”

Section: Addressed Aspects Of Patient Behaviormentioning

confidence: 99%

“…The app underwent a 2-month feasibility study where more than half participants remained active throughout that period and considered the content to be relevant and informative. Finally, Beck et al [98] describe the SymptomCare@Home system focused on patients receiving chemotherapy. The system facilitates reporting of relevant symptoms through IVR (interactive voice response), it also delivers immediate feedback and self-management coaching appropriate for the patient's state and treatment toxicity.…”

Section: Addressed Aspects Of Patient Behaviormentioning

confidence: 99%

A Review of AI and Data Science Support for Cancer Management

Parimbelli

Wilk

Cornet

et al. 2020

Preprint

View full text Add to dashboard Cite

Introduction - Thanks to improvement of care, cancer has become a chronic condition. But due to the toxicity of treatment, the importance of supporting the quality of life (QoL) of cancer patients increases. Monitoring and managing QoL relies on data collected by the patient in his/her home environment, its integration, and its analysis, which supports personalization of cancer management recommendations. We review the state-of-the-art of computerized systems that employ Data Science methods to monitor the health status and provide support to cancer patients managed at home. Objective - Our main objective is to analyze the literature to identify open research challenges that a novel decision support system for cancer patients and clinicians will need to address, point to potential solutions, and provide a list of established best-practices to adopt. Methods - We designed a review study, in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzing studies retrieved from PubMed related to monitoring cancer patients in their home environments via sensors and self-reporting: what data is collected, what are the techniques used to collect data, semantically integrate it, infer the patient state from it and deliver coaching/behavior change interventions. Results - Starting from an initial corpus of 819 unique articles, a total of 180 papers were considered in the full-text analysis and 110 were finally included in the review. Our findings are organized and presented in four main sub-topics consisting of data collection, data integration, predictive modeling and patient coaching. Conclusion - Development of modern decision support system for cancer needs to utilize best practices like the use of validated electronic questionnaires for quality of life assessment, adoption of appropriate information modeling standards supplemented by terminologies/ontologies, adherence to FAIR data principles, external validation, stratification of patients in subgroups for better predictive modeling, and adoption of formal behavior change theories. Open research challenges include supporting emotional and social dimensions of well-being, including PROs in predictive modeling, and providing better customization of behavioral interventions for the specific population of cancer patients.

show abstract

Essential Components of an Electronic Patient-Reported Symptom Monitoring and Management System

Mooney,

Gullatte,

Iacob

et al. 2024

JAMA Netw Open

View full text Add to dashboard Cite

ImportanceMulticomponent electronic patient-reported outcome cancer symptom management systems reduce symptom burden. Whether all components contribute to symptom reduction is unknown.ObjectiveTo deconstruct intervention components of the Symptom Care at Home (SCH) system, a digital symptom monitoring and management intervention that has demonstrated efficacy, to determine which component or combination of components results in the lowest symptom burden.Design, Setting, and ParticipantsThis randomized clinical trial included participants who were older than 18 years, had been diagnosed with cancer, had a life expectancy of 3 months or greater, were beginning a chemotherapy course planned for at least 3 cycles, spoke English, and had daily access and ability to use a telephone. Eligible participants were identified from the Huntsman Cancer Institute, University of Utah (Salt Lake City), and from Emory University Winship Cancer Institute, including Grady Memorial Hospital (Atlanta, Georgia), from August 7, 2017, to January 17, 2020. Patients receiving concurrent radiation therapy were excluded. Dates of analysis were from February 1, 2020, to December 22, 2023.InterventionsParticipants reported symptoms daily during a course of chemotherapy and received automated self-management coaching with an activity tracker without (group 1) and with (group 2) visualization, nurse practitioner (NP) follow-up for moderate-to-severe symptoms without (group 3) and with (group 4) decision support, or the complete SCH intervention (group 5).Main Outcomes and MeasuresThe primary outcome, symptom burden, was assessed as the summed severity of 11 chemotherapy-related symptoms rated on a scale of 1 to 10 (with higher scores indicating greater severity), if present.ResultsThe 757 participants (mean [SD] age, 59.2 [12.9] years) from 2 cancer centers were primarily female (61.2%). The most common cancer diagnoses were breast (132 [17.4%]), lung (107 [14.1%]), and colorectal (99 [13.1%]) cancers; 369 patients (48.7%) had metastatic disease. The complete SCH intervention including automated self-management coaching and NP follow-up with decision support (group 5) was superior in reducing symptom burden to either of the self-management coaching groups, as shown by the mean group differences in area under the curve (group 1, 1.86 [95% CI, 1.30-2.41] and group 2, 2.38 [95% CI, 1.84-2.92]; both P &lt; .001), and to either of the NP follow-up groups (group 3, 0.57 [95% CI, 0.03-1.11]; P =.04; and group 4, 0.66 [95% CI, 0.14-1.19]; P = .014). Additionally, NP follow-up was superior to self-management coaching (group 1 vs group 3, 1.29 [95% CI, 0.72-1.86]; group 1 vs group 4, 1.20 [95% 12 CI, 0.64-1.76]; group 2 vs group 3, 1.81 [95% CI, 1.25-2.37]; and group 2 vs group 4, 1.72 [95% CI, 1.17-2.26]; all P &lt; .001), but there was no difference between the 2 self-management coaching groups (−0.52 [95% CI, −1.09 to 0.05]; P = .07) or between the 2 NP groups (−0.10 [95% CI, −0.65 to 0.46]; P = .74).Conclusions and RelevanceIn this randomized clinical trial of adult participants undergoing chemotherapy treatment for cancer, the complete intervention, rather than any individual component of the SCH system, achieved the greatest symptom burden reduction. These findings suggest that a multicomponent digital approach to cancer symptom management may offer optimal symptom burden reduction.Trial RegistrationClinicalTrials.gov Identifier: NCT02779725

show abstract

SymptomCare@Home

Cited by 46 publications

References 32 publications

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study

A Review of AI and Data Science Support for Cancer Management

Essential Components of an Electronic Patient-Reported Symptom Monitoring and Management System

Contact Info

Product

Resources

About