Prospective trial on telemonitoring of geriatric cancer patients using handheld devices

Application of Patient-Generated Health Data Among Older Adults With Cancer: Scoping Review

BACKGROUND

The advancement of information and communication technologies has spurred a growing interest in and increased applications of patient-generated health data (PGHD). In particular, PGHD may be promising for older adults with cancer who have increased survival rates and experience a variety of symptoms.

OBJECTIVE

This scoping review aimed to identify the characteristics of research on PGHD as applied to older adults with cancer and to assess the current use of PGHD.

METHODS

Guided by Arksey and O'Malley as well as the JBI (Joanna Briggs Institute) methodology for scoping reviews, 6 electronic databases were searched: PubMed, Embase, CINAHL, Cochrane Library, Scopus, and Web of Science. In addition, the reference lists of the selected studies were screened to identify gray literature. The researchers independently screened the literature according to the predefined eligibility criteria. Data from the selected studies were extracted, capturing study, participant, and PGHD characteristics.

RESULTS

Of the 1090 identified studies, 88 were selected. The publication trend gradually increased, with a majority of studies published since 2017 (69/88, 78%). Almost half of the studies were conducted in North America (38/88, 43%), followed by Europe (30/88, 34%). The most common setting in which the studies were conducted was the participant's home (69/88, 78%). The treatment status varied; the median sample size was 50 (IQR 33.8-84.0). The devices that were used to measure the PGHD were classified as research-grade wearable devices (57/113, 50.4%), consumer-grade wearable devices (28/113, 24.8%), or smartphones or tablet PCs for mobile apps (23/113, 20.4%). More than half of the studies measured physical activity (69/123, 56.1%), followed by patient-reported outcomes (23/123, 18.7%), vital signs (13/123, 10.6%), and sleep (12/123, 9.8%). The PGHD were mainly collected passively (63/88, 72%), and active collection methods were used from 2015 onward (20/88, 23%). In this review, the stages of PGHD use were classified as follows: (1) identification, monitoring, review, and analysis (88/88, 100%); (2) feedback and reporting (32/88, 39%); (3) motivation (30/88, 34%); and (4) education and coaching (19/88, 22%).

CONCLUSIONS

This scoping review provides a comprehensive summary of the overall characteristics and use stages of PGHD in older adults with various types and stages of cancer. Future research should emphasize the use of PGHD, which interacts with patients to provide patient-centered care through patient engagement. By enhancing symptom monitoring, enabling timely interventions, and promoting patient involvement, PGHD have the potential to improve the well-being of older adults with cancer, contributing to better health management and quality of life. Therefore, our findings may provide valuable insights into PGHD that health care providers and researchers can use for geriatric cancer care.

TRIAL REGISTRATION

Open Science Framework Registry OSF.IO/FZRD5; https://doi.org/10.17605/OSF.IO/FZRD5.

Oncologic treatment support via a dedicated mobile app: a prospective feasibility evaluation (OPTIMISE-1)

BACKGROUND

Mobile health (mhealth) is gaining interest, with mobile devices and apps being ever more available among medical facilities and patients. However, in the field of radiation oncology, the medical benefits of mhealth apps are still underexplored. As an additional approach to patient care during radiotherapy, we designed a mobile treatment surveillance app based on patient-reported outcomes.

OBJECTIVE

We aimed to examine the feasibility of app-based treatment surveillance in patients undergoing radiotherapy (RT). Alongside technical practicability and acceptance, we assessed patient satisfaction and quality of life during treatment.

METHODS

This prospective single-center study was performed at Heidelberg University Hospital between August 2018 and January 2020. During RT we measured patients' quality of life, symptoms, and treatment satisfaction. Respective questionnaires (EORTC QLQ-C30 with diagnosis-specific modules, RAND PSQ-18) were presented to patients via a mobile app running on a designated tablet device. The primary endpoint was determined by the fraction of patients who completed at least 80% of the items. Secondary endpoints were disease-related quality of life and patient satisfaction.

RESULTS

A total of 49 cancer patients (14 breast, 13 pelvic, 12 lung, 10 prostate) were eligible for analysis. 79.6% (95% confidence interval: 66.4-88.5%; n = 39) of all patients completed at least 80% of the items received by the mobile app. A mean of 227.5 ± 48.25 questions were answered per patient. Breast cancer patients showed the highest rate of answered questions, with 92.9% (n = 13) completing at least 80% of the items.

CONCLUSION

Patients showed high acceptance, with 79.6% (n = 39) completing at least 80% of the given items. The use of a mobile app for reporting symptoms and quality of life during RT is feasible and well accepted by patients. It may allow for resource-efficient, detailed feedback to the medical staff and assist in the assessment of side effects over time.

Mobile applications in radiation oncology-current choices and future potentials

PURPOSE

To review existing scientific literature on mobile applications (apps) in the field of radiation oncology and to evaluate characteristics of commercially available apps across different platforms.

METHODS

A systematic review of the literature for publications presenting apps in the field of radiation oncology was carried out using the PubMed database, Cochrane library, Google Scholar, and annual meetings of major radiation oncology societies. Additionally, the two major marketplaces for apps, App Store and Play Store, were searched for available radiation oncology apps for patients and health care professionals (HCP).

RESULTS

A total of 38 original publications which met the inclusion criteria were identified. Within those publications, 32 apps were developed for patients and 6 for HCP. The vast majority of patient apps focused on documenting electronic patient-reported outcomes (ePROs). In the two major marketplaces, 26 apps were found, mainly supporting HCP with dose calculations.

CONCLUSION

Apps used in (and for) scientific research in radiation oncology are rarely available for patients and HCP in common marketplaces.

Predictors of Adherence to Cancer-Related mHealth Apps in Cancer Patients Undergoing Oncological or Follow-Up Treatment-A Scoping Review

mHealth interventions in cancer care are being increasingly applied in various settings. Nevertheless, there is a phenomenon wherein individuals show different usage patterns, which could affect the effectiveness of the intervention. In general, it is important to know the predictors of app adherence and usage patterns to improve the design and content (i.e., tailoring). The aim of this scoping review was to provide an overview of predictors of adherence to cancer-related mHealth apps in cancer patients. A systematic literature search was conducted in March 2021 in the electronic databases PubMed, CINAHL, and PsychINFO without limitation in year, focusing on cancer patients undergoing oncological or follow-up treatment using mHealth apps. The initial database search yielded a total of N = 8035 records. After title, abstract, and full-text screening, 10 articles met inclusion criteria. Studies were published between 2013 and 2020. Studies focused on children and adolescents (2/10) as well as adults (8/10). The predictors identified could be categorized into sociodemographic variables, cancer-related factors and others. This study provides an initial insight into relevant predictors of app adherence in cancer patients. However, no clear predictor of increased app adherence was found. Further research of usage patterns is therefore needed so that mHealth interventions can be tailored during development.

Treating advanced lung cancer in older Veterans with comorbid conditions and frailty

Advanced lung cancer is a deadly malignancy that is a common cause of death among Veterans. Significant advancements in lung cancer therapeutics have been made over the past decade and survival outcomes have improved. The Veteran population is older, has more medical comorbidities and frailty compared to the general population. These factors must be accounted for when evaluating patients for treatment and selecting treatment options. This article explores the impact of these important issues in the management of advanced lung cancer. Recent clinical trials leading to the approval of modern therapies will be outlined and treatment outcomes specific to older patients discussed. The impact of key comorbidities that are common in Veterans and their impact on lung cancer treatment will be reviewed. There is no gold standard frailty index for assessment of frailty in patients with advanced lung cancer and the ability to predict tolerability and benefit from systemic therapies. Currently available systemic therapies are associated with higher risk of adverse events and lower potential for clinically meaningful improvement in outcomes. Future research needs to focus on designing better frailty indices and developing novel therapies that are safer and more effective therapies for frail patients, who constitute a considerable proportion of individuals diagnosed with lung cancer.

Smartphone application-based follow-up care of patients after bariatric surgery: A mixed-method study of usability

OBJECTIVE

Due to potential short-term and long-term complications, adequate lifelong follow-up is crucial for patients after bariatric surgery. However, compliance with postoperative follow-up is poor despite clear national and international guidelines. This feasibility trial aimed to evaluate the usability of a smartphone application-based follow-up program in patients after bariatric surgery.

METHODS

Patients were included after having undergone a primary bariatric surgery. Instead of attending meetings in our outpatient clinic, they were followed up using a smartphone application. After 6 months, the System Usability Scale (SUS) was used to measure participant perception. Additional interviews were performed to gain more insight into the usability of the app.

RESULTS

Between August 2020 and February 2021, 52 patients met the inclusion criteria and agreed to participate in the study, of whom 5 (9.6%) dropped out of the study. At the time of analysis, 31 patients have been followed up for 6 months, among whom 26 patients completed the SUS questionnaire. The mean overall score of SUS is 82.1 ± 19.8. In the qualitative analysis, participants were generally positive about the follow-up care and found it easy to use, despite some minor technical problems.

CONCLUSION

Our smartphone app-based follow-up program was proven to be effective in the aftercare succeeding bariatric surgery. Our data indicates that the satisfaction, efficiency, learnability, and ease of use of the smartphone application were coherent in the acceptance and use of mobile technology by patients.

A review of AI and Data Science support for cancer management

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 AI and 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's 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 109 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 systems 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.

A narrative review of current evidence supporting the implementation of electronic patient-reported outcome measures in the management of chronic diseases

An application of telemedicine of growing interest and relevance is the use of personal computers and mobile devices to collect patient-reported outcomes (PROs). PROs are self-reports of patients' health status without interpretation by anyone else. The tools developed to assess PROs are known as patient-reported outcomes measures (PROMs). The technological innovations that have led to an increased ownership of electronic devices have also facilitated the development of electronic PROMs (ePROMs). ePROMs are a conduit for telemedicine in the care of patients with chronic diseases. Various studies have demonstrated that the use of ePROMs in routine clinical practice is both acceptable and feasible with patients increasingly expressing a preference for an electronic mode of administration. There is increasing evidence that the use of electronic patient-reported outcome (ePROMs) could have significant impacts on outcomes valued by patients, healthcare providers and researchers. Whilst the development and implementation of these systems may be initially costly and resource-intensive, patient preferences and existing evidence to support their implementation suggests the need for continued research prioritisation in this area. This narrative review summarises and discusses evidence of the impact of ePROMs on clinical parameters and outcomes relevant to chronic diseases. We also explore recently published literature regarding issues that may influence the robust implementation of ePROMs for routine clinical practice.