How Should Oncologists Choose an Electronic Patient-Reported Outcome System for Remote Monitoring of Patients With Cancer?

Comparison of Electronic Surveillance With Routine Monitoring for Patients With Lymphoma at High Risk of Relapse: Prospective Randomized Controlled Phase 3 Trial (Sentinel Lymphoma)

Background

Relapse is a major event in patients with lymphoma. Therefore, early detection may have an impact on quality of life and overall survival. Patient-reported outcome measures have demonstrated clinical benefits for patients with lung cancer; however, evidence is lacking in patients with lymphoma. We evaluated the effect of a web-mediated follow-up application for patients with lymphoma at high risk of relapse.

Objective

This study aims to demonstrate that monitoring patients via a web application enables the detection of at least 30% more significant events occurring between 2 systematic follow-up consultations with the specialist using an electronic questionnaire.

Methods

We conducted a prospective, randomized phase 3 trial comparing the impact of web-based follow-up (experimental arm) with a standard follow-up (control arm). The trial was based on a 2-step triangular test and was designed to have a power of 90% to detect a 30% improvement in the detection of significant events. A significant event was defined as a relapse, progression, or a serious adverse event. The study covered the follow-up period after completion of first-line treatment or relapse (24 months). Eligible patients were aged 18 years and older and had lymphoma at a high risk of relapse. In the experimental arm, patients received a 16-symptom questionnaire by email every 2 weeks. An email alert was sent to the medical team based on a predefined algorithm. The primary objective was assessed after the inclusion of the 40th patient. The study was continued for the duration of the analysis.

Results

A total of 52 patients were included between July 12, 2017, and April 7, 2020, at 11 centers in France, with 27 in the experimental arm and 25 in the control arm. The median follow-up was 21.3 (range 1.3-25.6) months, and 121 events were reported during the study period. Most events occurred in the experimental arm (83/119, 69.7%) compared with 30.2% (36/119) in the control arm. A median number of 3.5 (range 1-8) events per patient occurred in the experimental arm, and 1.8 (range 1-6) occurred in the control arm (P=.01). Progression and infection were the most frequently reported events. Further, 19 patients relapsed during follow-up: 6 in the experimental arm and 13 in the control arm (P<.001), with a median follow-up of 7.7 (range 2.8-20.6) months and 6.7 (range 1.9-16.4) months (P=.94), respectively. Statistical analysis was conducted after including the 40th patient, which showed no superiority of the experimental arm over the control arm. The study was therefore stopped after the 52nd patient was enrolled.

Conclusions

The primary objective was not reached; however, patient-reported outcome measures remain essential for detecting adverse events in patients with cancer, and the electronic monitoring method needs to demonstrate its effectiveness and comply with international safety guidelines.

Cost-Effectiveness Analysis of a Machine Learning-Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at Home: Retrospective Study

BACKGROUND

Dependent older people or those losing their autonomy are at risk of emergency hospitalization. Digital systems that monitor health remotely could be useful in reducing these visits by detecting worsening health conditions earlier. However, few studies have assessed the medico-economic impact of these systems, particularly for older people.

OBJECTIVE

The objective of this study was to compare the clinical and economic impacts of an eHealth device in real life compared with the usual monitoring of older people living at home.

METHODS

This study was a comparative, retrospective, and controlled trial on data collected between May 31, 2021, and May 31, 2022, in one health care and home nursing center located in Brittany, France. Participants had to be aged >75 years, living at home, and receiving assistance from the home care service for at least 1 month. We implemented among the intervention group an eHealth system that produces an alert for a high risk of emergency department visits or hospitalizations. After each home visit, the home care aides completed a questionnaire on participants' functional status using a smartphone app, and the information was processed in real time by a previously developed machine learning algorithm that identifies patients at risk of an emergency visit within 7 to 14 days. In the case of predicted risk, the eHealth system alerted a coordinating nurse who could then inform the family carer and the patient's nurses or general practitioner.

RESULTS

A total of 120 patients were included in the study, with 60 in the control group and 60 in the intervention group. Among the 726 visits from the intervention group that were not followed by an alert, only 4 (0.6%) resulted in hospitalizations (P<.001), confirming the relevance of the system's alerts. Over the course of the study, 37 hospitalizations were recorded for 25 (20.8%) of the 120 patients. Additionally, of the 120 patients, 9 (7.5%) were admitted to a nursing home, and 7 (5.8%) died. Patients in the intervention group (56/60, 93%) remained at home significantly more often than those in the control group (48/60, 80%; P=.03). The total cost of primary care and hospitalization during the study was €167,000 (€1=US $1.09), with €108,000 (64.81%) attributed to the intervention group (P=.20).

CONCLUSIONS

This study presents encouraging results on the impact of a remote medical monitoring system for older adults, demonstrating a reduction in both emergency department visits and hospitalization costs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05221697; https://clinicaltrials.gov/study/NCT05221697.

A sociotechnical framework to assess patient-facing eHealth tools: results of a modified Delphi process

Among the thousands of eHealth tools available, the vast majority do not get past pilot phases because they cannot prove value, and only a few have been systematically assessed. Although multiple eHealth assessment frameworks have been developed, these efforts face multiple challenges. This study aimed to address some of these challenges by validating and refining an initial list of 55 assessment criteria based on previous frameworks through a two-round modified Delphi process with in-between rounds of interviews. The expert panel (n = 57) included participants from 18 countries and 9 concerned parties. A consensus was reached on 46 criteria that were classified into foundational and contextual criteria. The 36 foundational criteria focus on evaluating the eHealth tool itself and were grouped into nine clusters: technical aspects, clinical utility and safety, usability and human centricity, functionality, content, data management, endorsement, maintenance, and developer. The 10 contextual criteria focus on evaluating the factors that vary depending on the context the tool is being evaluated for and were grouped into seven clusters: data-protection compliance, safety regulatory compliance, interoperability and data integration, cultural requirements, affordability, cost-benefit, and implementability. The classification of criteria into foundational and contextual helps us assess not only the quality of an isolated tool, but also its potential fit in a specific setting. Criteria subscales may be particularly relevant when determining the strengths and weaknesses of the tool being evaluated. This granularity enables different concerned parties to make informed decisions about which tools to consider according to their specific needs and priorities.

Psychosocial assessment practices for hematopoietic stem cell transplantation: a national survey study

Psychosocial health predicts and contributes to medical outcomes for patients undergoing hematopoietic stem cell transplantation (HSCT). Yet, there are no standards for psychosocial assessments or support for both patients and caregivers across the care continuum. To examine the current state of psychosocial care, clinicians were sent a survey of their psychosocial assessment practices for patients and caregivers undergoing HSCT via the Listservs of professional organizations. Descriptive statistics and bivariate analyses were performed to summarize the findings. While 96% of participants reported routine pre-HSCT psychosocial assessment of patients, only 10.6% routinely used a validated transplant risk-assessment measure. Just 27% routinely performed follow-up psychosocial assessments. In contrast, only 47% of participants routinely assessed the psychosocial needs of family caregivers pre-HSCT, and 13% routinely performed follow-up assessments for caregivers. Most (90%) reported social workers were the primary providers of assessments. While patient-report measures were used for evaluation, the majority of assessments were clinical interviews. No significant differences were found between programs that treated adult and pediatric patients versus those only treating adult patients. Our findings highlight the lack of standard psychosocial practices for patients and family caregivers undergoing HSCT and we offer recommendations to fill this gap.

Psychosocial Assessment Practices for Hematopoietic Stem Cell Transplantation: A National Survey Study

Psychosocial health predicts and contributes to medical outcomes for patients undergoing hematopoietic stem cell transplantation (HSCT). Yet, there are no standards for psychosocial assessments or support for both patients and caregivers across the care continuum. To examine the current state of psychosocial care, clinicians were sent a survey of their psychosocial assessment practices for patients and caregivers undergoing HSCT via the Listservs of professional organizations. Descriptive statistics and bivariate analyses were performed to summarize the findings. While 96% of participants reported routine pre-HSCT psychosocial assessment of patients, only 10.6% routinely used a validated transplant risk-assessment measure. Just 27% routinely performed follow-up psychosocial assessments. In contrast, only 47% of participants routinely assessed the psychosocial needs of family caregivers pre-HSCT, and 13% routinely performed follow-up assessments for caregivers. Most (90%) reported social workers were the primary providers of assessments. While patient-report measures were used for evaluation, the majority of assessments were clinical interviews. No significant differences were found between programs that treated adult and pediatric patients versus those only treating adult patients. Our findings highlight the lack of standard psychosocial practices for patients and family caregivers undergoing HSCT and we offer recommendations to fill this gap.

Monitoring health as an opportunity to categorize preventative and early-treatment actions in a self-care journey: our experience with a Healthcare Magenta Scorecard

Background

Applying a digital health intervention to measure health and wellbeing status offers opportunities to guide and augment healthcare and promotion. In our scenario, we consider mainly digital-native patients and present an evaluation of a new Healthcare Magenta Scorecard towards this end.

Methods

Grounded in the six domains of health and promotion (physical activity; sleep quality; nutrition; habits/lifestyle; mental health; quality of life) we developed a health Magenta Scorecard (Magenta Score), a mobile based Electronic Patient Reported Outcomes (e-PRO) that measures patients health and wellbeing every 3-5 months. The Magenta Scorecard was derived from previously published evidence-based instruments. We collected data as patients were onboarded into our healthcare system (T0 and T1, time span between measurements, 141 days) and provided correlations among our domains of care.

Results

A total of 1,622 participants responded to T0 and T1 our Magenta Scorecard. Participants mean age was 31.3 [95% confidence interval (CI): 31.2-31.5] years and female (63.4%). Fifty-five percent (n=892) of our sample were categorized as relating to Health and Wellbeing promotion, 8.5% (n=138) disease management, 35.7% (n=579) self-care care support and only 0.8% (n=13) pertained to case management. From our care coordination guided approach, our Magenta Scorecards reported mean improvement across the study cohort of 26 ± standard deviation (SD) points, from T0 (649, 95% CI: 643-656) to T1 (675, 95% CI: 668-682). Our Magenta Scorecard domains had significant, albeit weak spearman correlations.

Conclusions

We demonstrated our Magenta Scorecard rationale and its guided approach. The Magenta Scorecard displayed adequate responsiveness and was significantly correlated across all of the domains investigated. Further prospective research is needed to validate our results in the long term.

Electronic patient-reported outcomes (e-PROMs) in palliative cancer care: a scoping review

BACKGROUND

In palliative oncology settings, electronic patient-reported outcome (PRO) assessment can play an important role in supporting clinical activities for clinicians and patients. This scoping review aims to map the technological innovation of electronic patient-reported outcome measures (e-PROMs) in cancer palliative care and how PRO data collected through e-PROMs can influence the monitoring and management of symptoms and enable better communication between health professionals and patients.

METHODS

A scoping review study was designed according to the Arksey and O'Malley framework. Medline, Embase, Web of Science, SCOPUS, PsycINFO and CINAHL and gray literature sources were consulted. The inclusion criteria were people over 18 years old receiving palliative and/or end-of-life care using e-PROMs.

RESULTS

Thirteen primary studies were included: nine quantitative studies, two qualitative studies, and two mixed-method studies. The recently developed software that supports e-PROMs allows patients to receive feedback on their symptoms, helps clinicians prioritize care needs and monitors patients' conditions as their symptoms change. Electronic PRO data prompt difficult, end-of-life communication between clinicians and patients to better organize care in the last phase of life.

CONCLUSION

This work shows that electronic PRO data assessment provides valuable tools for patients' well-being and the management of symptoms; only one study reported conflicting results. However, with studies lacking on how clinicians can use these tools to improve communication with patients, more research is needed.

Real-world implementation of an eHealth system based on an artificial intelligence designed to predict and reduce emergency department visits by older adults: pragmatic trial

Background

Frail older people use emergency services extensively, and digital systems that monitor health remotely could be useful in reducing these visits by earlier detection of worsening health conditions.

Objective

We aimed to implement a system that produces alerts when the machine learning algorithm identifies a short-term risk for an emergency department (ED) visit and examine health interventions delivered after these alerts and users’ experience. This study highlights the feasibility of the general system and its performance in reducing ED visits. It also evaluates the accuracy of alerts’ prediction.

Methods

An uncontrolled multicenter trial was conducted in community-dwelling older adults receiving assistance from home aides (HAs). We implemented an eHealth system that produces an alert for a high risk of ED visits. After each home visit, the HAs completed a questionnaire on participants’ functional status, using a smartphone app, and the information was processed in real time by a previously developed machine learning algorithm that identifies patients at risk of an ED visit within 14 days. In case of risk, the eHealth system alerted a coordinating nurse who could then inform the family carer and the patient’s nurses or general practitioner. The primary outcomes were the rate of ED visits and the number of deaths after alert-triggered health interventions (ATHIs) and users’ experience with the eHealth system; the secondary outcome was the accuracy of the eHealth system in predicting ED visits.

Results

We included 206 patients (mean age 85, SD 8 years; 161/206, 78% women) who received aid from 109 HAs, and the mean follow-up period was 10 months. The HAs monitored 2656 visits, which resulted in 405 alerts. Two ED visits were recorded following 131 alerts with an ATHI (2/131, 1.5%), whereas 36 ED visits were recorded following 274 alerts that did not result in an ATHI (36/274, 13.4%), corresponding to an odds ratio of 0.10 (95% IC 0.02-0.43; P<.001). Five patients died during the study. All had alerts, 4 did not have an ATHI and were hospitalized, and 1 had an ATHI (P=.04). In terms of overall usability, the digital system was easy to use for 90% (98/109) of HAs, and response time was acceptable for 89% (98/109) of them.

Conclusions

The eHealth system has been successfully implemented, was appreciated by users, and produced relevant alerts. ATHIs were associated with a lower rate of ED visits, suggesting that the eHealth system might be effective in lowering the number of ED visits in this population.

Trial Registration

clinicaltrials.gov NCT05221697; https://clinicaltrials.gov/ct2/show/NCT05221697.

Assessing a new pre-screening score for the simplified evaluation of the clinical quality and relevance of e-health applications. (Preprint)

Background

In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution.

Objective

We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions.

Methods

The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution’s targeted population size, the level of clinical assessment, and information about the provider.

Results

In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33).

Conclusions

This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.

Developing a Mobile Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events Administration System to Capture Postradiation Toxicity in Oncology: Usability and Feasibility Study

Background

Accurate self-reported symptomatic toxicity documentation via the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) is essential throughout cancer treatment to ensure safety and understand therapeutic efficacy. However, the capture of accurate toxicities from patients undergoing radiation therapy is challenging because this is generally provided only at the time of scheduled visits.

Objective

This study seeks to establish the usability and feasibility of a mobile PRO-CTCAE Administration System (mPROS) to capture toxicities related to radiation therapy.

Methods

English-speaking adult patients who were undergoing radiation therapy for cancer were enrolled and given a brief demonstration of the Say All Your Symptoms (SAYS) and Symptom Tracking Entry Program (STEP) interfaces of the mPROS app, followed by a patient-use phase where patient actions were observed as they navigated mPROS to enter toxicities. Patient feedback was captured via a semistructured interview and brief questionnaire.

Results

We enrolled 25 patients (age: mean 60.7 years; females: n=13, 52%; White patients: n=13; 52%; non-Hispanic patients: n=19, 76%; college graduates: n=17, 68%). Patients almost equally preferred the SAYS (n=14, 56%) or STEP (n=11, 44%) interfaces, with 21 patients (84%) agreeing that they would use mPROS to report their symptoms to their health care team and 19 patients (76%) agreeing that they would recommend mPROS to others.

Conclusions

The mPROS app is usable and feasible for facilitating the patient reporting of radiation therapy–related symptomatic toxicities. A revised version of mPROS that incorporates patient input and includes electronic health record integration is being developed and validated as part of a multicenter trial.

Strategies to Mitigate Chemotherapy and Radiation Toxicities That Affect Eating

Background: Cancer and its therapy is commonly associated with a variety of side effects that impact eating behaviors that reduce nutritional intake. This review will outline potential causes of chemotherapy and radiation damage as well as approaches for the amelioration of the side effects of cancer during therapy. Methods: Information for clinicians, patients, and their caregivers about toxicity mitigation including nausea reduction, damage to epithelial structures such as skin and mucosa, organ toxicity, and education is reviewed. Results: How to anticipate, reduce, and prevent some toxicities encountered during chemotherapy and radiation is detailed with the goal to improve eating behaviors. Strategies for health care professionals, caregivers, and patients to consider include (a) the reduction in nausea and vomiting, (b) decreasing damage to the mucosa, (c) avoiding a catabolic state and muscle wasting (sarcopenia), and (d) developing therapeutic alliances with patients, caregivers, and oncologists. Conclusions: Although the reduction of side effects involves anticipatory guidance and proactive team effort (e.g., forward observation, electronic interactions, patient reported outcomes), toxicity reduction can be satisfying for not only the patient, but everyone involved in cancer care.