Adaptation and Evaluation of a Symptom-Monitoring Digital Health Intervention for Patients With Relapsed and Refractory Multiple Myeloma: Pilot Mixed-Methods Implementation Study

The advantages, disadvantages, threats, and opportunities of electronic patient-reported outcome systems in cancer: A systematic review

Objective

Electronic patient-reported outcome (ePRO) systems hold promise for revolutionizing communication between cancer patients and healthcare providers across various care settings. This systematic review explores the multifaceted landscape of ePROs in cancer care, encompassing their advantages, disadvantages, potential risks, and opportunities for improvement.

Methods

In our systematic review, we conducted a rigorous search in Scopus, Web of Science, and PubMed, employing comprehensive medical subject heading terms for ePRO and cancer, with no date limitations up to 2024. Studies were critically appraised and thematically analyzed based on inclusion and exclusion criteria, including considerations of advantages, disadvantages, opportunities, and threats.

Findings

Analyzing 85 articles revealed 69 themes categorized into four key areas. Advantages (n = 14) were dominated by themes like "improved quality of life and care." Disadvantages (n = 26) included "limited access and technical issues." Security concerns and lack of technical skills were prominent threats (n = 10). Opportunities (n = 19) highlighted advancements in symptom management and potential solutions for technical challenges.

Conclusion

This review emphasizes the crucial role of continuous exploration, integration, and innovation in ePRO systems for optimizing patient outcomes in cancer care. Beyond traditional clinical settings, ePROs hold promise for applications in survivorship, palliative care, and remote monitoring. By addressing existing limitations and capitalizing on opportunities, ePROs can empower patients, enhance communication, and ultimately improve care delivery across the entire cancer care spectrum.

Assessing Patient-Reported Outcomes in Routine Cancer Clinical Care Using Electronic Administration and Telehealth Technologies: Realist Synthesis of Potential Mechanisms for Improving Health Outcomes

BACKGROUND

The routine measurement of patient-reported outcomes in cancer clinical care using electronic patient-reported outcome measures (ePROMs) is gaining momentum worldwide. However, a deep understanding of the mechanisms underpinning ePROM interventions that could inform their optimal design to improve health outcomes is needed.

OBJECTIVE

This study aims to identify the implicit mechanisms that underpin the effectiveness of ePROM interventions and develop program theories about how and when ePROM interventions improve health outcomes.

METHODS

A realist synthesis of the literature about ePROM interventions in cancer clinical care was performed. A conceptual framework of ePROM interventions was constructed to define the scope of the review and frame the initial program theories. Literature searches of Ovid MEDLINE, Ovid Embase, Scopus, and CINAHL, supplemented by citation tracking, were performed to identify relevant literature to develop, refine, and test program theories. Quality appraisal of relevant studies was performed using the Mixed Methods Appraisal Tool.

RESULTS

Overall, 61 studies were included in the realist synthesis: 15 (25%) mixed methods studies, 9 (15%) qualitative studies, 13 (21%) descriptive studies, 21 (34%) randomized controlled trials, and 3 (5%) quasi-experimental studies. In total, 3 initial program theories were developed regarding the salient components of ePROM interventions-remote self-reporting, real-time feedback to clinicians, and clinician-patient telecommunication. The refined theories posit that remote self-reporting enables patients to recognize and report symptoms accurately and empowers them to communicate these to clinicians, real-time feedback prompts clinicians to manage symptoms proactively, and clinician-patient telephone interactions and e-interactions between clinic encounters improve symptom management by reshaping how clinicians and patients communicate. However, the intervention may not achieve the intended benefit if ePROMs become a reminder to patients of their illness and are not meaningful to them and when real-time feedback to clinicians lacks relevance and increases the workload.

CONCLUSIONS

The key to improving health outcomes through ePROM interventions is enabling better symptom reporting and communication through remote symptom self-reporting, promoting proactive management of symptoms through real-time clinician feedback, and facilitating clinician-patient interactions. Patient engagement with self-reporting and clinician engagement in responding to feedback are vital and may reinforce each other in improving outcomes. Effective ePROM interventions might fundamentally alter how clinicians and patients interact between clinic encounters.

Implementation of electronic prospective surveillance models in cancer care: a scoping review

BACKGROUND

Electronic prospective surveillance models (ePSMs) for cancer rehabilitation include routine monitoring of the development of treatment toxicities and impairments via electronic patient-reported outcomes. Implementing ePSMs to address the knowledge-to-practice gap between the high incidence of impairments and low uptake of rehabilitation services is a top priority in cancer care.

METHODS

We conducted a scoping review to understand the state of the evidence concerning the implementation of ePSMs in oncology. Seven electronic databases were searched from inception to February 2021. All articles were screened and extracted by two independent reviewers. Data regarding the implementation strategies, outcomes, and determinants were extracted. The Expert Recommendations for Implementing Change taxonomy and the implementation outcomes taxonomy guided the synthesis of the implementation strategies and outcomes, respectively. The Consolidated Framework for Implementation Research guided the synthesis of determinants based on five domains (intervention characteristics, individual characteristics, inner setting, outer setting, and process).

RESULTS

Of the 5122 records identified, 46 interventions met inclusion criteria. The common implementation strategies employed were "conduct educational meetings," "distribute educational materials," "change record systems," and "intervene with patients to enhance uptake and adherence." Feasibility and acceptability were the prominent outcomes used to assess implementation. The complexity, relative advantage, design quality, and packaging were major implementation determinants at the intervention level. Knowledge was key at the individual level. At the inner setting level, major determinants were the implementation climate and readiness for implementation. At the outer setting level, meeting the needs of patients was the primary determinant. Engaging various stakeholders was key at the process level.

CONCLUSIONS

This review provides a comprehensive summary of what is known concerning the implementation of ePSMs. The results can inform future implementation and evaluation of ePSMs, including planning for key determinants, selecting implementation strategies, and considering outcomes alongside local contextual factors to guide the implementation process.

Association of patient activity bio-profiles with health-related quality of life in patients with newly diagnosed multiple myeloma: a prospective observational cohort study

BACKGROUND

Due to the nature of their disease, patients with multiple myeloma (MM) often have bone disease-related pain that limits physical activity and diminishes health-related quality of life (HRQOL). Digital health technology with wearables and electronic patient reported outcome (ePRO) tools can provide insights into MM HRQoL.

METHODS

In this prospective observational cohort study conducted at Memorial Sloan Kettering Cancer in NY, NY, USA, patients with newly diagnosed MM (n = 40) in two cohorts (Cohort A - patients <65 years; Cohort B - patients ≥65 years) were passively remote-monitored for physical activity at baseline and continuously for up to 6 cycles of induction therapy from Feb 20, 2017 to Sep 10, 2019. The primary endpoint of the study was to determine feasibility of continuous data capture, defined as 13 or more patients of each 20-patient cohort compliant with capturing data for ≥16 h of a 24-hr period in ≥60% of days of ≥4 induction cycles. Secondary aims explored activity trends with treatment and association to ePRO outcomes. Patients completed ePRO surveys (EORTC - QLQC30 and MY20) at baseline and after each cycle. Associations between physical activity measurements, QLQC30 and MY20 scores, and time from the start of treatment were estimated using a linear mixed model with a random intercept.

FINDINGS

Forty patients were enrolled onto study, and activity bioprofiles were compiled among 24/40 (60%) wearable user participants (wearing the device for at least one cycle). In an intention to treat feasibility analysis, 21/40 (53%) patients [12/20 (60%) Cohort A; 9/20 (45%) Cohort B] had continuous data capture. Among data captured, overall activity trended upward cycle over cycle for the entire study cohort (+179 steps/24 h per cycle; p = 0.0014, 95% CI: 68-289). Older patients (age ≥65 years) had higher increases in activity (+260 steps/24 h per cycle; p < 0.0001, 95% CI: -154 to 366) compared to younger patients (+116 steps/24 h per cycle; p = 0.21, 95% CI: -60 to 293). Activity trends associated with improvement of ePRO domains, including physical functioning scores (p < 0.0001), global health scores (p = 0.02), and declining disease burden symptom scores (p = 0.042).

INTERPRETATION

Our study demonstrates that feasibility of passive wearable monitoring is challenging in a newly diagnosed MM patient population due to patient use. However, overall continuous data capture monitoring remains high among willing user participants. As therapy is initiated, we show improving activity trends, mainly in older patients, and that activity bioprofiles correlate with traditional HRQOL measurements.

FUNDING

Grants -National Institutes of HealthP30 CA 008748, Awards - Kroll Award 2019.

Digital Health for Patients With Multiple Myeloma: An Unmet Need

Multiple myeloma (MM) is associated with the highest symptom burden and lowest health-related quality of life (HRQoL) among patients with hematologic malignancies. HRQoL in MM is heterogeneous, varying over the course of disease, with the highest burden at diagnosis and relapse. Patients with MM are increasingly being treated with oral maintenance medications at home. As a result, longitudinal monitoring of medication adherence and patient-reported outcomes, including HRQoL, could inform on disease status, therapeutic tolerability, and satisfaction with care. Digital health technologies, including telemedicine, mobile health, and wearable devices, are poised to become an integral part of modern health care, in part due to the surge in telemedicine necessitated by the COVID-19 pandemic. Although the literature has many reports on the use of digital health technologies in other types of cancers, fewer studies report on their application to MM. In the current narrative review, we survey the applications of digital health for MM. Although there is evidence that some are associated with improved health outcomes, challenges exist that must be met to ensure more widespread adoption. These include the need for increased awareness by patients and health care providers, lack of access by the typical older patient with MM, absence of randomized clinical trials, and low integration with current workflows such as electronic health records. Following our summary of technologies that could benefit patients with MM, we end by describing our vision for how they can be integrated into each phase of the patient journey.

Feasibility and Effectiveness of Assessing Subhealth Using a Mobile Health Management App (MibyeongBogam) in Early Middle-Aged Koreans: Randomized Controlled Trial

BACKGROUND

Mobile health (mHealth) is a major source of health management systems. Moreover, the demand for mHealth, which is in need of change due to the COVID-19 pandemic, is increasing worldwide. Accordingly, interest in health care in everyday life and the importance of mHealth are growing.

OBJECTIVE

We developed the MibyeongBogam (MBBG) app that evaluates the user's subhealth status via a smartphone and provides a health management method based on that user's subhealth status for use in everyday life. Subhealth is defined as a state in which the capacity to recover to a healthy state is diminished, but without the presence of clinical disease. The objective of this study was to compare the awareness and status of subhealth after the use of the MBBG app between intervention and control groups, and to evaluate the app's practicality.

METHODS

This study was a prospective, open-label, parallel group, randomized controlled trial. The study was conducted at two hospitals in Korea with 150 healthy people in their 30s and 40s, at a 1:1 allocation ratio. Participants visited the hospital three times as follows: preintervention, intermediate visit 6 weeks after the intervention, and final visit 12 weeks after the intervention. Key endpoints were measured at the first visit before the intervention and at 12 weeks after the intervention. The primary outcome was the awareness of subhealth, and the secondary outcomes were subhealth status, health-promoting behaviors, and motivation to engage in healthy behaviors.

RESULTS

The primary outcome, subhealth awareness, tended to slightly increase for both groups after the uncompensated intervention, but there was no significant difference in the score between the two groups (intervention group: mean 23.69, SD 0.25 vs control group: mean 23.1, SD 0.25; P=.09). In the case of secondary outcomes, only some variables of the subhealth status showed significant differences between the two groups after the intervention, and the intervention group showed an improvement in the total scores of subhealth (P=.03), sleep disturbance (P=.02), depression (P=.003), anger (P=.01), and anxiety symptoms (P=.009) compared with the control group.

CONCLUSIONS

In this study, the MBBG app showed potential for improving the health, especially with regard to sleep disturbance and depression, of individuals without particular health problems. However, the effects of the app on subhealth awareness and health-promoting behaviors were not clearly evaluated. Therefore, further studies to assess improvements in health after the use of personalized health management programs provided by the MBBG app are needed. The MBBG app may be useful for members of the general public, who are not diagnosed with a disease but are unable to lead an optimal daily life due to discomfort, to seek strategies that can improve their health.

TRIAL REGISTRATION

Clinical Research Information Service KCT0003488; https://cris.nih.go.kr/cris/search/search_result_st01.jsp?seq=14379.