Big Data From Small Devices: The Future of Smartphones in Oncology

Automated, Real-Time Integration of Biometric Data From Wearable Devices With Electronic Medical Records: A Feasibility Study

PURPOSE

A major barrier to the incorporation of biometric data into clinical practice is the lack of device integration with electronic medical records (EMRs). We developed infrastructure to transmit biometric data from an Apple Watch into the EMR for physician review. The study objective was to test feasibility of using this infrastructure for patients undergoing radiotherapy.

METHODS

The study included patients with breast or prostate cancer receiving ≥3 weeks of radiotherapy who reported owning an Apple Watch. Daily resting heart rate (HR), HR variability, step count, and exercise minutes were automatically transferred to our EMR using a custom app installed on each patient's iPhone. Biometric data were presented to the treating radiation oncologist for review on a weekly basis during creation of the on-treatment note. Feasibility was defined a priori as physician review of biometric data for at least 90% of patients. Time trends in biometric data were tested using the Jonckheere-Terpstra test. Patient satisfaction was assessed using the System Usability Scale (SUS), with scores above 80 considered above-average user experience.

RESULTS

Of the 20 patients enrolled, biometric data were successfully transmitted to the EMR and reviewed by the radiation oncologist for 95% (n = 19) of patients, thus meeting the a priori feasibility threshold. For patients with radiation courses ≥4 weeks, exercise minutes decreased over time (P = .01) and daily mean HR variability increased over time (P = .02). The median SUS was 82.5 (IQR, 70-87.5).

CONCLUSION

Our study demonstrates the feasibility of real-time integration of biometric data collected from an Apple Watch into the EMR with subsequent physician review. The high rates of physician review and patient satisfaction provide support for further development of large-scale collection of wearable device data.

Daily physical activity monitoring in older adults with metastatic prostate cancer on active treatment: Feasibility and associations with toxicity

INTRODUCTION

Physical activity may be associated with cancer treatment toxicity, but generalizability to geriatric oncology is unclear. As many older adults have low levels of physical activity and technology use, this area needs further exploration. We evaluated the feasibility of daily step count monitoring and the association between step counts and treatment-emergent symptoms.

MATERIALS AND METHODS

Adults aged 65+ starting treatment (chemotherapy, enzalutamide/abiraterone, or radium-223) for metastatic prostate cancer were enrolled in a prospective cohort study. Participants reported step counts (measured via smartphone) and symptoms (Edmonton Symptom Assessment Scale) daily for one treatment cycle (i.e., 3-4 weeks). Embedded semi-structured interviews were performed upon completion of the study. The feasibility of daily monitoring was evaluated with descriptive statistics and thematic analysis. The predictive validity of a decline in daily steps (compared to pre-treatment baseline) for the emergence of symptoms was examined using sensitivity and positive predictive value (PPV). Associations between a 15% decline in steps and the emergence of moderate (4-6/10) to severe (7-10/10) symptoms and pain in the next 24 h were assessed using logistic regression.

RESULTS

Of 90 participants, 47 engaged in step count monitoring (median age = 75, range = 65-88; 52.2% participation rate). Daily physical activity monitoring was found to be feasible (94% retention rate; 90.5% median response rate) with multiple patient-reported benefits including increased self-awareness and motivation to engage in physical activity. During the first treatment cycle, instances of a 15% decline in steps were common (n = 37, 78.7%), as was the emergence of moderate to severe symptoms overall (n = 40, 85.1%) and pain (n = 26, 55.3%). The predictive validity of a 15% decline in steps on the emergence of moderate to severe symptoms was good (sensitivity = 81.8%, 95% confidence interval [CI] = 68.7-95.0; PPV = 73.0%, 95% CI = 58.7-87.3), although the PPV for pain was poor (sensitivity = 77.8%, 95% CI = 58.6-97.0; PPV = 37.8%, 95% CI = 22.2-53.5). In the regression models, changes in daily physical activity were not associated with symptoms or pain.

DISCUSSION

Changes in physical activity had modest ability to predict moderate to severe symptoms overall. Although participation was suboptimal, daily activity monitoring in older adults with cancer appears feasible and may have other uses such as improving physical activity levels. Further studies are warranted.

Predictors of Financial Toxicity in Patients Receiving Concurrent Radiation Therapy and Chemotherapy

Purpose

Financial toxicity (FT) is a significant concern for patients with cancer. We reviewed prospectively collected data to explore associations with FT among patients undergoing concurrent, definitive chemoradiation therapy (CRT) within a diverse, urban, academic radiation oncology department.

Methods and Materials

Patients received CRT in 1 of 3 prospective trials. FT was evaluated before CRT (baseline) and then weekly using the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire Core-30 questionnaire. Patients were classified as experiencing FT if they answered ≥2 on a Likert scale question (1-4 points) asking if they experienced FT. Rate of change of FT was calculated using linear regression; worsening FT was defined as increase ≥1 point per month. χ², t tests, and logistic regression were used to assess predictors of FT.

Results

Among 233 patients, patients attended an average of 9 outpatient and 4 radiology appointments over the 47 days between diagnosis and starting CRT. At baseline, 52% of patients reported experiencing FT. Advanced T stage (odds ratio, 2.47; P = .002) was associated with baseline FT in multivariate analysis. The mean rate of FT change was 0.23 Likert scale points per month. In total, 26% of patients demonstrated worsening FT during CRT. FT at baseline was not associated with worsening FT (P = .98). Hospitalization during treatment was associated with worsening FT (odds ratio, 2.30; P = .019) in multivariate analysis.

Conclusions

Most patients reported FT before CRT. These results suggest that FT should be assessed (and, potentially, addressed) before starting definitive treatment because it develops early in a patient's cancer journey. Reducing hospitalizations may mitigate worsening FT. Further research is warranted to design interventions to reduce FT and avoid hospitalizations.

"I Beat Cancer to Feel Sick:" Qualitative Experiences of Sleep Disturbance in Black Breast Cancer Survivors and Recommendations for Culturally Targeted Sleep Interventions

BACKGROUND

Sleep disturbance is common and distressing among cancer survivors. Black breast cancer survivors (BBCS) suffer disproportionately from sleep disturbance, yet there is limited research on how to address this issue.

PURPOSE

This study aimed to understand the multifaceted experiences of sleep disturbance among BBCS and how to culturally target a mobile health (mHealth) intervention to improve sleep outcomes in BBCS.

METHODS

Semi-structured interviews were conducted in a purposive sample of 10 BBCS. Interviews were audio-recorded, transcribed, and coded for key barriers to sleep and potential solutions to incorporate into behavioral interventions using NVivo 12. Inductive applied thematic analysis techniques were employed to identify emergent themes.

RESULTS

Ten BBCS (mean age = 54, SD = 10) described their experiences of sleep disturbance with themes including: (1) barriers to quality sleep (e.g., cancer worry, personal responsibilities), (2) psychosocial impacts of sleep disturbance (e.g., fatigue, distress), and (3) commonly used strategies to improve sleep. The second section discusses suggestions for developing mHealth interventions to improve sleep for BBCS including: (1) feedback on an existing mHealth intervention and (2) intervention topics suggested by BBCS.

CONCLUSIONS

Our findings highlight the challenges associated with sleep disturbance in BBCS. Participants report culturally targeted mHealth interventions are needed for BBCS who experience chronic sleep disturbance that affects their overall quality of life. These interventions should address coping with sleep-related issues relevant to many breast cancer survivors and BBCS (e.g., sexual intimacy, fear of cancer recurrence) and should incorporate intervention strategies acceptable to BBCS (e.g., prayer, meditation).

The AIMS home-video method: parental experiences and appraisal for use in neonatal follow-up clinics

Background

In The Netherlands, prematurely born infants and their parents are offered regular developmental check-ups in a hospital setting. In line with providing healthcare at distance, the use of video footage showing the infant’s behavior and movements, taken by parents at home and assessed by professionals online, might be a fruitful future practice. The focus of this study was to gain insight into parental experiences with the Alberta Infant Motor Scale home-video method and their appraisal of its applicability for use in an outpatient neonatal follow-up clinic.

Method

A qualitative descriptive study among parents of healthy extremely or very premature infants (GA 26.2–31.5 weeks) participating in a longitudinal study of motor development between 3–18 months corrected age. Ten semi-structured interviews were conducted and transcribed verbatim. Data was analyzed independently. Inductive content analysis was performed following the process of the AIMS home-video method.

Results

Parents appraised the AIMS home-video method as manageable and fun to do. Instructions, instruction film, and checklists were clear. Transferring the video footage from their phone to their computer and uploading it to the web portal was sometimes time-consuming. Parents gained a better awareness of their infant’s motor development and found the provided feedback a confirmation of what they already thought about their infant’s development and was reassuring that their child was doing well. First-time parents seemed more uncertain and had a greater need for information about (motor) development, but on the other hand, also had confidence in their child.

All parents thought that home-videos can be an addition to follow-up visits, but cannot replace (all) visits. It may be an opportunity to reduce the frequency of hospital visits, while still having their infant monitored.

Conclusion

Parents appraised the AIMS home-video method positively and are of the opinion that home-videos can be of added value in monitoring infants at risk in neonatal follow-up additional to hospital visits. In future research a user-friendly application and/or platform to exchange video footage safely between parents and professionals should be developed with all possible stakeholders involved and implementation should be explored.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03398-9.

Lack of Acceptance of Digital Healthcare in the Medical Market: Addressing Old Problems Raised by Various Clinical Professionals and Developing Possible Solutions

Various digital healthcare devices and apps, such as blood glucose meters, blood pressure monitors, and step-trackers are commonly used by patients; however, digital healthcare devices have not been widely accepted in the medical market as of yet. Despite the various legal and privacy issues involved in their use, the main reason for its poor acceptance is that users do not use such devices voluntarily and continuously. Digital healthcare devices generally do not provide valuable information to users except for tracking self-checked glucose or walking. To increase the use of these devices, users must first understand the health data produced in the context of their personal health, and the devices must be easy to use and integrated into everyday life. Thus, users need to know how to manage their own data. Medical staff must teach and encourage users to analyze and manage their patient-generated healthcare data, and users should be able to find medical values from these digital devices. Eventually, a single customized service that can comprehensively analyze various medical data to provide valuable customized services to users, and which can be linked to various heterogeneous digital healthcare devices based on the integration of various health data should be developed. Digital healthcare professionals should have detailed knowledge about a variety of digital healthcare devices and fully understand the advantages and disadvantages of digital healthcare to help patients understand and embrace the use of such devices.

Deep neural networks for COVID-19 detection and diagnosis using images and acoustic-based techniques: a recent review

The new coronavirus disease (COVID-19) has been declared a pandemic since March 2020 by the World Health Organization. It consists of an emerging viral infection with respiratory tropism that could develop atypical pneumonia. Experts emphasize the importance of early detection of those who have the COVID-19 virus. In this way, patients will be isolated from other people and the spread of the virus can be prevented. For this reason, it has become an area of interest to develop early diagnosis and detection methods to ensure a rapid treatment process and prevent the virus from spreading. Since the standard testing system is time-consuming and not available for everyone, alternative early screening techniques have become an urgent need. In this study, the approaches used in the detection of COVID-19 based on deep learning (DL) algorithms, which have been popular in recent years, have been comprehensively discussed. The advantages and disadvantages of different approaches used in literature are examined in detail. We further present the databases and major future challenges of DL-based COVID-19 detection. The computed tomography of the chest and X-ray images gives a rich representation of the patient's lung that is less time-consuming and allows an efficient viral pneumonia detection using the DL algorithms. The first step is the preprocessing of these images to remove noise. Next, deep features are extracted using multiple types of deep models (pretrained models, generative models, generic neural networks, etc.). Finally, the classification is performed using the obtained features to decide whether the patient is infected by coronavirus or it is another lung disease. In this study, we also give a brief review of the latest applications of cough analysis to early screen the COVID-19 and human mobility estimation to limit its spread.

The validity of mobile applications to facilitate patient care provided to cancer patients: opportunities and limitations

BACKGROUND

The use of health-related applications (apps) on smartphones has become widespread. This is especially of value during the ongoing SAR-COV-2 pandemic, where the accessibility for health care services has been greatly limited. Patients with free access to apps can obtain information to improve their understanding and management of health issues. Currently, there are cancer-related apps available on iPhones and androids. However, there are no guidelines to control these apps and ensure their quality. Furthermore, these apps may significantly modify the patients' perception and knowledge toward drug-related health services.

OBJECTIVE

The aim of this study was to assess the convenience, quality, safety and efficacy of apps for cancer patient care.

METHODS

The study was conducted by searching all apps related to cancer care on both Google Play Store and Apple iTunes Store. A detailed assessment was then performed using the mobile application rating scale (MARS) and risk assessment tools.

RESULTS

The results indicated that on a scale from 1-5, 47% of the apps were rated ≥ 4. The MARS assessment of the apps indicated an overall quality rating of 3.38 ± 0.9 (mean ± SD). The visual appeal of the app was found to have a significant effect on app functionality and user engagement. The potential benefits of these apps come with challenges and limitations. Patents related to smartphone applications targeting patients were also discussed.

CONCLUSION

We recommend a greater emphasis toward producing evidence-based apps. These apps should be rigorously tested, evaluated and updated by experts, particularly clinical pharmacists. Also, these may alter patient attitudes toward services provided by physicians and pharmacists. Finally, these apps should not replace in-person interactive health services.

Lifestyle and Empowerment Techniques in Survivorship of Gynaecologic Oncology (LETSGO study): a study protocol for a multicentre longitudinal interventional study using mobile health technology and biobanking

INTRODUCTION

The number of gynaecological cancer survivors is increasing and there is a need for a more sustainable model of follow-up care. Today's follow-up model is time-consuming and patients have reported unmet needs regarding information about their cancer and strategies for managing the consequences of treatment. The main aim of this study is to assess health-related empowerment-in terms of patient education, psychosocial support, and promotion of physical activity-in a new follow-up model by comparing it to standard follow-up in a quasi-randomised study involving intervention hospitals and control hospitals.

METHODS AND ANALYSIS

At the intervention hospitals, patients will be stratified by risk of recurrence and late effects to either 1 or 3 years' follow-up. Nurses will replace doctors in half of the follow-up visits and focus in particular on patient education, self-management and physical activity. They will provide patients with information and guide them in goal setting and action planning. These measures will be reinforced by a smartphone application for monitoring symptoms and promoting physical activity. At the control hospitals, patients will be included in the standard follow-up programme. All patients will be asked to complete questionnaires at baseline and after 3, 6, 12, 24 and 36 months. Blood samples will be collected for biobanking at 3, 12 and 36 months. The primary outcome is health-related empowerment. Secondary outcomes include health-related quality of life, adherence to physical activity recommendations, time to recurrence, healthcare costs and changes in biomarkers. Changes in these outcomes will be analysed using generalised linear mixed models for repeated measures. Type of hospital (intervention or control), time (measurement point), and possible confounders will be included as fixed factors.

ETHICS AND DISSEMINATION

The study is approved by the Regional Committee for Medical Research Ethics (2019/11093). Dissemination of findings will occur at the local, national and international levels.

TRIAL REGISTRATION NUMBER

NCT04122235.

Evaluation of a Remote Symptom Assessment and Management (SAM) System for People Receiving Adjuvant Chemotherapy for Breast or Colorectal Cancer: Mixed Methods Study

Background

The Symptom Assessment and Management (SAM) program is a structured, online, nurse-supported intervention to support symptom self-management in people receiving adjuvant chemotherapy post surgery for breast or colorectal cancer.

Objective

The objective of this study was to describe the development, implementation strategy, and evaluation of the SAM system.

Methods

The development of the SAM program involved 3 phases. In phase 1, the web app was developed through consultation with consumers and clinicians and of the literature to ensure that the system was evidence-based and reflected the realities of receiving treatment and supporting patients through treatment. In phase 2, 7 participants recorded the severity of 6 symptoms daily over the course of 1 cycle of chemotherapy. In phase 3, 17 participants recorded their symptoms daily over the course of 3 cycles of chemotherapy. Once symptoms were recorded, participants received immediate feedback on the severity of their symptoms and self-management recommendations, which could include seeking immediate medical attention. Data on quality of life, symptom burden, anxiety and depression, distress, and self-efficacy were collected during treatment; participants’ perceptions of the SAM program were evaluated following participation via interview.

Results

The outcomes of the SAM project include the development of a system that is reliable and easy to use and navigate. Participants reported benefits related to using the SAM program that included feeling more in control of managing their symptoms and feeling reassured. Engagement with the system on a daily basis was variable, with some participants completing the symptom tracker daily and others engaging some of the time. The feedback from all participants was that the system was easy to navigate and the information was relevant and supportive.

Conclusions

The SAM program has the potential to enhance the management of symptoms for people receiving chemotherapy treatment. The system creates an accurate repository of symptoms that can be accessed easily and highlight patterns in symptom experience. These can be shared with clinicians, with patient permission, to inform and support treatment plans. The potential to predict the risk of developing severe symptoms can be developed to anticipate the need for care and support. Further considerations on how to increase engagement with the system, the value of the system for people diagnosed with other tumor types and treatment regimes, and the incorporation of the system into everyday clinical practice are needed.

Accuracy of Mobile Applications versus Wearable Devices in Long-Term Step Measurements

Fitness sensors and health systems are paving the way toward improving the quality of medical care by exploiting the benefits of new technology. For example, the great amount of patient-generated health data available today gives new opportunities to measure life parameters in real time and create a revolution in communication for professionals and patients. In this work, we concentrated on the basic parameter typically measured by fitness applications and devices-the number of steps taken daily. In particular, the main goal of this study was to compare the accuracy and precision of smartphone applications versus those of wearable devices to give users an idea about what can be expected regarding the relative difference in measurements achieved using different system typologies. In particular, the data obtained showed a difference of approximately 30%, proving that smartphone applications provide inaccurate measurements in long-term analysis, while wearable devices are precise and accurate. Accordingly, we challenge the reliability of previous studies reporting data collected with phone-based applications, and besides discussing the current limitations, we support the use of wearable devices for mHealth.

Harnessing consumer smartphone and wearable sensors for clinical cancer research

As smartphones and consumer wearable devices become more ubiquitous, there is a growing opportunity to capture rich mobile sensor data continuously, passively, and in real-world settings with minimal burden. In the context of cancer, changes in these passively sensed digital biomarkers may reflect meaningful variation in functional status, symptom burden, quality of life, and risk for adverse clinical outcomes. These data could enable real-time remote monitoring of patients between clinical encounters and more proactive, comprehensive, and personalized care. Over the past few years, small studies across a variety of cancer populations support the feasibility and potential clinical value of mobile sensors in oncology. Barriers to implementing mobile sensing in clinical oncology care include the challenges of managing and making sense of continuous sensor data, patient engagement issues, difficulty integrating sensor data into existing electronic health systems and clinical workflows, and ethical and privacy concerns. Multidisciplinary collaboration is needed to develop mobile sensing frameworks that overcome these barriers and that can be implemented at large-scale for remote monitoring of deteriorating health during or after cancer treatment or for promotion and tailoring of lifestyle or symptom management interventions. Leveraging digital technology has the potential to enrich scientific understanding of how cancer and its treatment affect patient lives, to use this understanding to offer more timely and personalized support to patients, and to improve clinical oncology outcomes.

Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning

In this review, we aim to assess the current state of science in relation to the integration of patient-generated health data (PGHD) and patient-reported outcomes (PROs) into routine clinical care with a focus on surgical oncology populations. We will also describe the critical role of artificial intelligence and machine-learning methodology in the efficient translation of PGHD, PROs, and traditional outcome measures into meaningful patient care models.

Use of patient-generated health data across healthcare settings: implications for health systems

Objective

The growing prevalence of chronic conditions requiring changes in lifestyle and at-home self-management has increased interest in and need for supplementing clinic visits with data generated by patients outside the clinic. Patient-generated health data (PGHD) support the ability to diagnose and manage chronic conditions, to improve health outcomes, and have the potential to facilitate more “connected health” between patients and their care teams; however, health systems have been slow to adopt PGHD use in clinical care.

Materials and Methods

We surveyed current and potential users of PGHD to catalog how PGHD is integrated into clinical care at an academic health center. The survey included questions about data type, method of collection, and clinical uses of PGHD. Current users were asked to provide detailed case studies of PGHD use in research and care delivery.

Results

Thirty-one respondents completed the survey. Seventeen individuals contributed detailed case studies of PGHD use across diverse areas of care, including behavioral health, metabolic and gastrointestinal conditions, musculoskeletal/progressive functional conditions, cognitive symptoms, and pain management. Sensor devices and mobile technologies were the most commonly reported platforms for collection. Clinicians and researchers involved in PGHD use cited the potential for PGHD to enhance care delivery and outcomes, but also indicated substantial barriers to more widespread PGHD adoption across healthcare systems.

Conclusion

The results of our survey illustrate how PGHD is used in targeted areas of one healthcare system and provide meaningful insights that can guide health systems in supporting the widespread use of PGHD in care delivery.