Innovations in research and clinical care using patient‐generated health data

Abstract

Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and treatment histories, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, smartphones, and the Internet of Things have facilitated new ways to collect PGHD during clinic visits and in daily life. The goal of the current review was to provide an overview of the current clinical, regulatory, technological, and analytic landscape as it relates to PGHD in oncology research and care. The review begins with a rationale for PGHD as described by the US Food and Drug Administration, the Institute of Medicine, and other regulatory and scientific organizations. The evidence base for clinic-based and remote symptom monitoring using PGHD is described, with an emphasis on PROs. An overview is presented of current approaches to digital phenotyping or device-based, real-time assessment of biometric, behavioral, self-report, and performance data. Analytic opportunities regarding PGHD are envisioned in the context of big data and artificial intelligence in medicine. Finally, challenges and solutions for the integration of PGHD into clinical care are presented. The challenges include electronic medical record integration of PROs and biometric data, analysis of large and complex biometric data sets, and potential clinic workflow redesign. In addition, there is currently more limited evidence for the use of biometric data relative to PROs. Despite these challenges, the potential benefits of PGHD make them increasingly likely to be integrated into oncology research and clinical care.

Harnessing consumer smartphone and wearable sensors for clinical cancer research

“…Additional sensors such as Bluetooth scales or blood pressure monitors or beacons to estimate in-home location may provide additional data about health status, home environment, and activities of daily living 50 , 51 . Passive monitoring of diet or eating behaviors has proven challenging, although using smartphone cameras with machine learning algorithms to label foods and estimate portions may be less burdensome than manually entering foods 6 . Research is underway investigating wearable sensors to detect biomarkers in sweat 52 and ingestible sensors to monitor medication compliance 53 .…”

“…Mobile sensor data can complement snapshots of health gathered during clinic visits as well as other forms of patient-generated health data 6 such as patient-reported outcomes (PROs). Expanding use of PROs in clinical trials 7 reflects growing awareness that PROs may improve capture of treatment toxicities (compared to clinician ratings, which tend to underestimate symptom severity and frequency 8 ), helping patients make informed decisions and better prepare for what to expect during treatment.…”

Digital Phenotyping and Patient-Generated Health Data for Outcome Measurement in Surgical Care: A Scoping Review

“…Technology-enabled solutions that capture patient-generated health data (PGHD)—data related to activity, mobility, cognition, behavior, mood and social interactions—are rapidly evolving with the aim of a more personalized, patient-centered, and data-driven approach to the delivery of surgical care [ 1 , 2 , 3 , 4 , 5 ]. The concept of “digital phenotyping” was first coined in 2015 by J.P Onnela as the moment-by-moment quantification of individual human phenotypes in situ using data related to activity, behavior, and communications from personal digital devices, such as smartphones and wearable sensors (wearables) [ 6 , 7 , 8 , 9 , 10 ].…”

Living with Metastatic Cancer: A Roadmap for Future Research

“…To facilitate biopsychosocial screening protocols, cancer programs may consider leveraging the rapid technological advances of the past several decades, such as eHealth. eHealth is the use of information and communication technologies to facilitate care, and examples include online patient portals, telemedicine, and smartphone apps [ 140 , 141 ]. A recent trial underscores the potential benefits of using eHealth to routinely monitor patients’ side effects during cancer treatments; Basch and colleagues [ 142 ] randomized over 700 patients with advanced cancer undergoing chemotherapy to report on treatment side effects either on a weekly basis using tablet computers or at intervals determined by their providers.…”

“…As applied to the 3P Model, early detection of precipitating factors (i.e., side effects) using routine eHealth PRO monitoring led to early intervention, which may have buffered against the development of perpetuating factors and thus improved outcomes. Since this seminal study, multiple eHealth systems have been developed for monitoring PROs and other patient-generated data (e.g., from wearables) [ 140 , 141 , 145 ], and several cancer centers have integrated routine eHealth PRO monitoring into patient portals and electronic medical records to promote patient–provider communication, shared-decision making, and patient-centered care [ 146 , 147 , 148 ]. Importantly, eHealth offers the flexibility to tailor biopsychosocial screenings to individual patient and treatment-related characteristics (e.g., predisposing factors, precipitating factors such as disease characteristics and known side effects of treatment regimens), further promoting patient-centered care [ 137 ].…”