Medicine X | Nokia
A global community of researchers, patients,
and technologists. Five teams challenged to
rethink how research is done.
In 2016, five teams from some of the world’s leading medical research institutes were selected to explore how digital health devices could shape the future of research. Each study was inspired by our Everyone Included™ research principles, which emphasize the role of patients and multidisciplinary care teams in study design.
The results were remarkable. The teams used NOKIA devices, including activity trackers, sleep monitors and smart scales, to investigate a range of clinical problems from heart failure management to opioid use post knee replacement. These new streams of behavioral data provided unique insights into a part of the patient journey that is often overlooked.
Read below about the five finalist teams and the winning study. This is the new era of Everyone Included research, empowered by the patient and by technology.
Physical activity, sleep and cognitive function
Technical University of Denmark
PI: Francois Patou, PhD
Background: An estimated 18.7% of the general population lives with Mild Cognitive Impairment (MCI), a syndrome characterized by a cognitive decline greater than expected for an individual of a given age and education level, but that does not notably interfere with activities of daily life. Around 38% of MCI cases develop into dementia within 5 years. For older adults, physical activity has been correlated with preserving cognitive functioning as well as promoting better sleep quality. Likewise, studies have shown that sleep disturbances promote cognitive decline and other neuropsychiatric features. Although these associations between physical activity, sleep quality, and cognitive functioning are widely acknowledged, the mechanisms leading to the observed patterns are yet to be determined.
Objective: Leverage Nokia digital health products pervasively night and day to observe associations between and among physical activity, sleep quality, and cognitive function.
Wearables for heart failure management
PI: Seth Martin, MD, MHS
Background: Over six million Americans are affected by heart failure (HF) and nearly one million new cases are diagnosed annually. Despite advances in care, mortality at five years is nearly 50%, surpassing many cancers. The cornerstone of HF management is close follow-up with providers, rapid medication titration to achieve optimal dosing guided by blood pressure (BP) and heart rate, and adherence to significant lifestyle changes. In patients with the most severe class of HF, limiting sodium and fluid intake and daily monitoring of weight become central aspects of symptom management. As the vast majority of management occurs at home, connected health has emerged as a technology that may enable patients to engage in more proactive disease self-management. However, there has not yet been a study that investigates its potential benefit in patients with HF.
Objective: To assess whether connected health technology improves engagement and lifestyle activation in the medically complex and resource intensive HF population.
Sleep quality in juvenile-onset psychosis
Boston Children’s Hospital
PI: Catherine Brownstein MPH, PhD
Background: Schizophrenia is a devastating mental disorder that affects 1% of the world’s population and often leads a deteriorating course with premature mortality. Sleep disturbances are often seen in schizophrenia patients, with 80% of hospitalized individuals with schizophrenia having some form of sleep disorder. The most commonly seen disorder is obstructive sleep apnea, which is a risk factor for sudden cardiac death in schizophrenia.
Boston Children’s Hospital (BCH) has amassed a cohort of children with very early onset psychosis (VEOP, defined as onset before age 13). As this rare but devastating condition is related to adult-onset schizophrenia, we hypothesized that sleep disorders are also occurring in this population. Severe patients often miss appointments due to inability to travel, so employing patient-reported data is ideal for those with this condition.
Objective: Aim 1 was to analyze sleep/wake cycles between children with very early onset psychosis for signs of a sleep disorder. Aim 2 was to investigate changes in sleep patterns due to parental awareness of problems highlighted by the Withings Aura. Correcting childhood sleep disorders in this vulnerable population may lead to improved outcomes later in life.
Using wearables in post-partum depression
PI: Simal Ozen Irmak
Background: One in nine new mothers experiences postpartum depression (PPD), a common and often under-diagnosed condition that hinders the health and wellbeing of the whole family and costs over $1 billion to society. Despite its high occurrence, little is known about the development of PPD; and even less is done in terms of prevention or timely diagnosis.
Objectives: We hypothesized that by monitoring personal health and wellness metrics, one can 1) predict and help the women at risk of developing PPD, 2) improve the postpartum experience of all new parents.
Trajectories in post operative pain
Washington University in St Louis
PI: Michael Bottros, MD
Background: The United States is in an “opioid epidemic” with substantial increases in opioid prescriptions, addiction rates, and overdose-related deaths. Significant, but often overlooked, contributors to this epidemic are prescribing patterns and postoperative opioid use. Patients may be discharged with large quantities of opioids on a “just-in-case” basis, possibly to increase patient satisfaction, because physician follow-up occurs 4 or more weeks postoperatively. This prescribing pattern may lead to large amounts of medication left unprotected at home, potentially facilitating continued use/misuse by patients, family members, or friends. Furthermore, surgeries are increasingly becoming outpatient or short-stay requiring a considerable amount of recovery at home with self-management; currently little is known about these recovery trajectories of individual patients. Advancements in digital health may allow for better understanding of the progression of patients’ recovery after discharge from surgery, leading to more rational analgesic prescribing and improved patient safety.
Objective: We hypothesize that opioids are overprescribed at hospital discharge and that high- resolution patient-generated data may provide clearer pictures of individual postoperative recovery trajectory and opioid need. In turn, we expect such information to enable individualized postoperative analgesic prescribing, improved patient safety, and prevention of excessive unused circulating opioid medications that could be diverted/misused.