UNC Lineberger researchers are looking to use wearable technology to help bladder and colorectal cancer patients catch and address post-surgical symptoms and complications before they require more intensive medical care.
A team led by UNC Lineberger’s Lixin Song, PhD, RN, FAAN, received a seed grant award to launch a pilot study of using wearable technologies, such as the Fitbit and other devices, to monitor colon and bladder cancer patients for concerning symptoms and complications when they’re home after surgery.
“This is a showcase of the application of data science and how we can accelerate data science to serve a clinical purpose and improve patient outcomes, while reducing the provider and caregiver’s burden,” Song said.
Monitoring symptoms to prevent readmission
Surgery is a common treatment for colorectal cancer, the second leading cause of cancer death in the United States, according to the National Cancer Institute. It’s the third most common cancer. The median age of diagnosis is 67 years.
Surgery is also a part of the treatment plan for many patients with bladder cancer, which is the sixth most common cancer in the United States, according to the National Cancer Institute. The median age of diagnosis with bladder cancer is 73.
Researchers want to prevent unnecessary medical care for colon and bladder cancer patients, particularly after surgery for placement of an ostomy, which is a surgical opening that allows waste to pass through. Dehydration, infections or other symptoms and complications can lead patients to return to the hospital, Song said.
“We believe that most of these readmissions could be prevented to some extent by better monitoring and better patient and caregiver education,” she said.
Previous research led by UNC Lineberger researchers and published in the Journal of Clinical Oncology found national readmission rates were 30 percent 30 days after discharge from the hospital, and 43 percent at 90 days for patients undergoing bladder removal surgery.
Using wearable devices after surgery
In the study supported by the seed grant and led by Song, UNC Lineberger’s Matthew Nielsen, MD, MS, FACS, of the UNC Department of Urology and additional collaborators will gather vital statistics and data on patient symptoms and signs of complications, such as their heart rate, activities and weight change, from wearable devices. They will also use questionnaires to collect information directly from patients.
Through the effort, they want to triage patients based on the severity of their symptoms, and provide guidance and personalized feedback directly to patients.
Ultimately, they want to catch problems early and provide patients with resources to address problems so they can avoid unnecessary readmissions, use of the emergency room and other complications. They are also studying whether they can save time for nurses and other medical staff by using this technology.
“We are very excited to continue our longstanding collaborations with Dr. Song in this important new study,” Nielsen said. “Readmissions after complex cancer surgery reflect important unmet needs for our patients. We are hopeful that innovative approaches such as those proposed in this study will help us improve patient experience and outcomes.”
Overcoming the digital divide
UNC Lineberger is the only institution conducting the pilot study, and it is just the first step in a multi-part study. Researchers have received an additional grant — a $914,000, four-year grant from the National Institutes of Health — to launch the second phase of their study. This additional study will focus on the use of voice and movement monitoring to track patient symptoms automatically.
The grant, from the National Science Foundation Smart and Connected Health program, was awarded to Song and additional collaborators from the UNC-Chapel Hill Department of Computer Science.
Using technology that can automatically collect the data using wearable devices that take measurements from patients or using wireless technology to track patient movements, they also hope to overcome the “digital divide” for some patients, who have issues manually entering in computer data.
“What we want to do is use radio frequency signals that commonly exist in the environment, such as a home setting, that our system can pick up on – such as a sudden change in posture, a gesture, or a fall, to send an alert to the caregiver, or to the hospital if danger is detected,” Song said.