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Aiming to Predict Recovery and Tailor Support for Spine Surgery Patients

Aiming to Predict Recovery and Tailor Support for Spine Surgery Patients

A Johns Hopkins team is using innovative methods to predict how patients will fare after surgery for spine degeneration and to tailor support for these patients during their recovery. Richard Skolasky, director of the Spine Outcomes Research Center at the Johns Hopkins University School of Medicine, aims to enable surgeons to predict, at three months postoperatively, how patients’ recovery trajectories may evolve throughout the first year. This information may then help surgeons tailor support for these patients.

To do this, Skolasky and his team first determined which aspects of recovery were most important to patients. They convened focus groups of spine patients and asked them about their health-related goals, which the researchers then mapped onto the validated PROMIS (Patient-Reported Outcomes Measurement Information System) health domains. They then used the data from PROMIS health assessments to develop a risk calculator to help predict a patient’s symptoms and functional limitations one year after surgery. These projections can guide physicians in setting realistic expectations with patients for what they will achieve in their recovery. 

With support from the orthopaedic spine division, and in collaboration with the Johns Hopkins Department of Physical Medicine and Rehabilitation, Skolasky’s group is beginning another aspect of this research—to develop a mobile application to track the recovery of spine patients by collecting real-life data. 

“The six to 12 weeks after surgery is such an important time for patients to resume their activities, like getting up and starting to walk, and for clinicians to ensure that infection doesn’t develop,” Skolasky says. “These ‘real-life’ measurements can be very valuable during this time.”

Skolasky says the application will enable two-way communication during those 12 weeks by prompting patients to do physical therapy exercises and sending clinicians real-time updates on pain and mood levels. “They like receiving reminders via phone, as opposed to paper instructions, which can get lost,” he says.

Additionally, the application will create individualized “rules” for each patient, so if their recovery deviates from what is expected, the application will alert the provider. For example, if a patient reports more limited mobility than expected, the information will be relayed to the clinician, who can address this issue in a follow-up appointment.

Another potential benefit is the immediacy of the mobile platform, which may increase reporting accuracy. “When the app asks about a patient’s pain, the patient reports how their pain is affecting their life, in their natural environment, versus reporting pain in a clinical setting after having traveled to their appointment,” Skolasky says.  

The risk calculator is currently in the validation stages, and Skolasky and his team hope to begin development of the app in late 2019.  

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