Johnson & Johnson has announced a suite of digital tools designed for patients preparing to undergo or recovering from knee, hip, and weight loss surgery.
The Health Partner platform consists of three tools — a website, mobile app, and care portal — all of which are interconnected to provide patients adaptive education and surgery support. Along with offering providers a means to interact with their patients in real-time, the tools also match users with encouraging messages from patients who have been through their experiences.
While the platform is patient-facing, Johnson & Johnson will be distributing the Health Partner platform through providers. More specifically, the service will be offered as part of Johnson & Johnson Medical Devices Companies' CareAdvantage program.
“I think the combination of the agreed-upon care path, … the ability to bring up references to their peer groups, the ability to bring up short videos of others who have gone through this with encouraging messages — it really is a very rich experience for the patient,” Stuart McGuigan, VP and chief information officer at Johnson & Johnson, told MobiHealthNews. “It goes beyond the feeling of a clinical tool, but is something that is intended to delight the patient as they go along.”
McGuigan said that design of the platform came from multiple viewpoints existing within Johnson & Johnson’s substantial body of consumer- and medical-focused enterprises.
“What we discovered is if we bring those things together we can create, along with our technology, a tool to help patients through their journey,” he said. “So, the technology reflects all of that behavior science, all the deep clinical understanding, and all of our technical acumen to help patients prepare for and then recover from knee replacement, hip replacement, and bariatric surgery.
McGuigan described Health Partner as a “go-forward” platform, one which Johnson & Johnson intends to expand to new clinical areas including oncology, diabetes, and mental health. Further, the company hopes to refine the platform’s mechanics over time by improving its systems through machine learning. McGuigan’s examples of targeted refinements included the method in which users are individually categorized and assigned to peer resource groups, and the ways in which the platform predicts and adjusts around a patient’s recovery path.
“Those groups will continue to evolve as we apply advanced analytical methods to make sure we have the most useful clustering, in terms of helping to guide and predict outcomes," he said. "That’s part of the learning part of the application that’s more forward looking as we collect more and more data, we’ll be able to more and more particularize the peer group you belong to to one that is really most meaningful to you as a person, but also highly predictive of outcomes.”