Value-based Healthcare: Three Ways Healthcare Systems Can Get More Usage Out of Their Patient Engagement Tools

What should healthcare systems do once patient data are collected? The rapid expansion of artificial intelligence technologies including machine/deep learning offers opportunities to combine data from PRO measures with structured and unstructured demographic-, clinical-, and process-level data to enhance decision making at the point of care [⁶]. At our institution, PROs captured prior to consultations with patients considering total knee replacement surgery are used in an artificial intelligence–enabled patient decision aid to provide personalized predictions of health outcomes.

Patients may also benefit from tools that offer more passive interactions, including those that allow them to engage outside the healthcare setting and in their usual environments. Digital phenotyping, defined as the moment-by-moment capture of an individual’s activity using data from smartphones or wearable sensors, is one such approach that allows passive capture of continuous patient-generated activity, behavior, and communications data as biomarkers of health [⁴]. Investigators, including those at the University of California San Francisco, are using wearable sensors and mobile applications as tools for assessing functional outcomes and assessing physical performance prior to and following total knee replacement [¹]. Natural language processing of open unstructured video, audio, and free text might also offer new technology-enabled opportunities to minimize the burden on patients and improve their experiences using less obtrusive patient engagement tools.

Ultimately, a three-phased approach is necessary for successful integration and use of patient engagement tools in orthopaedics: (1) defining functional needs along the care pathway, (2) creating meaningful experiences for patients and teams, and (3) leveraging data for patient engagement tools using technology as strategies for driving high-value musculoskeletal care.