A P R I L 2 0 1 6 O U T P A T I E N TS U R G E R Y. N E T 7
healthcare delivery model. For example,
most current patient models are based on
intermittent data and feedback loops that
largely fall apart when patients are dis-
charged to home. But it's data that's needed
in order to react to and manage a patient's changing condition. We live in an
emerging world of the quantified self,
which involves individuals using wear-
able and other types of sensors to measure many aspects of their physiological
state. Tapping into many of these technologies will let us monitor patients out-
side of the traditional clinical environment and provide numerous new ways to
collect data remotely as they recover from surgery. Today it's possible to give
joint replacement patients consumer wearable sensors that can track the
amount of steps they take in a day or even the range of motion in the recently
replaced joint. That data could soon flow back into electronic medical records
and care platforms, giving caregivers real-time snapshots of how recoveries are
progressing.
You'd be able discharge patients after same-day surgery and have confidence in
the smarter means available to track and interact with them in the digital dimen-
sion, which can provide often continuous data so patient care is proactive instead
of reactive.
Integrating a digital layer during pre-op and post-op interactions with patients
and their families will enhance the continuum of care, and will be increasingly
incentivized as healthcare systems transition from a fee-for-service reimburse-
ment model to value-based care.
Looking ahead
Collecting, mining and applying machine-learning to the tsunami of Big Data more
effectively will allow for predictalytics — recognizing performance patterns in stats
that can be used to improve workflow, enhance clinical outcomes and prevent
Technology is disrupting
the old way of doing things
to create a new and better
healthcare delivery model.
