The post-acute world is becoming fundamental to a hospital’s success in creating a patient-centered, longitudinal network of care. Like the rest of the industry, these organizations are under scrutiny to drive quality outcomes. And in a changing competitive landscape, Skilled Nursing Facilities, Home Health, Assisted Living and Long Term Care organizations are looking for ways to differentiate themselves, drive better care, and reduce the number of adverse events within their patient populations.
During this session, we will examine the roll that predictive, artificial intelligence (AI) driven solutions play in driving market differentiation and care quality for post-acute providers. We will examine the predictive use cases that best support quality goals and how AI applications can drive better investment and operational decisions to enable greater market share. We will also discuss the challenges with predictive analytic adoption within a market that is lagging in HIT adoption.
List the major changes that are impacting the post-acute provider segment including increased competition, mandates, payment models, consumer expectations, and clinical integration
Discuss the key ways in which predictive analytics can drive value for post-acute providers in terms of competitive advantage, market differentiation, increased volume, and decreased losses
Summarize the points along the post-acute care continuum where predictive analytics are most relevant and effective