For many years, experts have been debating whether AI will help providers provide better care for their patients. AI is used to provide valuable insights into issues that impact the broader population, but it has not yet been effective in treating individual patients.
AI may soon become ubiquitous in point-of-care settings, providing data that can be used to inform decision making. This is possible by turning existing clinical guidelines into digital and automated process models that deliver the type of care that clinicians need.
Process model capabilities enable clinicians to plan how their patients should be cared for and provide recommendations on how best to deliver that care. Process models help clinicians plan their activities and decide on where to place them; AI provides clinical advisors who can tell them where to go to make decisions and what actions to take to help them have better outcomes.
Similarly, value-oriented care could become a real possibility. Since the 1990s, healthcare providers have been excited about the potential benefits of value-oriented care, but have struggled with how to measure the quality of care.
One advantage of using AI-based process models is that they resemble many of todays quality indicators. Process models do not only track the status of a patient, but they also leave a digital record of the care that was provided and what actions were taken. Each stage in that care trail can be measured based on current best practices and outcomes. By utilizing digital process models, healthcare organizations can determine how value-oriented care is delivered and how that value affects patient care plans.