Artificial intelligence (AI) is poised to revolutionize healthcare operations, health research, the delivery of medical care and how patients are supported to maintain health. It is and will be a critical part of long—term healthcare solutions.
AI already is in numerous industry processes, apps and systems with which we interact daily, and healthcare is primed for AI expansion. It will not be used just to support making medical diagnoses and detecting disease. That is just the tip of the spear. The larger part of healthcare is more like other commercial sectors—logistics, administration, processes and customer relations. These are areas where AI has improved efficiency and cost. Healthcare costs remain under pressure to be lowered. They should be areas to start changing today with AI.
While value from AI is being achieved by applying it to healthcare operations, logistics, administrative process and to support customer engagement, AI application validation to enhance clinical care delivery can continue. There is promising work showing that AI is augmenting areas such as radiology and pathology interpretation. With increasing data and the coming reality of receiving patient data from multiple sources, AI also is needed to support data processing, visualization and decisions support. The application of AI through machine learning and natural language processing can bring special value across the current healthcare continuum to the creation of better outcomes. The use of these tools in healthcare will also support new models of value—based care and the increase of data—driven health personalization and transformation.
Success with AI involves new ways of thinking and working. AI must be leveraged to find ways to improve performance, and impact patient outcomes to include directly supporting and influencing the patient. With expanding data on patients, AI is critical to finding the right data, at the right time, and providing insights in actionable manners to patients, providers and administrators. The need for this increases as data volume and the need for value—based care expands. Why all the discussion about AI being a potential threat to jobs, and perhaps even the futures of individual healthcare businesses and services? Providers, in particular, should not be concerned about their jobs. They should be advocating for evidence—based use and implementation of AI in all aspects of healthcare operations across the continuum of care, and in support of patient engagements/activation. There are multiple use cases including compliance, coding, process flows and business operations that could be adopted today, which will not put lives or care at risk.
AI can begin to support other specific areas such as decision support and data processes, while continued research is used to establish outcome—focused, evidence—based practices for AI in diagnostic support; radiology, pathology, point of care, and with robotic surgeries, among other areas of healthcare service and support.
That’s a partial look at the state of artificial intelligence in healthcare today, and why the time is right for a new approach to AI that recognizes and incorporates its value, based upon evidence. In my next blog, I’ll be talking about some of the challenges providers face, and suggestions for how to navigate this evolving new world.