My previous blog installment described the opportunities with better analytics and patient experience. This blog will highlight artificial intelligence (AI), and all the opportunities it brings to the industry.
Despite the myriad of trend articles claiming a seismic change in healthcare as a result of AI applications, the reality of the impact we see is more deliberative. Most importantly, the impact of AI in healthcare is in value propositions, dependent on the other trends we have noted for their context and relevance.
There are two main areas where AI is impacting healthcare in meaningful ways.
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First, the opportunity for virtual agent solutions cannot be underestimated. Provider, payer and pharma entities alike— and every other industry—continue to evolve their options for engaging prospects and customers in the most effective way. AI-enabled assistants are either already in use in a limited form or on the roadmap for organizations industry wide. The challenge typically has become not how to validate the value proposition, but where to draw the line in the range of interaction points that can be exclusively directed or influenced by the virtual agent. In other words, determining where to hand back to human interaction. In general, that decision is more rooted in risk aversion that it is in the capabilities of the AI, assuming it is trained appropriately.
Secondly, and possibly more critically for the long term impact of AI, the role it plays in the integration story in Trend 3 cannot be overstated. Targeted machine learning solutions that focus on the interpretation of vast swathes of data are the domain of early iterations of AI—clearly with huge value in the fields of clinical discovery. But the more functional (and perhaps more tactical) application of AI in the intelligent automation of the many steps found in data pathways, data quality assessment, and ultimately integration, is critical to the success of personalization initiatives in both care coordination and care delivery.
These trends in artificial intelligence put a spotlight on the quality of existing data sources in healthcare. Whether it is data associated with building specifications to support wayfinding initiatives or process data points to describe a customer process to be AI-enabled, AI solutions can only be as good as the environment—specifically the data—they ingest at the outset. This becomes more complex as the range of digital health touchpoints for a health system expands.
Questions to Consider
- What are the realistic expectations you want to set for your patients in their virtual agent interactions with you? How effectively have you researched those expectations?
- What are the experiential dependencies or expectations you create by using virtual agents (e.g., “If it’s this easy to book an appointment, why do I have to call someone now that I need to get my insurance validated?”)
- How do you prioritize development paths for your AI-enabled interactions with patients or members?
To learn more about the top five digital health trends for providers, you can click here or download the guide below.