Artificial intelligence (AI) has continued to make major headlines as part of the life sciences industry’s trifecta of recent technology trends, and it’s not hard to see why.
Research published by MarketsandMarkets projected that the healthcare artificial intelligence market is expected to grow from $667.1 million in 2016 to more than $7.9 billion by 2022, a compound annual growth rate of 53 percent over the forecast period. This explains why companies such as IBM and Google are dominating advancements as they develop deep learning techniques that can revolutionize the way diseases are diagnosed, treated, and even prevented.
However, with AI’s success, comes its many challenges.
According to Niall Brennan, former chief data officer at Centers for Medicare and Medicaid Services (CMS), one of the key challenges related to whether or not artificial intelligence and machine learning gain traction is “translating it into something tangible that will resonate with payers and lead them to think about realigning financial incentives” to improve patient outcomes and reduce healthcare costs.
As healthcare organizations start to focus on consumer expectations in response to rising out-of-pocket costs and value-based reimbursements, providers will need to learn how to personalize the patient experience, reduce unnecessary expenditures, and maintain open lines of communication between office visits to keep patients as healthy as possible.
Such a paradigm shift in care delivery will rely heavily on data leveraged from direct and indirect sources to provide a more holistic view of an individual patient. This is why patient engagement, leveraged by Artificial Intelligence, is a viable solution that the healthcare industry needs, and deserves.
When it comes to patient engagement, the promise of AI is to improve the experience by anticipating patient needs, providing faster and more effective outcomes. To successfully optimize AI for patient engagement, life sciences companies should ensure that their strategy includes:
- Engaging patients with insights that are conversational and contextual, and adjusting based on the situation to respond in real time.
- Teaming providers with the intelligent guidance of AI so they can provide patients with next-best actions, personalized to them.
- Empowering patients who want to actively participate and engage in their health with intelligent guidance and support when needed.
AI can certainly play a role for life sciences companies looking to deliver on elevated customer expectations. But recognizing AI’s potential isn’t enough. To derive real value, life sciences companies must carefully examine how the technology will fit into their specific business processes, and how it will affect their patients’ lives overall.
However, AI is only one part of the equation. Those that want to stay relevant in their professions will need to focus on skills and capabilities that artificial intelligence has trouble replicating — understanding, motivating, and interacting with human beings. A smart machine might be able to diagnose an illness and even recommend treatment better than a doctor; however, it takes a person to sit with a patient, understand their life situation, and help determine which treatment plan is optimal.