- “COVID-19 Use Cases, Goals, Challenges, Impact” (here)
- “AI Use Cases & the COVID-19 Pandemic: Goals, Challenges and Impact” (here)
- “AI in Times of Crisis: How Industry AI Can Improve Patient Health Outcomes (here)
These pieces all begin to describe where AI is being leveraged to help with the current public health crisis. This post and the next couple (in short order) elaborate on what we at CognitiveScale call Intelligent Interventions - a set of AI use cases that cover Care Management, Service Experience, and more. These are AI use cases and solutions where we have experience with large health insurance companies (payers) and healthcare systems (providers).
AI-powered COVID-19 Healthcare solutions are based on an impressive array of models that provide community risk scores, spread predictions, near term hospital capacity, individual risk scores, contact tracing, and much more. As discussed in the previous works, there are challenges with delivering personalized, predictive, proactive, prescriptive and trusted solutions that leverage internal and external data and models - and deliver insights across the distributed network that is Healthcare.
Intelligent Interventions cover a range of these solutions, from targeted, personalized communications to a number of specific administrative and clinical interventions:
- Base-level Interventions = Communications Optimization. Your members’ / patients‘ community becomes a high risk zone - how do you reach them with targeted messaging: the right message to the right person at the right time via the right channel?
- Targeted, Personalized Interventions: Higher risk patients / members have needs that could put them at further risk, so how do you collect the requisite data and attach AI skills and models to help intervene better over an entire journey of care, for example? How do you help guide people to targeted resources, improve care with personalized attention, and ultimately drive optimized outcomes?
- People in certain locations can be guided to public health, provider or health plan resources
- A member with a pending prescription refill can be alerted to options like mail-order refills
- A patient in a care management program can get access to in-home options or smart devices that help keep them out of harm’s way
- Intervention Optimization: How do you track success, learn from actions, and improve interventions over time?
Example AI-powered Intelligent Intervention solutions include:
- Identification: Signals / triggers / event-driven insights for use with patients and members, in care management programs, or in support of location-based initiatives.
- Engagement: Hyper-personalized communications and interactions, such as:
- Service Intervention, e.g. notification of local resources
- Telemedicine Intervention
- News - Curated to Location, Needs, Preferences
- Personal Concierge: Across multiple delivery channels (apps, portals, chatbots), AI-powered insights can provide tools like individual risk scores, symptom checkers with care guidelines and public health resources, and provider search tools.
In subsequent posts I will touch on what we are doing to architect and operationalize Intelligent Intervention solutions - and how these solutions will support broader care management and service experience initiatives.
Jeffrey Eyestone is CognitiveScale’s Healthcare AI Advisor. In this role, Jeffrey works with Healthcare organizations - primarily health insurance companies, providers & healthcare systems, public health organizations, and technology vendors - across their AI roadmap. From strategic insight into how to develop AI competencies and centers of excellence to more tactical development of AI roadmaps and delivery of AI solutions, Jeffrey helps clients realize the value of AI across numerous healthcare AI use cases.