AI-Enabled IoT — Implications for Healthcare Providers

Healthcare providers are at the dawn of a new AI-driven era enabled by data from IoT and other digital sources. Product leaders of healthcare provider IoT applications should exploit this opportunity for AI-enabled IoT to create new value propositions leading to new revenue streams.

Overview

Key Findings

• Healthcare providers’ low data latency requirements for clinical purposes are shifting attention to edge compute, Internet of Things (IoT) architecture along with edge artificial intelligence (AI) techniques.
• Cloud-out and edge-in architectures can exploit AI-enabled IoT opportunities to balance the requirements of horizontal scalability and healthcare specialization.
• Camera-based IoT applications offer the greatest edge-AI-enabled, IoT opportunity based on the number of possible use cases to deliver healthcare value in the next three years.

Recommendations

Product leaders undertaking healthcare-focused industry product planning and strategy activities for IoT applications should:

• Design solutions to actively participate in the larger ecosystem of devices and application stacks in the production environment by implementing open APIs, where possible, for data collection, transmission and storage.
• Differentiate their product and company by embracing and adopting industry standards, and participating in relevant healthcare standards workgroups or committees.
• Assist their healthcare provider customers in operationalizing these new technologies by offering support services geared for the specific clinical or operational workflows in which their products operate.

Analysis

When healthcare users envision the value of IoT within their environment, they typically think about the improved outcomes of decisions made with more contextually aware inputs — not the devices themselves. These improved outcomes are driven by the analysis of data collected from IoT. That analysis (AI-enabled) is fundamental to the requirements for smart-connected products and smart-connected operations in the healthcare delivery environment. These AI-enabled IoT solutions and products cooperate with intricate workflows, participating in a sophisticated multivendor environment to deliver care and drive organizational efficiencies.

Implications of AI-Enabled IoT for Product Leaders Targeting the Healthcare Provider Industry

• AI-enabled IoT in the healthcare provider industry supports delivery of the quadruple aim. All four objectives can be enhanced, enabled or improved through the accurate collection and analysis of healthcare environmental data:
• Improving the health of the population served — Direct use of AI to improve medical device capabilities
• Increase patient engagement with their health — The consumerization of AI-enabled wearables targeted at health and wellness
• Improve caregiver engagement with their patients and healthcare environment — Use smart IoT to help make the job of delivering care to patients easier
• Help to make healthcare affordable for patients — Use AI-enabled IoT to find and take advantage of efficiency and cost optimization opportunities in all aspects of healthcare delivery organization (HDO) operations
• AI can enhance IoT by adding analytic capabilities to edge devices, such as cameras. Computer vision-enhanced cameras analyze captured images in real time, performing functions such as fall detection, facial recognition of caregivers and patients and identification of medical device assets in the patient room. The ubiquity of cameras in the care delivery environment provides an opportunity for product leaders to gain traction in this market space, as most hospital systems have installed populations of security cameras that could be utilized for this purpose.
• Currently, AI-enabled IoT impacts healthcare where accurate tactical information is required to drive precise real-time decisions; this includes medical devices in critical care venues such as ICUs. Adding an intelligence layer to devices collecting vital data from critically ill patients can reduce caregiver fatigue and improve response time when health events occur.
• The added AI functional capabilities create an opportunity for HDO buyers to view IoT devices in a new light — where some of the human workload associated with introducing a new device in the workspace can be reduced or removed through AI. When implemented with this benefit in mind, this game-changing class of IoT can reduce the amount of toil for nursing and other clinical support staff — allowing them to serve more patients with better clinical results.
• AI-enabled IoT can help overcome industry challenges through added real-time, situational awareness:
• Power shifting to the consumer — Consumers, increasingly, have the opportunity, the incentives and the means to assert their will on their healthcare experiences.
• Evolving expectations of value delivery — Value-based care (VBC) is a global trend that addresses escalating costs and disparities in care.
• Regulatory uncertainty — Healthcare has always been highly regulated. Every year, new rules and operating protocols increase in number, breadth and depth.
• Industry structure transformation — Executive leaders are reevaluating their organizations’ value propositions and competitive positioning to establish sustainable business and operating models.
• Health cost conundrum — Healthcare cost is a multidimensional problem requiring complex cross-industry ecosystem partner alignment and collaboration to address. The demand for and cost of healthcare services continues to grow inexorably.
• Medical innovations in therapy, diagnosis and care delivery — Rapid innovation and new therapeutic and care delivery models are driving the global healthcare and life science industry with broad technology and resource implications for business and IT leaders.

Recommendations to Product Leaders

To unlock the potential benefits of AI-enabled IoT for healthcare delivery, product leaders targeting these efforts should:

• Architect solutions to maximize flexibility in functional use to support composability. These products and applications perform their job within a larger multivendor ecosystem of solutions. They must have the capability to be orchestrated into workflows to support many use cases. Be ready for demand for application function API access — other solution sets may need direct access to execute your functionality from outside your codebase.
• Ensure solutions allow for open data integration. Because the capabilities enabled by these products must participate as peers with other sets of capabilities in end users’ workflows, any data collected or created must allow for adaptable usage. This usage can come from anywhere in the environment, and should be supported through open APIs and use of data standards, where possible.
• Design the solution for easy implementation and operation. The healthcare technical environment is complex, your potential customers are looking for solutions that are easy to install and operate. AI-enabled IoT solutions are sophisticated, but do not need to be difficult to install and operate. Customers do not want to add unnecessarily to IT overhead or create additional technical burden for clinical end users.
• Prove time to value. Use data gained through production experience with existing customers to demonstrate to potential customers when they can expect to receive value with your solution or product.
• Architect for hybrid cloud while embracing cloud-out and edge-in concepts to maximize AI-enabled performance and scalability. More clinical solutions will be cloud-based once latency issues are resolved, and over time there will be less appetite from customers for on-premises solutions. Your designs will have to span this HDO cloud maturity path, meaning your solutions will need to cover on-premises, hybrid and cloud-only infrastructure patterns.
• Create support service programs to help with implementation and daily operations. Do not abandon your customers postimplementation. They will need help both technically and at the end-user level. Make sure your organization is ready with the right skill set to provide customer support and the ability to scale with your client base.