The World Economic Forum was founded on the principle of assembling multilateral stakeholder coalitions to address global challenges that can’t be solved by private enterprises or public bodies alone. After interviewing more than 50 leaders from across biopharma, providers, insurers, technology firms and innovators, government, academia and non-governmental organizations, seven use cases rose to the top time and again: three that may be considered most ripe for public-private acceleration and four to be considered for deeper exploration. The use cases that rose to the top did so because they share two characteristics: – Potential global health impact: What is a use case’s potential to positively affect global healthcare outcomes, access and efficiency? – Need for multi-sectoral collaboration: To what degree would it benefit from public-private partnership and focus, with potential across high-, low- and middle-income countries? Figure 2 plots the most critical AI in healthcare applications in terms of the need for complex collaboration and potential global impact. The purpose of winnowing the universe of applications to those few with the widest reach and highest potential impact is to spur stakeholders to focus on areas where they are best positioned to make progress and commit to doing so. Given the use case taxonomy and criteria for prioritization, experts were asked to rank a set of the most promising use cases. For patientlevel tools, the vast majority ranked data-driven diagnosis and risk stratification among their top-two use cases. For population-level tools, a strong number ranked infectious disease intelligence in their top two. For product-level tools, many ranked optimizing clinical trials to speed the impact of novel therapies as a leading AI use case. In addition to these three use cases, leaders identified an additional four for deeper exploration: administrative AI, patient support and triage, AI for drug research and discovery, and AI for managing supply chain and manufacturing medicines. These use cases, which each hold substantial promise for relieving the health system burden and creating a healthier world, will be discussed later in the report. Prioritizing AI use cases, illustrative exercise F I GUR E 2 Lower Higher Lower Higher Potential global health impact Need for public-private collaboration Anti-fraud and integrity Clinical Rx* decision support Drug safety and pharmacovigilance AI-facilitated care (e.g. robotics) Claims processing Provider capacity planning Image-based diagnosis Quality assurance and training Patient triage and support Administrative AI (provider-facing) Supply chain and manufacturing Clinical trial optimization Data-driven diagnosis and risk stratification Infectious disease intelligence Novel drug identification Patient and device monitoring Population risk management and intervention Hospital performance prediction The purpose of winnowing the universe of applications is to spur stakeholders to focus on areas where they are best positioned to make progress and commit to doing so. *Prescription Scaling Smart Solutions with AI in Health: Unlocking Impact on High-Potential Use Cases 10
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