AI in Healthcare: Expert Opinion

AI by 2030 This plan is based on recognising that the digital future in healthcare is an imperative, and that business models must change because of the evolution in technology, policy and culture, especially in light of the COVID-19 pandemic.

Mayo’s digital transformation starts with data, said Dr Halamka. Since 154 years ago, when the clinic launched patient records, there are many longitudinal data coming from various sources and in various formats that need to be digitised, because the data of the past are used to inform the care of the future.

Challenges here are: privacy protection, compliance with GDPR and HIPPA regulations, cultural expectation that the data are being used in positive ways. Due to this, de-identified aggregated data are an imperative to protect privacy.

De-identification is extremely difficult. Mayo uses natural language processing and machine learning, and once the data have low probability of re-identification, they are put out to Google Cloud in an encrypted container with controlled access. Third parties can use them for their own R&D, but the data never leave Mayo’s control.

These de-identified data are used to create products and services through the so-called AI Factory, where Mayo’s AI tools are integrated. The AI Factory can be used by Mayo staff to explore new ideas, e.g. in radiation oncology, diagnostics of neuromuscular diseases, etc. Thanks to this, each department at Mayo starts to think in this ‘platform’ approach. It integrates the data about patient with EHRs, providers, payors, etc. through algorithms that generate value for Mayo, creating a completely new business model.