Ontario is trying a wild experiment: Opening access to its residents’ health data

This has led companies interested in applying AI to healthcare to find different ways to scoop up as much data as possible. Google partnered with Stanford and Chicago university hospitals to collect 46 billion data points on patient visits. Verily, also owned by Google’s parent company Alphabet, is recruiting 10,000 people for its own long-term health studies. IBM has spent the last few years buying up health companies for their data, accumulating records on more than 300 million people.

Source: Gershgorn, D. (2018). Ontario is trying a wild experiment: Opening access to its residents’ health data.

I’ve pointed to this problem before; it’s important that we have patient data repositories that are secure and maintain patient privacy but we also need to use that data to make better decisions about patient care. Just like any research project needs carefully managed (and accurate) data, so too will AI-based systems. At the moment, this sees a huge competitive advantage accrue to companies like Google, that can afford to buy that data indirectly by acquiring smaller companies. But even that isn’t sustainable because there’s “no single place where all health data exists”.

This decision by the Ontario government seems to be a direct move against the current paradigm. By making patient data available to via an API, researchers will be able to access only the data approved for specific uses by patients, and it can remain anonymous. They get the benefit of access to enormous caches of health-related information while patient privacy is simultaneously protected. Of course, there are challenges that will need to be addressed including issues around security, governance, differing levels of access permissions.

And that’s just the technical issues (a big problem since medical software is often poorly designed). That doesn’t take into account the ethics of making decisions about individual patients based on aggregate data. For example, if an algorithm suggests that other patients who look like Bob tend not to follow medical advice and default on treatment, should medical insurers deny Bob coverage? These and many other issues will need to be resolved before AI in healthcare can really take off.