What if the data needed to launch a golden age of innovation in healthcare is already available?
This is actually the case in Canada, according to Mary Jane Dykeman, Managing Partner at INQ Law, a Toronto health and data law firm. And she knows what she’s talking about. A longstanding health lawyer, Dykeman’s data law practice focuses on privacy, data governance, artificial intelligence (AI), cyber preparedness and response, primarily in the health sector.
So what’s holding it back?
Dykeman says one roadblock to this tech renaissance is that much of the data generated by Canadian healthcare systems is siloed across and inside organizations. That limits the sector’s ability to power innovation by tapping into data at scale.
“This is a very exciting time to be working in health,” says Dykeman. “Our challenge is that healthcare organizations can include everything from hospitals to private practices, to mental health and addiction agencies and beyond. Each holds vast amounts of data. And these organizations typically have many legacy systems that don’t talk to each other.”
Essentially, the data is not centrally available or interoperable, she explains.
“Ask yourselves: where is your data, is it usable, and what steps must you take to ensure its quality? Only then can you generate insights from that data. That’s when the magic happens. This is the opportunity to transform the sector.”
To do that, the entry point is to innovate responsibly. The entry point is robust privacy and security protections. And to not include the public, the source of the health data, does them a disservice.
“The public deserves transparency about their data – both the negative and positive stories. They don’t know what is possible, because all they hear is the negative, about the last big data breach. Patient-centric design includes them, and can bring to them the same excitement we have about the tremendous opportunities to advance our health system with data. Because these transformations will ultimately help them, and if not them personally, others around them.”
Despite these challenges, the digitalization of healthcare is already underway.
For example, IBM’s Watson for Health is using cognitive technology to process data and improve diagnostic outcomes. AI technology is being used to significantly cut the time to market and cost of new drugs. These are just two of many current data-driven innovations in the sector.
An increasing number of Canadian companies are making breakthroughs in healthcare by leveraging data, machine learning (ML), AI or other data-driven approaches.
Dykeman points to two groundbreaking initiatives that are changing the face of healthcare:
- Signal 1 AI, a Toronto startup is employing a machine learning (ML) tool that can predict a patient’s risk of death. The tool was developed at Unity Health Toronto, a hospital network in the Greater Toronto Area, and will eventually be used as a model for other clinical areas..
- The Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH) is using big data, artificial intelligence and brain modelling to change how we understand and address mental illness.
Dykeman recently stepped in as interim vice president and chief legal and risk officer for CAMH. She notes, “CAMH, Unity and others are on the vanguard of using innovative approaches for better patient outcomes and enhanced operations.”
Four ways healthcare leaders can accelerate data-driven health outcomes
For healthcare leaders on a mission to boost their organization’s data innovation journey, Dykeman offers some key advice that helps to enable human, organizational and financial objectives:
Assemble key leaders with high data literacy to make change happen
“Data creates an opportunity that organizations miss out on if they don’t make it a priority,” she says. “And then, of course, you need the right people at the table. In a healthcare organization that should include an innovation lead – a person who has the aptitude, vision and influence. While it will vary among organizations, it can also include the CTO, CISO, privacy and legal leads, as well as program leads driving the change.
Map and organize your organization’s data
“Organizations need to make a commitment to find their data, itemize it, decide what to do with it and make it usable. This is a critical early step,” Dykeman advises.
Create a legal, privacy and ethics framework
“This should also start from day one,” she says. “Once you have a framework grounded in law, privacy and ethics, you can scale and unlock new ideas. This creates a solid foundation for change. These can never be afterthoughts, and have to be embedded in the decision-making.”
Decide on your organization’s execution path
“Every organization will have questions about how to execute a strategy,” Dykeman says, pointing out a few key questions organizations will need to tackle:
- Should your healthcare organization recruit data analysts and data scientists?
- Should you build machine learning and artificial intelligence algorithms in-house, or partner with others to acquire those services?
- How can healthcare organizations break down the silos and work more collaboratively?
“We are at a critical juncture on data strategy: to participate in this powerful collaboration, it’s imperative to get your data house in order – you’ll want to be part of the group that has, and are seeing results.”