One of the things that I enjoy most about my role is that I get to help people understand the art of what is possible in health care through the use of new technology.
There's often a culture shift involved, because of the way technology can impact care delivery workflows, but my team and I work throughout our organization to drive home the use cases for technology. This leads to "a-ha moments" when we meet with business line leaders.
For example, most technical workflows are rules-based - if you see X, then do Y. But machine learning is much more dynamic - you saw X, and you did Y, and it didn't work, so you should try Z. This opens up a lot of possibilities.
Even our own analytics team benefits from the use of new technology. A lot of analysts are used to leveraging dashboards and drilling down on their own - but cloud computing and graphical database implementations are revolutionizing data analytics to the point that the machine can guess the next question for you helping you get to and act on the answer more quickly.
More opportunities to help constituents
Technology is causing a shift in more than just the work that we do to design and deliver health care. It's also expanding the opportunities to help others succeed. It's not enough to simply help our employees succeed---as a payer, we're serving a group of constituents that includes providers, employers and consumers.
For providers, we see their needs changing as reimbursement models shift to value-based care. We are focused on implementing technology that will help providers manage "the whole person," instead of just treating patients when they are in the office.
For consumers, we see the effect of companies such as Amazon and Google influencing the way they interact with technology. In addition, new proposed rules on interoperability from HHS and CMS would mandate that data has to be available to the consumer at any time. This impacts us in two key ways: We need the foundational technology that enables consumers to access their data; and we have to manage security very differently. We're monitoring these rules very, very closely - and we're thinking about how consumers will need to be educated about these changes.
For employers, we see a struggle to control health care costs that's getting in the way of being competitive. We're trying to equip employers with the information they need to budget better - but also to help them understand the right plan design so the products they provide to employees support their wellbeing and enable them to be as productive as possible.
Collaboration and holistic decision-making
We will face challenges along the way. One of the biggest is that health care's legacy infrastructure does not always work seamlessly with modern technology. We need to figure out how we get these two platforms to talk to each other.
In addition, we have to protect the data we have. We know that we have to be sensitive to protected health information and other information that we have ownership of. As we move to cloud-based and open-source technology, we have had moments where we have been looking at old policies and procedures for on-premises data, and it's like putting a round peg into a square hole. We have to look at new policies and procedures for the cloud.
However, despite these challenges, technology will help us advance care delivery and decision-making. Artificial intelligence and machine learning, combined with the proposed rules to improve interoperability and ongoing efforts to promote value-based care, will create more data transparency. This will provide us with more opportunities to collaborate with all the stakeholders in the health care delivery system. We will be able to stop making decisions in silos and start making decisions more holistically to the benefit of all our members.