To mitigate risks, organizations need a well thought-out and constructed framework for dealing with data from a governance standpoint, from both a research and technological standpoint. For example, we think the AI environment should ideally be separate from the rest of the data infrastructure. Where possible, make use of containers and virtual machines to ensure there are no vulnerabilities. Adhere to best practices around coding standards and review processes. There’s a lot that organizations can and should do to ensure the utmost level ofethical excellence relative to AI, and also ensure their data is protected.
What else should healthcare organizations think about when using AI to recruit and retain workers?
Organizations need to be thinking about the ethical use of AI. We think that just as important as the efficacy of AI, if not more important, is how explainable the use of AI is. There needs to be better visibility into the AI data, and there needs to be more federated access to ensure recruiting and retention practices are lawful and ethical. At the same time, having a good data governance framework in place will help to recruit workers on a more equitable basis.
Your team predicts that by 2026, digital acceleration and data-driven policies will scale health equity in 60% of healthcare organizations, sparking further investments for environmental, social, and governance (ESG) goals. How will ESG initiatives continue to impact healthcare organizations?
环境、社会和治理的一个重要方面是它提供es aspirational goals that organizations can allocate resources toward and benchmark progress against. From a healthcare standpoint, and with social and governance considerations in particular, organizations can foster the wellbeing of the community and larger populations, not only patients. But it’s hard to navigate in that direction unless you have declared identifiable goals and have a framework in place to pursue them.
This is where data-driven approaches can be so valuable. Sometimes organizations are confident in their ability to deliver care, but when they actually do the work and look into the data, often they’ll find variations and outcomes that aren’t necessarily aligned with their aspirations for the organization. So having the right analytics tools in place is the way forward. Organizations need a broad set of analytics that can provide data on everything from clinical to operational to population health to social determinants and even consumer data. It all combines to offer a longitudinal and 360-degree view of patients and care-seeking consumers. In this way, digital acceleration can help promote health equity and drive progress towardESG goals.
How do you see digital-first strategies and enterprise technology investments delivering value to healthcare organizations?
Most obvious is they help to create a digital front door that gives patients convenience and better meets their expectations of providers. That’s a big deal. Digital-first is about offering an experience that can respond to the shifting wants and needs of patients and consumers.