Technology decisions rarely exist in isolation. They are shaped by business objectives, people, information, constraints, and the realities of execution. Our Insights draw on real-world experience to explore the challenges behind those decisions and what becomes possible when they're better understood.
Technology initiatives can move quickly toward platforms, vendors, architecture, and implementation, sometimes before the organization has fully agreed on what it is trying to make better.
AI can make information easier to find, understand, and use. It can also make long-standing information problems much harder to see.
What looks like a choice between development and licensing often becomes a much bigger decision about ownership, dependency, and the freedom to change.
A successful prototype can prove that AI is useful. It doesn't necessarily prove that an organization is ready to depend on it.
AI can become extraordinarily good at reasoning over clinical information, but it cannot recover important evidence that was never acquired.
Healthcare is organized around institutions and encounters. A person's health journey continues between them.
A system can be delivered successfully without producing the improvement that justified the investment in the first place.