TLDR
Legacy healthcare systems were built for a different era. Cloud migration alone is expensive and rarely fixes the underlying workflow issues. Today, building new internal and customer-facing healthcare platforms is often more economical and better aligned with how teams actually work, creating a far more practical foundation for integrating AI into everyday operations.
Healthcare App Modernization
When I speak with healthcare leaders, the hardest modernization decision is rarely whether to modernize, but what not to modernize.
The systems that deserve priority are the business-critical workflows teams rely on every day.
In these cases, building new, workflow-aligned tools is often more effective than migrating legacy systems.
I’ve seen three general patterns from my firm’s work with healthcare firms:
- Internal systems often:
- Work
- But are hard to change, access, or extend
- Cloud migration is a common response as a way to modernize workflows.
- Teams are increasingly choosing to:
- Build focused tools for specific workflows
- Introduce AI only when systems are designed to support it
Situation in Healthcare Ops
I was reading a report that says inefficiencies and poor integration in healthcare IT are costing hospitals and health systems more than $8 billion annually in lost productivity and system downtime.
That’s understandable because legacy tools still run a majority of essential internal workflows of healthcare organizations.
For example, workflows like patient care coordination, insurance and claims processing, contract and policy management, and internal reporting are mostly executed via legacy, on-premises tools that are very difficult to modify. Many of these systems were built years ago for a different era of work.
Although, these tools continue to function, process data, and support day-to-day decisions, over time, they become outdated.
These legacy tools are mostly:
- On-premises
- Rigid (no rules, no flexibility)
- Very difficult to modify
Migration to Cloud
When legacy system limitations become impossible to ignore, cloud migration is often treated as the obvious next step. It feels decisive. It feels safer than starting over. And in some cases, it is necessary.
But cloud migration is rarely the turning point leaders expect.
Moving a legacy system to the cloud almost always carries its limitations forward. The same brittle workflows remain. The same resistance to change shows up, just on modern infrastructure.
Months later, teams are left with higher operating costs and little real improvement in how work gets done. That’s how modernization efforts quietly fail.
What has changed is the economics behind the alternative. Building new, focused systems is no longer too expensive or too risky, the way it once was.
Economics of Software Development
The economics of software development have changed significantly in the last five years.
Modern frameworks, managed infrastructure, modular architectures, and AI coding assistants have significantly reduced the time and cost required to build secure, production-grade internal tools.
For many healthcare organizations, building new, focused digital workflows is now more practical than extending or migrating systems that were never designed to adapt. Instead of moving complexity forward, teams can redesign workflows around how work actually happens today.
This approach is especially relevant for high-trust healthcare workflows.
Insurance coverage decisions, internal policy guidance, and care coordination processes. These workflows depend on accuracy, accountability, and expert judgment. They benefit from intentional redesign rather than incremental patching.
New systems can be built with clear roles, better access patterns, and interfaces that reflect how teams actually collaborate across locations and devices.
Preparing for AI in Healthcare
Another common request we get is to layer AI functionality on top of existing tools and processes.
To use AI effectively, healthcare teams should rebuild workflows rather than adding AI to existing systems. AI works best when built into new systems from the start, not layered onto outdated ones. Building new tools makes it easier and safer to introduce AI features over time.
Real modernization means investing in new solutions that improve workflow, boost productivity, and support future innovation. At Coaldev, we design workflow systems that reduce friction, respect staff expertise, and enable responsible AI adoption, without risky or unnecessary migrations.
