AI Could Finally Solve Healthcare's Interoperability Problem

Ask any doctor, nurse, or hospital administrator what frustrates them most; bad data flow will be near the top of the list.

Healthcare has spent decades trying to fix interoperability—how systems talk to each other—but we're still stuck with manual workarounds, redundant processes, and software that doesn't play nice.

And yet, I think AI might finally get us to where we've been trying to go.

Here's why:

AI focuses on intent, not just rigid automation.

Unlike old-school RPA (which broke every time a screen layout changed), AI can analyze what a user is trying to do and adapt accordingly. In African healthcare specifically, LLMs can interpret heterogeneous documentation from rural clinics using different record-keeping systems without requiring standardized formatting.

Fixes can happen in real time.

Instead of waiting for an IT ticket, frontline staff can correct issues themselves through something as simple as a chat interface. These systems can bridge language gaps by processing clinical notes in local languages and dialects where traditional translation would fail.

It can work around closed systems.

Not every provider will open their data, but AI can act as a bridge retrieving critical insights without needing full backend integration. This means LLMs can extract meaning from legacy systems common in resource-constrained settings without requiring expensive upgrades.

The real innovation comes from new capabilities:

• Patient History Consolidation: Creating comprehensive patient profiles by harmonizing data from paper records, SMS-based health programs, and modern EHRs
• Knowledge Contextualization: Adapting global clinical guidelines to local contexts, considering factors like regional disease prevalence
• Cross-system Diagnostic Support: Enabling diagnostics that draw from fragmented data sources across different facilities

At the ParallelScore Corporate Innovation Lab, we're exploring how companies—not just in healthcare but across industries—can use AI to solve real-world inefficiencies.

I'll be diving into these innovation pathways at our launch event in Johannesburg. If you're interested in how AI can move beyond hype and improve how businesses operate, especially in challenging environments like African healthcare systems, let's talk.