Hospital managers, pharma teams, and health plan providers have completely different analytical needs — but share a common problem: the data they need to make decisions is scattered, incomplete, or trapped in free-text medical records, inaccessible to any conventional BI system.
Most hospital dashboards show what the management system recorded in structured fields. But the data most relevant to clinical, financial, and epidemiological decisions is in progress notes, reports, and notes — in the free text that no traditional BI can process.
iHealth solves this in two steps: first, it structures unstructured clinical data with NLP; then it delivers that data in analytics layers customized for each decision-maker profile — with the level of detail, frequency, and format each context requires.