Healthcare & Life Sciences

According to research on NHS interoperability, England experiences an estimated 1.8 million undetected medication errors at patient transitions every year, causing harm across more than 31,000 patient episodes annually. Moreover, 8 million outpatient appointments went unused last year, representing £1.2 billion in wasted resources annually.

Patients should not have to repeat themselves. Neither should your staff.

The NHS and private healthcare providers alike are grappling with the same underlying issue. Vast amounts of clinical and administrative data, held across systems that were never designed to share it. The burden falls on staff who end up filling the gaps manually, and on patients who experience the consequences of a system that does not quite join up.

What this looks like when it works

A referral is made and the receiving clinician has everything they need before the appointment. A patient is discharged and the follow-up is scheduled, the GP is notified, and the billing is coded without anyone re-entering a single detail. A compliance return that used to take a week to compile is produced in an afternoon.

The Problems We Solve

Clinical information spread across too many systems

Records, diagnostics, prescribing, appointments. Each sits in a different platform, and staff piece together the picture manually under time pressure. The risk that creates is not acceptable.

Referral and discharge processes that rely on people chasing people

When information does not move automatically between systems, it moves by email, phone and fax. That is slow, inconsistent and difficult to audit.

Clinical activity that does not reach the billing system

A gap between what has been delivered and what has been invoiced is a revenue problem. It is also usually an integration problem.

Research data that is hard to pull together consistently

Aggregating data from multiple sources for trials or population health work is genuinely difficult when those sources have never been connected. Manual collection introduces the kind of inconsistency that undermines the analysis.