# Pathways insights

> Pathways publishes writing on perioperative operations, clinical AI architecture, and the information problems behind preventable failures in surgical care.

*Source: https://getpathways.ai/insights*

## Clinical safety rules should not be model output

Safety-critical clinical screening should be implemented as deterministic, versioned rules rather than model output, because clinical governance requires reproducibility rather than accuracy alone. A rule that fires whenever its conditions are met can be tested, audited and re-run months later to produce the same answer — a property a probabilistic system cannot offer.

URL: https://getpathways.ai/insights/deterministic-rules-in-clinical-ai

## The medication history is the weakest link

Pre-operative medication histories are usually assembled from patient recall and a GP summary that may be months old. The drugs patients are least able to name — anticoagulants and SGLT2 inhibitors described as 'a blood thinner' or 'something for sugar' — are precisely the ones whose management must be planned days ahead, which is why they cause cancellations.

URL: https://getpathways.ai/insights/the-medication-history-problem

## What data sovereignty actually requires

Data sovereignty means patient information stays within Australian jurisdiction across its whole lifecycle — storage, processing, backup and any third-party service it passes through. Claiming an Australian region for the primary database is the easy part. The paths that matter are backups, subprocessors, support access, and, for AI systems, what is sent to a model provider.

URL: https://getpathways.ai/insights/what-data-sovereignty-requires

## Why clinics fill with the wrong patients

Pre-admission clinics fill with low-risk patients because slots are allocated in the order bookings arrive rather than by screened risk. The result is a clinic of largely well patients while the frail patient with poor functional capacity gets a short phone call. The constraint is allocation, not capability, so adding clinic capacity does not fix it.

URL: https://getpathways.ai/insights/why-clinics-fill-with-the-wrong-patients

## Cancellations are an information problem

Most day-of-surgery cancellations are caused by information that existed weeks before the operation but reached the anaesthetist too late to act on. Because the limiting factor is timing rather than clinical thoroughness, cancellation rates respond to moving assessment to the point of booking far more than to assessing more carefully at the clinic.

URL: https://getpathways.ai/insights/why-day-of-surgery-cancellations-are-an-information-problem