Cancellations are an information problem

Pathways screens every patient at the moment of booking rather than at the pre-admission clinic, so the findings that cause cancellations — unwithheld SGLT2 inhibitors, poor glycaemic control, undiagnosed sleep apnoea, missing discharge support — surface weeks ahead, while the list can still be optimised, rescheduled or backfilled.

The lever is timing rather than thoroughness. In almost every cancelled case the determining fact existed weeks earlier; it simply had not reached the anaesthetist while there was still time to act on it.

That also means the screening has to cover every booked patient, not the ones who look complex on paper. The patients who cancel lists are by definition the ones whose risk was not visible in advance.

Days rather than quarters. Because Pathways runs standalone over SMS with no PMS or EMR integration required, a service can begin sending assessments on its next elective list. There is nothing for patients to install and no software to deploy on hospital workstations — the platform runs in a browser.

Per site or by procedure volume, so the figure tracks the size of your pre-admission workload rather than a seat count. A short scoping conversation about your lists produces a fixed annual figure. Business is an annual agreement, invoiced yearly in advance.

Seat-count pricing does not describe this workload well. A pre-admission service might have three anaesthetists and eleven nurses, or the reverse, and the number of people who log in says very little about how many patients are being assessed. Volume does.

It also means adding a coordinator to the roster does not change what you pay, which removes a small but real disincentive to putting the right people in front of the queue.

Yes. Pathways keeps org-wide and per-patient audit logs with full workflow tracing on every risk analysis — the inputs used, the rule version that fired, the output produced, and the human who reviewed it, all timestamped. Logs are exportable for governance committees, M&M review and accreditation.

Because the safety-critical rules are deterministic and versioned, an audit is reproducible rather than merely archived: re-running a case against the rule version recorded at the time produces the same flags. That is the property that lets a decision made in March be examined in September without argument about whether the system “would have said something different”.

They proceed. Every completed profile carries a triage recommendation — anaesthetist review, pre-admission clinic, telephone review, or no further assessment — so clinic slots go to moderate-risk patients and anaesthetist time goes to red flags. Low-risk patients are not routed into a clinic appointment they do not need.

This is the throughput argument, and it runs in both directions. A pre-admission clinic booked out three weeks ahead with mostly healthy ASA 1 patients is not short of capacity so much as misallocating it. Screening every patient at booking makes the queue orderable by risk rather than by whoever called first.

The tracker shows exactly where they stopped — sent, opened, part-way through, or expired — and automated reminders go out without anyone chasing. A link can be resent in one click. Because the status is visible per patient rather than inferred from silence, an incomplete assessment becomes a task on a list instead of a discovery on the day of surgery.

Non-completion is normal and expected — it is why the tracker exists. The failure mode worth designing against is not the patient who does not finish, but the service that does not know they did not finish until the pre-admission clinic.

Patients who genuinely cannot complete a remote assessment are then a known, named group who can be routed to a phone call or a clinic slot deliberately, rather than turning up unassessed.

They are identified as a group rather than missed. The assessment needs only a phone that receives SMS and opens a link — no app, no login, no account. Patients who cannot complete it that way show as incomplete on the tracker, so the service can route them to a telephone assessment or a clinic slot deliberately instead of discovering the gap later.

The design point is that remote assessment does not have to work for every patient to be worth doing. It has to work for enough of them that the clinic’s finite capacity can be pointed at the ones it does not work for — which includes patients without a suitable phone, patients who need an interpreter, and patients who would simply rather come in.

What Pathways changes is that this group is visible in advance and small enough to plan around, instead of being indistinguishable from everyone else on the list.

No. It decides who should be in it. Every completed profile carries a triage recommendation — anaesthetist review, pre-admission clinic, telephone review, or no further assessment — so clinic slots go to the patients who need them. The clinic keeps doing the same work, for a different and better-chosen set of patients.

Most pre-admission clinics are not short of clinical capability. They are short of a mechanism for allocating their capacity, so slots fill in the order bookings arrive — producing a clinic of largely well patients while a frail patient with poor functional capacity gets a short phone call.

Screening every booked patient early makes the queue orderable by risk. The clinic’s capacity does not change; what changes is who is in it.