Watching the Waitlist: Risk Triage for People Who Are Not Patients Yet

A counselling practice’s waitlist is a spreadsheet sorted by referral date, which quietly asserts that the person who asked first needs help most. Between the referral and the first session, which may be four months apart, the practice learns nothing. Someone gets better and does not say. Someone gets much worse and does not say either, and the practice finds out when they arrive at an emergency department or when they stop answering the phone.

This is the transformation we would run for that practice. It is presented as a concept, built on the same method we use in client engagements, so the before, the after, and the path between them are all visible.

How long are people actually waiting?

The Canadian Institute for Health Information published wait times for community mental health counselling covering 2024-2025 across roughly 94,000 referrals. Half of the people referred received care within 30 days. Adults waited a median of 34 days, 41 days in urban areas and 25 days in rural ones. And 1 in 10 waited longer than four months, which CIHI puts at 131 days.

The direction matters more than the median. CIHI reports that wait times for community mental health counselling increased 36% between 2020 and 2024. A practice cannot fix that with software: the constraint is clinician hours, and no scheduling change creates a therapist. What software can change is whether the wait is blind.

That is the honest framing of this study. It does not shorten the queue. It makes the queue observable, so the order can reflect need rather than arrival time, and so deterioration reaches a person while there is still something useful to do about it.

Before and after: the waitlist

Drag the handle. The before is the referral-date spreadsheet; the after is the observed waitlist designed in its place.

The queue is the same length. What changes is that it has information in it, and that a clinician sees movement rather than a static list.

What we built

The concept above is the output of the same engagement steps we run in client work, and several of these are decisions a competent peer could argue with.

• We made the system incapable of lowering anyone’s priority. It can surface a person for clinician attention and it cannot do the opposite. This is asymmetric on purpose: a false surface costs a clinician two minutes, and a false reassurance costs something that cannot be undone. The design deliberately accepts a higher false-positive rate than a balanced classifier would.
• We treat non-response as a signal with structure rather than as missing data. Someone who completed three check-ins and stopped is surfaced differently from someone who never began, and the practice defines what each pattern means rather than inheriting a vendor’s default.
• We put crisis resources above the first question in every check-in, and we refuse to let the interface imply that anyone is reading in real time. Nobody is, and a form that feels like a conversation is the failure mode that gets someone hurt.
• We left the clinical judgment entirely un-automated. No score, no ranking model, no risk tier assigned by a model. Structured instruments the practice already trusts are administered and their movement is displayed; the interpretation is a clinician’s.
• We wire evals from day one against the practice’s own historical waitlist outcomes where those exist, scored on whether the cases that escalated would have been surfaced earlier, and every clinician dismissal becomes a test case.

How it works

The practice management system stays the source of truth for the waitlist itself. A structured check-in, built from an instrument the practice already uses, goes out on a cadence the clinical director sets. Responses and non-responses both feed a view the clinical team reads. Anything that moves, a score that worsened, a check-in that stopped arriving, a crisis pattern in free text, is surfaced for a clinician to read. Only a clinician changes a person’s position. Crisis patterns alert immediately rather than waiting for the next review.

Because responses and clinical context stay in Canadian infrastructure and processing runs with zero data retention, the design lines up with what PHIPA expects: a privacy impact assessment before deployment, an agreement naming the processor as an agent under section 17, and an audit log on every access. Retention is set deliberately short.

Why this pays back

This is the study in the collection where the economic argument is weakest and should be, so it is stated plainly rather than dressed up. The return is crisis presentations avoided among people who were waiting, valued at whatever an urgent intake or an emergency referral actually costs the practice. This study does not supply that number, because any figure invented for it would be exactly the kind of statistic the rest of these pages refuse to quote.

The limit worth saying before anyone signs: a practice whose waitlist is two weeks long does not need this. The value scales with the length of the wait, and below roughly a month the check-in cadence becomes an intrusion rather than a safety net. A practice should also expect modest response rates and decide in advance whether a partially observed waitlist is better than an unobserved one. We think it clearly is. A clinical director who disagrees has a defensible position, and should not buy this.