How to Automate Sigmund Software

One episode of care is written by six different clinicians

Sigmund Software builds an EHR, revenue cycle and CRM platform for behavioral health and addiction treatment organisations, and the platform is Sigmund AURA, a cloud-based and fully integrated record. The organisations running it are substance use disorder treatment providers, behavioral health centres, eating disorder centres, geropsychiatric facilities, and paediatric prevention and rehabilitation services.

What those settings have in common is that no single clinician owns the chart. A therapist writes the session. A psychiatrist writes the medication review. A nurse records vitals. A dietitian records what happened at the table. A case manager records what is happening with the family, the school or the court.

All of it belongs to one episode of care, and the thread running from the assessment to the treatment plan to the intervention to the note is exactly what an auditor traces when they arrive. A record written by six people has to read as though it were written by one.

The treatment team meeting is assembled by hand every week

Decisions in this kind of care are made in a room, on a schedule. The treatment team meets, works through each patient, and decides what changes: a level of care, a medication, a pass, a discharge date.

Preparing that room is somebody's morning. It means pulling this week's outcome measure scores, the group attendance, the vitals or weights, what the payer has authorised and for how much longer, and what the referring hospital has been told since the last time anyone rang them.

The work does not stop at discharge either. Aftercare is where behavioral health outcomes are won and lost, and finding out whether a patient actually arrived at the outpatient provider, the sober living house or the follow-up appointment means telephoning somebody else's front desk or signing in to somebody else's system. Most programs discover months later, from a readmission, that the handover never happened.

Sigmund Software

Outcome trends, not single scores Measures collected from whichever vendor hosts them, set beside the same patient's earlier results before the review happens.

Aftercare confirmed rather than assumed Discharged patients checked against the receiving provider's own record, so whether somebody arrived is a fact on the page.

Referral sources that went quiet Hospitals, courts and providers who used to send patients and have sent nobody this quarter, listed with the date of the last one.

The Golden Thread holds the record together

Sigmund has spent a long time on the problem of the multi-author chart, and the tooling reflects it.

Golden Thread is their name for information flowing between documents so the record builds itself with minimal keystrokes, which is the discipline a chart with six authors needs most. Target Behavior Tracking is the data collection and aggregate reporting tool for outcomes, with collection points running from pre-admission to well past discharge. Workflow Automation routes work to queues.

Each of those is strong because it works on one integrated record, which is also where it stops. Target Behavior Tracking reports the measures collected inside AURA; the instrument a funder insists on, hosted by the vendor who owns it, is not one of them. Workflow Automation routes a task to the right queue, but it cannot open the payer's site to find out whether the level of care was approved. And nothing in AURA can ring the outpatient clinic to ask whether a discharged patient turned up.

The team meeting can start with the answers already in it

Everything that meeting needs is already written down somewhere outside the building. Collecting it is a task, not a discussion.

Outcome measures pulled from whichever vendor hosts them and set beside that patient's scores from admission, so what reaches the table is a direction of travel rather than a number from Tuesday. The authorisation for each patient's level of care read at the payer's own site and ranked by what expires soonest, so a continued stay is argued while the days still count.

Discharged patients checked against the receiving provider's own record, so whether the handover happened is a fact somebody can see rather than an assumption nobody tests. Vitals and weights gathered against the range a clinician set, so the two patients worth discussing sit at the top of the list instead of somewhere in the chart. Referring hospitals, courts and providers ordered by how long since their last admission, so a quiet relationship is noticed while it can still be repaired. Family sessions that were meant to be scheduled and never were.

The line does not move for any of it. Reading, comparing and assembling can run unattended. Only a qualified person changes a record, alters a treatment plan or submits a claim, and each one is prepared and waiting when they do.

The team's hour should be spent deciding

The judgement exercised in that room is the reason the room exists. Gathering what it needs to look at is not judgement at all. It is an hour of somebody opening things and writing down what they say.

WebRun is an AI agent that drives a real Chrome browser, signed in as your own staff are, in a private environment of your own. Sessions are not shared between tools, and a workflow can be locked to an explicit list of domains, so it opens the payer sites, the outcomes vendor and the providers you named, and nothing else. You can watch a run and stop it partway.

It reads and it prepares. No note, plan or assessment is written by anything but a clinician, and nothing reaches a patient or a family until a qualified person has sent it.

Each workflow below names the sites it reads.