Case Studies
Healthcare

Clinical Operations Exception Monitoring

A healthcare operations team reduced SLA breach detection from T+48 hours to T+2 hours — without a single engineering sprint after initial setup.

Multi-site clinical network, T+2h breach detection, zero engineering after setup.

At a Glance

ClientMulti-site healthcare operations team
IndustryHealthcare — Clinical Site Performance & Compliance
ScaleMulti-site clinical network, tiered SLA commitments
Systems ConnectedPatient encounter system · SLA commitment database · Site-coordinator compliance file uploads
Workflow DeployedClinical Operations Exception Monitoring
Deployment19 days, read-only, zero engineering after setup

Key Metrics

SLA Breach Detection

T+48h → T+2h

Time from an SLA breach to it reaching someone who can act on it.

Time to Live

19 days

Read-only connection to first live exception alert.

Compliance Prep Time

~70%

Weekly compliance prep time reclaimed.

The Situation

A healthcare operations team managing clinical site performance had patient encounter data in one system, site SLA commitments tracked in a separate database, and weekly compliance reports uploaded as files by site coordinators. There was no unified view. SLA breaches — delayed reports, missed documentation windows, threshold crossings — were typically discovered during the weekly review call, 48–72 hours after they occurred. Compliance management required a traceable chain from detected exception to documented resolution, which manual processes could not reliably provide.

The weekly review call wasn't a review. It was the only alert the team had.
Current State — Before Autonmis
Broken

Data sources

Patient Encounter System

Clinical site activity data

SLA Commitment DB

Site-level contracted thresholds

Site Coordinator Files

Weekly compliance uploads

No unified view — sources never sync

Failure events

T+48h breach discovery
Weekly review is the only alert
No traceable exception chain for compliance

What Was Breaking

Why manual operations couldn't scale

01

Three sources, no shared review.

Patient encounter data, SLA commitments, and weekly compliance uploads from site coordinators were tracked separately, with nothing checking them against each other in real time.

02

The weekly call was the only detection point.

A breach that happened the day after the call sat unflagged for up to a full week — not just the 48–72 hours the average implied.

03

There was no traceable chain from breach to resolution.

Compliance review depends on documenting exactly when an exception was caught and how it was resolved — a requirement manual review couldn't reliably meet.

The approach

The Approach

1

Connect your sources

Patient system, SLA database, and coordinator file uploads connected — read-only, 19-day setup.

2

Configure SLA rules per site tier

Documentation windows, escalation thresholds, and breach definitions written in plain language.

3

Autonmis monitors continuously

Automated evaluation runs on schedule. Breaches surface in 2 hours with full traceable chain.

After

Patient Encounter System

Clinical site activity data

SLA Commitment DB

Site-level contracted thresholds

Site Coordinator Files

Weekly compliance uploads

Autonmis

Governed Intelligence Layer

Knowledge Base

rules · thresholds · logic

Morning Exception Brief
Real-time Breach Alerts
Compliance-Ready Reports

Connected to all three source types. The Knowledge Base was configured with SLA definitions, documentation window rules, and escalation thresholds specific to each site tier. Autonmis ran automated cross-source evaluation on a schedule, comparing actual site performance against contracted SLA thresholds and flagging exceptions before they became compliance events. Exception briefs were delivered to the ops lead each morning. When a threshold crossing occurred during the day, a Slack alert fired with the site, the specific SLA dimension, and the time elapsed since the breach. The lifecycle governance layer — draft → review → approved on every published analysis — meant every exception report that reached a compliance officer had been formally reviewed and promoted.

The Workflow

TriggerA site's actual performance crosses a contracted SLA threshold for its tier — a missed documentation window or an escalation-level deviation.
Data SourcesPatient encounter system · SLA commitment database · Site-coordinator compliance file uploads
Runs AsContinuous cross-source evaluation against Knowledge-Base-defined SLA and documentation-window rules per site tier; morning exception brief plus same-day Slack alert on threshold crossings.
Human in the LoopEvery exception report moves through a draft → review → approved lifecycle before it reaches a compliance officer; ops lead handles same-day triage from the morning brief.

Results

T+48 hours → T+2 hours

SLA breach detection

Previously found at weekly review call

Audited against the weekly-review-call baseline measured before connection.

~70% reduction

Weekly compliance prep time

Exception reports generated and reviewed automatically

Audited against compliance prep hours in the period before go-live.

Day one

Traceable exception-to-resolution chain established

Every breach has documented detection and resolution

Zero

Engineering dependency post-setup

Ops team manages rules and thresholds independently

19 days

Time to first live exception alert

From initial source connection to production monitoring

Governance Note

No exception report reaches a compliance officer unreviewed — every one moves through the same draft-to-approved promotion path a published dashboard does, so the audit trail behind a single flagged breach is as complete as the one behind a metric an executive sees.

Implementation

Time to live

3 weeks

Sources connected

3

Engineering dependency

Zero

Ready to see it in your stack?

We can scope your use case to a live workflow in the first session.

Three sources. No engineering dependency. First automation in under three weeks.

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Composite deployment example. The business workflow reflects real implementation patterns. Company names, operational data, and reported outcomes have been synthesized for illustration.