Post-discharge monitoring that surfaces risk early and keeps escalation clinician-led.
Aescia runs structured patient check-ins after discharge, flags concerning trajectories, and presents a simple “who needs attention first” view to the clinical team. The goal is safer discharge, fewer avoidable returns, and more predictable follow-up.
Fastest pilot path: choose a cohort, agree escalation ownership, run an 8 to 12 week pilot with workflow and outcomes metrics.
Expected impact, in plain language
- Fewer avoidable representations and readmissions through earlier detection and consistent follow-up.
- More throughput when saved bed-days are reutilised for additional cases.
- Lower avoidable cost when events are prevented or managed earlier in the community.
We can model your local value using your cohort volume, baseline readmission rate, average length of stay, and a bed-day value. Aescia pricing can be aligned to outcomes via gainshare.
Details you can expand
Impact model: throughput and avoided costs
Below is a practical, conservative template that we tailor to your site. It separates two buckets because finance teams often treat them differently.
Throughput gains (reutilised capacity): saved bed-days that are used for additional admissions or surgery.
Avoided costs (cash releasing): preventable returns, admissions, and complication pathways.
Example structure (site-specific numbers plug in):
- Eligible discharges per year: N
- Engagement rate: 50 to 70 percent (pilot-measured)
- Index length of stay reduction: 0.25 to 1.0 days in engaged patients (cohort dependent)
- Readmission reduction: 10 to 25 percent relative reduction (cohort dependent)
- Bed-day value: your local finance figure or proxy (varies by jurisdiction and accounting method)
- Reutilisation fraction: often 50 to 80 percent (how much saved capacity becomes real throughput)
Outputs we calculate with your inputs:
- Bed-days saved: from shorter index stays plus fewer readmission days
- Additional cases enabled: bed-days saved × reutilisation ÷ average length of stay
- Financial value range: throughput value plus avoided cost value
We do not claim guaranteed savings. The pilot is designed to measure engagement, escalation load, and early signals of outcome lift in your context.
What Aescia actually does
- Structured check-ins using prompts that map to your pathway.
- Trajectory flags so clinicians see who needs attention first.
- Consistent escalation with site-specific rules and transparent logic.
- Auditable trail of follow-up attempts, responses, and escalations.
What a credible pilot looks like
- Duration: 8 to 12 weeks
- Cohort size: 100 to 300 discharges (or smaller if governance is heavy)
- Workflow metrics: response rate, time-to-escalation, clinician time per escalated patient
- Outcome metrics: Emergency Department representations, readmissions, complications caught earlier, patient experience
- Operational metrics: escalations resolved remotely, discharge confidence, burden on follow-up staff
Is this clinical decision-making by AI?
No. Aescia is structured follow-up and escalation workflow. Where automation helps is summarisation and prioritisation. Escalation remains clinician-controlled.
Implementation effort
A pilot can run without deep integration at first. If it works and the workflow is validated, integration becomes worth doing and easier to justify internally.
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