← Back to home

Clinical evidence & health system impact

The evidence base for post-discharge monitoring, projected outcomes, and our approach to rigorous clinical evaluation.

Evidence for post-discharge monitoring

The clinical rationale for structured post-discharge monitoring is well-established in the literature:

  • Readmission rates: 5–15% of patients are readmitted within 30 days across most surgical and medical cohorts
  • Preventability: Retrospective analyses consistently estimate 30–50% of readmissions are potentially preventable
  • Timing: Most preventable readmissions occur in the first 7–14 days post-discharge, when monitoring is most valuable
  • Intervention points: Early identification of deterioration allows management through outpatient review, community care, or telephone advice—avoiding emergency presentation

Projected health system impact

Conservative modeling based on published literature suggests the following impact at a typical large hospital:

Cardiothoracic surgery cohort example

Based on 800 annual discharges

25–30

Readmissions prevented annually

Assuming 8% baseline rate, 40% reduction in preventable returns

100–150

Bed-days recovered annually

From avoided readmissions plus earlier confident discharge

Economic value

The recovered bed capacity translates to significant operational value:

  • Direct cost avoidance: Each avoided readmission saves the direct cost of the admission episode
  • Throughput improvement: Freed bed-days can be reutilized at approximately 70% efficiency
  • Combined value: $8.1M+ in projected annual operational value for a single high-volume surgical unit

These projections are conservative estimates based on published literature. Actual outcomes will be measured through structured clinical evaluation.

Our approach to evaluation

Aescia engages with health services through scoped, time-limited clinical evaluations with:

  • Predefined endpoints and success criteria
  • Transparent outcome reporting
  • Site-specific ethics and governance approvals
  • Comparison against matched historical cohorts where appropriate

We do not seek routine clinical deployment without appropriate evidence. Our commercial model is aligned with demonstrated outcomes.

Regulatory posture

Aescia is positioned as Software as a Medical Device (SaMD):

  • Current use is limited to approved evaluation contexts
  • Development follows IEC 62304 software lifecycle practices
  • Risk classification and regulatory pathway completion is in progress
  • All clinical outputs are advisory and require clinician review

Published references

Key literature supporting the clinical rationale:

  • Jencks SF, et al. (2009). Rehospitalizations among patients in the Medicare fee-for-service program. NEJM.
  • van Walraven C, et al. (2011). Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ.
  • Leppin AL, et al. (2014). Preventing 30-day hospital readmissions: a systematic review and meta-analysis. JAMA Internal Medicine.
  • Hansen LO, et al. (2011). Interventions to reduce 30-day rehospitalization: a systematic review. Annals of Internal Medicine.

Key projections

30–50%

Readmissions potentially preventable

70%

Reutilization of freed bed-days

$8.1M+

Projected annual value per unit

Learn about our governance framework

Governance & compliance