Follow Up with Every Patient by Voice AI — Without Adding Headcount
Vokalith conducts structured post-visit patient follow-up calls — checking on recovery, treatment adherence, and any new concerns — and escalates to clinical teams when needed.
100%
Follow-up coverage per protocol
85%
Reduction in manual follow-up calls
3×
Earlier complication detection
The Challenge
Why manual intake fails here
Patient follow-up calls are consistently under-resourced. Manual follow-up capacity is limited, resulting in inconsistent contact and missed opportunities to detect complications early.
Follow-up gaps
Under staffing pressure, follow-up calls are prioritised inconsistently — some patients receive them, others do not.
Adherence not tracked
Without structured follow-up, medication and treatment adherence is not verified, increasing non-compliance risk.
No structured follow-up record
Manual follow-up calls are often undocumented, leaving a gap in the clinical record between visits.
Delayed complication detection
Without consistent follow-up, post-procedure complications and readmission risk indicators go undetected.
How Vokalith Helps
What the automated workflow looks like
Scheduled follow-up calls
AI contacts patients at clinically configured intervals — 24h post-discharge, 1-week post-procedure, or per your follow-up protocol.
Structured recovery assessment
Each call collects structured post-visit data — symptom status, medication adherence, side effects, concerns, activity levels.
Automated escalation
Responses indicating complications, deterioration, or missed medications trigger immediate clinical team notification.
EHR documentation
Follow-up data is written directly to the EHR, maintaining a complete post-visit record without manual documentation.
Capabilities
What's included
- Scheduled post-visit follow-up calls
- Structured recovery & adherence assessment
- Medication compliance verification
- Automated clinical escalation
- EHR integration
- Configurable follow-up intervals
- Longitudinal follow-up record
Related
Related Use Cases
Insights
