Patient result status • LIS-linked escalation

Mulago Results Check by Kebeza

A WhatsApp-based pathology result status checking workflow that allows patients to check whether a result is ready, while helping the laboratory detect delayed, not-ready, or not-found cases that may need internal follow-up.

StatusWorking pilot
Front-endWhatsApp
Back-endLIS query
EscalationTelegram alerts

The problem

Patients often return physically or call repeatedly just to find out whether a pathology result is ready. This creates avoidable congestion, frustration, cost, and staff interruption.

In cancer diagnosis, every unnecessary delay between specimen collection, result availability, patient notification, clinical review, and treatment planning matters.

What the system does

The workflow allows a patient to send a lab number through WhatsApp. The system checks the Laboratory Information System, returns a structured status response, and escalates not-ready or not-found cases to the laboratory team for follow-up.

Result readiness LIS verification Escalation alerts Patient navigation Audit trail

System workflow

Patient sends a lab number.
The patient starts with a WhatsApp message and enters their pathology lab number.
Webhook captures the request.
The system receives the message, extracts the lab number and phone number, and prepares a status query.
LIS query checks status.
The workflow checks whether the result is ready, not ready, or not found.
Decision logic responds.
Ready results trigger patient notification. Not-ready or not-found responses trigger internal escalation.
Telegram alert supports follow-up.
Delayed or unmatched cases can be sent to the laboratory team for review and action.
Digital trail is created.
Each interaction can be timestamped, supporting audit, monitoring, and performance reporting.

Patient benefit

Patients can avoid unnecessary travel and repeated counter visits when all they need is to know whether a result is ready.

Laboratory benefit

The laboratory gets a cleaner way to detect pending, delayed, or not-found cases instead of relying only on manual follow-up.

Health-system benefit

The same model can support turnaround-time monitoring, escalation rates, and evidence for service improvement.

Measurable indicators

  • Number of patient result checks.
  • Percentage of cases marked ready, not ready, or not found.
  • Escalation rate for delayed or unmatched cases.
  • Time from escalation to status update.
  • Potential reduction in phone calls and return visits.

Scale potential

This model can start with pathology results, then expand to other diagnostic service lines where patients repeatedly need status updates.

  • Histology and cytology result readiness.
  • Microbiology culture result status.
  • PCR result readiness.
  • Radiology report readiness.
  • Blood bank crossmatch readiness.
Important note: This workflow checks result readiness/status. It does not deliver confidential diagnostic content publicly and should be implemented with appropriate institutional approvals, patient privacy safeguards, and laboratory governance.

Support patient-centered diagnostic access

Kebeza is building practical digital health workflows that reduce unnecessary patient travel, improve laboratory accountability, and strengthen cancer diagnostic pathways.