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Simulated proof asset · India diagnostic centres · Updated 2026-07-12

Diagnostic centre WhatsApp follow-up and DPDP evidence readiness example

A transparent synthetic proof-of-work showing how AICloudStrategist maps diagnostic-centre calls, WhatsApp, website bookings, referrals, home collection, corporate camp lists and insurance queries into safer automation-readiness queues.

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Honesty label

This is a simulated internal proof-of-work asset. It uses synthetic diagnostic-centre workflow counts only. It is not a real clinic, lab, diagnostic centre, patient, client, PHI dataset, production export, legal opinion, medical advice, privacy advice, security advice, DPDP compliance attestation, audit certification, booking result, revenue result, ROI result, testimonial, logo or ranking claim.

Why this asset exists

Diagnostic centres often want faster WhatsApp reminders, report-delivery nudges, missed-call callbacks and no-show recovery. This page demonstrates the owner-visible evidence AICS would assemble first: consent capture, notice links, WhatsApp opt-in, processor/vendor records, retention-review cadence, no-show SLA ownership, report-delivery route and AI boundary wording.

Synthetic input summary

MetricResult from synthetic sampleDiagnostic meaning
Workflow rows reviewed10Small synthetic sample for demonstrating method, not a real diagnostic-centre export.
Synthetic monthly records3,365Workflow volume represented across calls, WhatsApp, bookings, referrals, home collection and insurance queries.
Consent evidence gap records1,580 (47.0%)Rows where consent evidence would need review before expanding follow-up automation.
Notice-link gap records2,085 (62.0%)Rows needing clearer purpose and notice linkage.
WhatsApp opt-in gap records750 (22.3%)Rows where channel-specific opt-in evidence needs verification.
Owner assignment gap records1,370 (40.7%)Rows lacking visible accountable ownership.
Processor/vendor record gap records1,940 (57.7%)Rows where CRM, WhatsApp BSP, telephony, cloud or lab-system responsibility needs documentation.
Retention review >180 days records1,560 (46.4%)Rows with stale retention-review cadence in the synthetic sample.
No-show follow-up >120 minutes records1,475 (43.8%)Rows where callback or no-show follow-up is late.
AI boundary disclosure gap records2,085 (62.0%)Rows where scripts need clearer scheduling/status/routing-only boundaries.
Attachment/PDF report-delivery records to review1,615 (48.0%)Rows where portal-link alternatives and report-delivery risk should be reviewed.

Highest-priority synthetic workflow flags

WorkflowMonthly recordsSelected flags
W06 — Corporate camp list640Consent, notice, owner, processor, retention, late no-show follow-up and AI-boundary gaps.
W02 — Missed call callback310Consent, notice, owner, processor, retention, late no-show follow-up and AI-boundary gaps.
W08 — Abandoned booking145Consent, notice, owner, processor, retention, late no-show follow-up and AI-boundary gaps.
W01 — WhatsApp referral420Notice, processor/vendor record and AI-boundary gaps.
W05 — Doctor network upload190Notice, WhatsApp opt-in, processor, retention and AI-boundary gaps.

Owner-dashboard proof pack

  1. Channel map for missed calls, WhatsApp, website booking, referrals, home collection and insurance queries.
  2. Consent, notice and WhatsApp opt-in status by workflow, owner and record volume.
  3. Processor/vendor evidence queue for CRM, WhatsApp BSP, lab system, cloud storage, email, telephony and analytics tools.
  4. No-show callback SLA with first follow-up timestamp, owner and escalation reason.
  5. Report-delivery route review covering portal links, email attachments, WhatsApp PDFs and print pickup.
  6. AI boundary script review for scheduling, status, routing, emergency escalation and clinical-question handoff.
  7. Written approval before any real case study, testimonial, logo, patient outcome, booking, revenue or ranking claim.

Reproducible artifact

The source model and generated markdown report are stored internally at /home/agent/.hermes/aicloudstrategist/case-studies/simulated-india-diagnostic-center-dpdp-whatsapp-followup-2026-07-12/. Inputs are explicit in sample_india_diagnostic_center_workflows.csv; calculations are deterministic and labelled as simulated.

Verification: python3 india_diagnostic_center_dpdp_followup_diagnostic.py regenerated the report with rows=10, total_records=3365, consent_gap_records=1580, notice_gap_records=2085, whatsapp_opt_in_gap_records=750, owner_gap_records=1370, processor_gap_records=1940, stale_retention_records=1560, late_followup_records=1475, ai_boundary_gap_records=2085 and attachment_delivery_records=1615. Input SHA256: 44cc54a5718c447753ba8073059bf667ad7d7147b0fff8cde80c756aa470ae21.

Claim boundary

No real Indian clinic, diagnostic lab, diagnostic centre, patient, client, PHI, production data, Data Protection Board filing, DPDP compliance status, audit attestation, security audit, legal advice, medical advice, privacy advice, security advice, booking lift, revenue outcome, ROI, regulator outcome, platform partnership, logo, testimonial or ranking is claimed. Real implementation would require explicit scope, data-handling approval, organisation-approved policies, payment route and written authorization before any public proof use.