A healthcare technology provider for centralized device, app and caregiver data with LakeStack, reducing analytics turnaround from two weeks to just 30 minutes.
Customer overview
Industry and customer challenges
Medication adherence platforms often operate across disconnected data streams, “devices, apps, caregivers, and manual logs”. As patient volumes expand, identifying high-risk behavior becomes slow and increasingly resource-intensive. Our customer experienced similar challenges:
1. Device, app, and caregiver data scattered across three silos
Adherence devices, mobile apps, and caregiver notes all lived in separate systems.
2. Slow analytics dependent on custom development
Every reporting request needed custom scripts from outsourced developers.
3. Care teams lacked real-time risk visibility
Identifying non-adherent or high-risk patients required manual review.
4. Outdated, manually curated dashboards
Executives relied on inconsistent dashboards updated through manual processes.
How LakeStack helped
LakeStack was deployed within weeks, establishing a unified data foundation across ingestion, modeling, governance, and AI-driven insights. All without requiring internal engineering resources.
LakeStack ingested and harmonized device streams, app activity, and caregiver logs into a single clinical model.
Patient adherence histories were organized into FHIR-aligned timelines, enabling faster review and trending.
Prebuilt GenAI models surfaced missed doses, rising risk profiles, and drop-off patterns automatically.
Teams gained instant visibility into patient cohorts, escalations, and operational workloads.
NLQ allowed care teams to ask questions like: “Show patients with 3+ missed doses last week.”
Audit trails, structured access, and PHI-safe handling were deployed out-of-the-box.
Success metrics
- 80-90% of engineering cost avoided.
- 40% improvement in high-risk patient identification.
- Analytics turnaround cut from 2 weeks to 30 minutes.
- Onboarding and ingestion cost offset through MAP funding.
- AI-ready foundation enabled rapid launch of new data-driven products.
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