Healthcare Intelligence Case Study
Hospital MRA: unifying revenue, operations and clinical intelligence.
An enterprise AI platform that connects fragmented hospital data, identifies financial risk, supports care teams, strengthens documentation and delivers role-specific intelligence from the C-suite to frontline clinicians.
23%Fewer claims denialsReported result
87%LOS prediction accuracyPredictive insight
340%ROI in 18 monthsBusiness impact
The challenge
Critical hospital decisions were constrained by fragmented systems.
The hospital network needed more than another reporting tool. It required a unified intelligence layer capable of understanding financial, operational and clinical signals together—without disrupting existing systems.
Revenue leakage
An 18% denial rate, coding gaps and missed reimbursement opportunities were creating avoidable financial loss.
Operational inefficiency
Extended length of stay and delayed discharge planning reduced bed availability and increased the cost of care.
Documentation gaps
Incomplete clinical documentation affected coding accuracy, reimbursement speed, audit readiness and care continuity.
Data silos and compliance exposure
EMRs, imaging archives, billing platforms and unstructured notes operated separately, limiting traceability and increasing audit risk.
The solution
A unified intelligence layer across the hospital ecosystem.
Hospital MRA connects existing data sources, standardizes and enriches multi-modal information, applies AI models and presents decision-ready insights through secure role-based experiences.
Connected data sources
EMR
Clinical recordsEncounters, diagnoses and care history
RCM
Billing & claimsCodes, denials and reimbursement data
PACS
Medical imagingRadiology studies and worklists
TXT
Clinical documentsNotes, summaries and reports
→
AI & intelligence core
ETL
Data integrationIngestion, validation and standardization
ML
Predictive modelsDenials, LOS and readmission risk
NLP
Clinical language intelligenceDocumentation quality and coding signals
CV
Imaging intelligenceAbnormality assistance and prioritization
MLO
MLOps governanceMonitoring, versioning and traceability
API
Enterprise servicesSecure APIs and access controls
→
Role-based experiences
FIN
Revenue intelligenceDenials, coding and cash flow
OPS
Clinical operationsLOS, discharge and capacity planning
RAD
Radiology workstationAI-assisted reading and QA
CDI
Documentation portalCompleteness, impact and coaching
HIPAA-aligned controlsRole-based accessEncryption in transit & at restAudit loggingModel monitoringData lineage
Core dashboard modules
One platform, purpose-built experiences for every stakeholder.
Each module translates complex hospital data into focused decisions for the teams responsible for financial, operational and clinical performance.
01
Revenue Cycle Management Dashboard
Provides real-time visibility into denial risk, coding opportunities, audit exposure and projected cash flow—down to claim-level detail.
Denial risk heatmapCoding opportunity trackerAudit risk monitorCash-flow forecastingClaim drill-downs
Designed for: CFOs, revenue-cycle directors, billing managers and coding teams.
02
Clinical Operations Dashboard
Helps clinical leaders anticipate length of stay, accelerate discharge readiness, monitor bottlenecks and plan capacity using live operational intelligence.
LOS predictionDischarge readinessBed capacity planningReadmission riskLive census tracking
Designed for: CMOs, department heads, utilization review teams and care coordinators.
03
Radiology Intelligence Workstation
Supports radiologists with prioritized worklists, AI-assisted image review, visual heatmaps and second-reader quality assurance.
AI-assisted readingAbnormality heatmapsPriority worklistComparative analyticsSecond-reader QA
Designed for: Radiologists, referring physicians and radiology administrators.
04
Documentation Quality Portal
Uses clinical NLP to identify missing documentation, quantify revenue impact, support coding teams and guide targeted physician improvement.
Completeness scorecardsRevenue impactNLP suggestionsPhysician performanceTargeted training
Designed for: CDI specialists, coding teams and physician champions.
Delivery approach
Designed around measurable decisions—not isolated AI experiments.
The delivery model prioritised trusted data, clinically meaningful workflows, model transparency and incremental adoption across hospital teams.
Human-in-the-loop by designAI recommendations support qualified teams; final clinical, coding and operational decisions remain with authorised users.
01
Discover & align
Map stakeholders, workflows, KPIs, data ownership, compliance boundaries and priority decisions across finance, operations and clinical teams.
02
Integrate & standardize
Connect EMR, billing, PACS and document sources; validate data quality; establish lineage, access rules and reusable pipelines.
03
Model & validate
Develop predictive, NLP and imaging models with domain validation, performance thresholds, explainability and controlled review.
04
Design role-based workflows
Translate intelligence into dashboards, alerts and drill-down journeys tailored to each stakeholder’s operating context.
05
Deploy, monitor & improve
Release through governed environments, monitor model and system performance, capture feedback and continuously improve outcomes.
Reported business impact
Financial, operational and clinical value in one transformation.
The source case study reports improvements across denial prevention, revenue recovery, length of stay, documentation quality and radiology response.
Reduction in claims denials
Denial rate reported to have moved from 18% to 13.9% within 12 months.
Annual revenue recovery
Attributed to better coding accuracy and earlier denial prevention.
Decrease in average LOS
Average stay reported to have reduced from 5.8 to 4.9 days.
ROI in the first 18 months
Reported across recovered revenue, operational savings and productivity gains.
22%Improvement in bed turnover
87%LOS prediction accuracy
94%AI/radiologist concordance
60%Faster coding-query turnaround
Figures shown are reported outcomes from the original DevsTree Hospital MRA case study and are presented for portfolio storytelling.
Security & governance
Enterprise intelligence with healthcare-grade controls.
The platform architecture is designed to protect sensitive clinical and financial data while maintaining model accountability, user traceability and controlled access across teams.
Protected health data
Encryption, secure storage patterns and controlled data movement across services.
Role-based authorization
Fine-grained access aligned with clinical, coding, executive and administrative responsibilities.
Model monitoring
Performance, drift, thresholds and model versions tracked through governed MLOps practices.
Auditability & lineage
Traceable user activity, source data, generated recommendations and downstream actions.
Technology stack
Scalable data engineering and decision intelligence.
The visible source stack combines object storage, distributed processing, cloud analytics and business intelligence to support high-volume multi-modal healthcare workloads.
MIN
MinIOObject storage
SPK
PySparkDistributed processing
DBX
DatabricksData & AI platform
PBI
Power BIInteractive analytics
Build with DevsTree
Turn fragmented healthcare data into trusted operational intelligence.
From healthcare data architecture and AI model development to role-based dashboards, MLOps and secure cloud deployment, DevsTree can support the complete transformation lifecycle.