Healthcare

How a Multi-Hospital Healthcare Network Unified Patient Intelligence,
Reduced Claims Denials, and Enabled Real-Time Healthcare Analytics with Microsoft Fabric

Built an AI-powered healthcare intelligence platform that reduced claims denials from 18% to 8% and accelerated reporting from 14 days to 1 day.

softreetechnology.com/case-studies
Healthcare executives using Microsoft Fabric-powered patient intelligence dashboards to monitor clinical, financial, and operational performance.
0% Claims Denial Reduction
Claims Denial Reduction
0-Day Executive Reporting
1-Day Executive Reporting
0% Better Risk Prediction
30% Better Risk Prediction

Client Profile

A mid-market enterprise in the IT services sector, operating across North America and managing a complex IT environment. The client partnered with Softree Technology to leverage Healthcare Patient Intelligence Platform for improved IT service management and operational efficiency.

Use Cases
Healthcare Analytics & AI-Powered Patient Intelligence
Industry
Healthcare
Project Type
Healthcare Data Modernization & AI-Powered Patient Intelligence Platform
Scale of Operation
Serving over 3 million patients annually across multiple hospitals, specialty clinics, and care facilities with unified clinical, financial, and operational intelligence.
End Users
5,000+ Clinical, Operational, and Executive Users These values align well with the enterprise-scale healthcare transformation described in the case study and create a credible Fortune 1000 / large health system profile.
Service Provided
Healthcare Data ModernizationMicrosoft Fabric ImplementationAI & Machine LearningData EngineeringHealthcare AnalyticsExecutive ReportingPower BI DevelopmentData Governance
The Client Challenge

Business Process Challenges

  1. Integrated data across multiple hospitals, clinics, and care facilities using EMR, EHR, claims, and operational systems.
  2. Unified patient, clinical, financial, and operational data to provide a comprehensive view of healthcare performance.
  3. Enabled better identification of high-risk patients, readmission risks, and care gaps.
  4. Streamlined clinical and operational data consolidation to support faster, proactive care decisions.
  5. Addressed an 18% claims denial rate and improved visibility into billing inefficiencies and revenue leakage.
  6. Reduced dependency on manual executive reporting by consolidating data from previously siloed systems.
  7. Improved reporting efficiency from cycles exceeding 14 days through centralized and automated analytics.
  8. Established a scalable healthcare analytics foundation to support value-based care and AI-driven decision-making.
Our Approach

Our Strategic Approach

  1. Designed and implemented a Healthcare Patient Intelligence Platform using Microsoft Fabric for clinical, financial, and operational analytics.
  2. Consolidated data from EMR/EHR systems, FHIR APIs, claims platforms, laboratory systems, and operational applications into a unified environment.
  3. Leveraged Microsoft Fabric OneLake and Spark-based processing to establish a centralized healthcare data foundation.
  4. Implemented automated data pipelines for near real-time data ingestion, transformation, and governance.
  5. Applied AI/ML and predictive analytics for patient readmission risk, ICU escalation, chronic disease progression, and population health management.
  6. Developed Power BI dashboards with role-based insights for clinicians, operational leaders, and executives.
  7. Integrated Microsoft Purview for data governance, compliance, security, and end-to-end data lineage.
  8. Built a scalable and secure architecture to support healthcare analytics, AI adoption, and improved operational outcomes.
Our Solution Architecture

How we delivered it.

PA
Power Apps
Integrated Power Apps layer in the solution architecture.
PA
Power Automate
Integrated Power Automate layer in the solution architecture.
D
Dataverse
Integrated Dataverse layer in the solution architecture.
PB
Power BI
Integrated Power BI layer in the solution architecture.
S
SharePoint
Integrated SharePoint layer in the solution architecture.
A
Azure
Integrated Azure layer in the solution architecture.
Visual Proof

Explore the Solution Through visuals

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The Outcome

What changed for the client.

  1. Reduced executive reporting cycles from 14 days to just 1 day, enabling faster access to critical insights.
  2. Improved AI-powered patient risk prediction accuracy by 30%, supporting earlier identification of high-risk patients.
  3. Reduced claims denials from 18% to 8%, improving financial performance.
  4. Lowered revenue leakage from 14% to 4% through improved billing and financial visibility.
  5. Shortened reimbursement cycles from 45 days to 12 days.
  6. Reduced manual processing from 70% to 15%, allowing teams to focus on higher-value activities.
  7. Improved visibility into bed utilization, staffing efficiency, patient flow, and departmental performance.
  8. Established a scalable analytics foundation to support future GenAI clinical copilots, predictive workforce optimization, remote patient monitoring, and personalized care pathways.
Results & Business Impact

The numbers behind the rollout.

01
Claims Denial Reduction
10% Claims Denial Reduction
02
1-Day Executive Reporting
1-Day Executive Reporting
03
30% Better Risk Prediction
30% Better Risk Prediction
Reference Tech Stack

The full integration layer.

Power Apps
Power Automate
Dataverse
Power BI
SharePoint
Azure
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FAQ

Frequently asked questions.

Microsoft Fabric provided a unified platform for integrating EMR, claims, operational, and financial data into a single source of truth. Its built-in analytics, AI capabilities, governance features, and seamless Power BI integration enabled the organization to eliminate data silos while accelerating reporting and decision-making.
AI-powered predictive models helped identify patients at risk of readmission, ICU escalation, and chronic disease progression before critical events occurred. This allowed clinical teams to take proactive actions, while operational leaders benefited from improved staffing, bed utilization, and patient flow management through predictive analytics.
The platform delivered significant improvements across clinical, financial, and operational functions, including reducing executive reporting time from 14 days to 1 day, lowering claims denials from 18% to 8%, decreasing revenue leakage from 14% to 4%, and improving patient risk prediction accuracy by 30%, resulting in faster decisions and better healthcare outcomes.

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