Healthcare & Life Sciences

Emergency Department Performance Analytics Platform

A Microsoft Fabric and Power BI analytics platform helped a multi-specialty healthcare network reduce emergency department wait times by approximately 34%.

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data
0%
Reduction in patient wait time
0%
Reduction in manual reporting effort
Real Time
Operational decision-making

Client Profile

A global enterprise in the IT services sector, operating across North America and managing a complex IT environment. The client partnered with Softree Technology to leverage Emergency Department Performance Analytics Platform for improved IT service management and operational efficiency.

Use Cases
Operations, Healthcare Analytics, Patient Flow Optimization
Industry
Healthcare & Life Sciences
Project Type
Emergency Department Performance Analytics Platform
Scale of Operation
Large multi-specialty healthcare network operating multiple hospitals and emergency departments.
End Users
Emergency Department Leadership, Clinical Staff, and Operations Teams
Service Provided
Data EngineeringMicrosoft FabricPower BI DevelopmentHealthcare AnalyticsData Visualization
The Client Challenge

Business Process Challenges

A large multi-specialty healthcare network operating multiple hospitals and emergency departments lacked unified visibility into patient flow, resource utilization, and service performance. Clinical, operational, and capacity data was fragmented across different system and facilities.

Emergency department leaders faced long patient wait times, overcrowding, delayed triage, inconsistent bed utilization, and limited operational visibility. Manual spreadsheet-based reporting often surfaced operational issues a full day after they occurred, making it difficult for teams to respond quickly.

Emergency department leaders faced several operational challenges:

  1. Long patient wait times made it difficult to maintain efficient patient movement through emergency departments.
  2. Emergency department overcrowding created pressure on available beds, clinical teams, and supporting resources.
  3. Delayed triage limited the ability of teams to quickly identify and prioritize patients requiring attention.
  4. Inconsistent bed utilization made it difficult to understand available capacity and allocate beds effectively.
  5. Limited operational visibility prevented leaders from getting a consolidated view of performance across hospitals and facilities.
  6. Manual spreadsheet-based reporting required teams to collect and consolidate information from different sources.
  7. Delayed reporting cycles often surfaced operational issues a full day after they occurred, reducing the ability to respond proactively.
  8. Fragmented clinical and operational data made it difficult to identify bottlenecks, understand demand patterns, and coordinate resources across facilities.
Our Approach

Our Strategic Approach

Softree developed a governed, scalable analytics platform using Microsoft Fabric and Power BI. Data from EHR, ambulance, laboratory, radiology, staffing, and bed-management systems was unified in OneLake through Microsoft Fabric Data Factory pipelines.

The solution used Lakehouse and Warehouse layers for curated and governed datasets, while Power BI semantic models powered executive, departmental, and shift-level dashboards. Microsoft Entra ID authentication and Row-Level Security provided controlled access to analytics across the organization.

Our Solution Architecture

How we delivered it.

MF
Microsoft Fabric
Integrated Microsoft Fabric layer in the solution architecture.
O
OneLake
Integrated OneLake layer in the solution architecture.
DF
Data Factory
Integrated Data Factory layer in the solution architecture.
L
Lakehouse
Integrated Lakehouse layer in the solution architecture.
W
Warehouse
Integrated Warehouse layer in the solution architecture.
RI
Real-Time Intelligence
Integrated Real-Time Intelligence layer in the solution architecture.
PB
Power BI
Integrated Power BI layer in the solution architecture.
PQ
Power Query
Integrated Power Query layer in the solution architecture.
DG
Dataflows Gen2
Integrated Dataflows Gen2 layer in the solution architecture.
S
SQL
Integrated SQL layer in the solution architecture.
D
DAX
Integrated DAX layer in the solution architecture.
SM
Semantic Models
Integrated Semantic Models layer in the solution architecture.
SD
Star-Schema Design
Integrated Star-Schema Design layer in the solution architecture.
MEI
Microsoft Entra ID
Integrated Microsoft Entra ID layer in the solution architecture.
RS(
Row-Level Security (RLS)
Integrated Row-Level Security (RLS) layer in the solution architecture.
Visual Proof

Explore the Solution Through visuals

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The Outcome

What changed for the client.

The platform delivered near real-time operational visibility across emergency departments and improved the speed of data-driven decision-making. Patient wait times were reduced by approximately 34%, while manual reporting effort decreased from around 22 hours per week to under 6 hours per week.

The governed Microsoft Fabric data foundation also created an AI-ready environment for future predictive and AI related healthcare operations.

Results & Business Impact

The numbers behind the rollout.

01
Reduction in patient wait time
35%
02
Reduction in manual reporting effort
80%
03
Operational decision-making
Real Time
Reference Tech Stack

The full integration layer.

Microsoft Fabric
OneLake
Data Factory
Lakehouse
Warehouse
Real-Time Intelligence
Power BI
Power Query
Dataflows Gen2
SQL
DAX
Semantic Models
Star-Schema Design
Microsoft Entra ID
Row-Level Security (RLS)
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FAQ

Frequently asked questions.

Softree delivers custom solutions across AI and automation, Power Platform, SharePoint customization, full-stack web and SaaS engineering, and data analytics.
We combine modern software engineering standards, secure cloud configurations, pre-built accelerators, and agile delivery methodologies to produce governed, scalable applications.
Our agile delivery model typically produces scoped initial MVPs in 4 to 8 weeks, with comprehensive enterprise deployments completed in 10 to 12 weeks.
Yes. We design and build secure custom API gateways, REST connectors, and database bridges to ensure our custom solutions integrate seamlessly with your existing legacy infrastructure.

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