TIBCO Software Case Studies University of Iowa Hospitals and Clinics Transforms the O.R.

	University of Iowa Hospitals and Clinics Transforms the O.R. TIBCO Software

University of Iowa Hospitals and Clinics Transforms the O.R.

TIBCO Software

Technology Category	Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries	Healthcare & Hospitals
Applicable Functions	Business Operation Quality Assurance
Use Cases	Clinical Image Analysis Predictive Maintenance Remote Patient Monitoring
Services	Software Design & Engineering Services System Integration
Challenge	In the United States, roughly one in 20 patients admitted to a hospital develops an infection, with surgical site infections being the most common. These infections account for more than 30 percent of occurrences, leading to illness, prolonged hospitalization, and even death. The total cost of hospital-acquired infections is estimated at $10 billion per year. Surgeons at the University of Iowa Hospitals and Clinics wanted to know when patients were susceptible to surgical infections to make critical treatment decisions in the operating room. Dr. John Cromwell believed that predictive analytics could prevent a high percentage of surgical site infections and decrease healthcare costs. However, the division’s desktop analytics environment could not handle large distributed data volumes, posing a major roadblock. Read More
About Customer	The University of Iowa Hospitals and Clinics is one of the most highly regarded medical facilities in the United States. It is known for its advanced medical care and research capabilities. The hospital is committed to improving patient outcomes and reducing healthcare costs through innovative solutions. Dr. John Cromwell, the director of gastrointestinal, minimally invasive, and bariatric surgery, leads a team dedicated to leveraging predictive analytics to enhance patient care. The hospital's senior application developer, Jose Maria Monestina, plays a crucial role in implementing advanced analytics technologies to support the hospital's mission. Read More
Solution	To address the challenge, the team needed a flexible, enterprise-grade, advanced analytics platform that encompassed the entire analytics lifecycle. They implemented TIBCO Statistica technology to predict outcomes for Dr. Cromwell’s team. This platform allowed them to connect to disparate enterprise systems and bring the data into a common data set with embedded analytical tools. By moving from desktop to enterprise analytics, they turned prediction theory into a life-enhancing reality in the operating room. The team used patient healthcare data, historical data, and real-time data to create predictive models. This combination allowed them to deliver predictive analytics in a real-time environment, improving healthcare outcomes. The Statistica tools enabled them to manage the ever-increasing types of data that healthcare institutions are tasked with, keeping track of various models needed for predictive analytics. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Industries

Healthcare & Hospitals

Applicable Functions

Business Operation

Quality Assurance

Use Cases

Clinical Image Analysis

Predictive Maintenance

Remote Patient Monitoring

Services

Software Design & Engineering Services

System Integration

Challenge

In the United States, roughly one in 20 patients admitted to a hospital develops an infection, with surgical site infections being the most common. These infections account for more than 30 percent of occurrences, leading to illness, prolonged hospitalization, and even death. The total cost of hospital-acquired infections is estimated at $10 billion per year. Surgeons at the University of Iowa Hospitals and Clinics wanted to know when patients were susceptible to surgical infections to make critical treatment decisions in the operating room. Dr. John Cromwell believed that predictive analytics could prevent a high percentage of surgical site infections and decrease healthcare costs. However, the division’s desktop analytics environment could not handle large distributed data volumes, posing a major roadblock.

About Customer

The University of Iowa Hospitals and Clinics is one of the most highly regarded medical facilities in the United States. It is known for its advanced medical care and research capabilities. The hospital is committed to improving patient outcomes and reducing healthcare costs through innovative solutions. Dr. John Cromwell, the director of gastrointestinal, minimally invasive, and bariatric surgery, leads a team dedicated to leveraging predictive analytics to enhance patient care. The hospital's senior application developer, Jose Maria Monestina, plays a crucial role in implementing advanced analytics technologies to support the hospital's mission.

Solution

To address the challenge, the team needed a flexible, enterprise-grade, advanced analytics platform that encompassed the entire analytics lifecycle. They implemented TIBCO Statistica technology to predict outcomes for Dr. Cromwell’s team. This platform allowed them to connect to disparate enterprise systems and bring the data into a common data set with embedded analytical tools. By moving from desktop to enterprise analytics, they turned prediction theory into a life-enhancing reality in the operating room. The team used patient healthcare data, historical data, and real-time data to create predictive models. This combination allowed them to deliver predictive analytics in a real-time environment, improving healthcare outcomes. The Statistica tools enabled them to manage the ever-increasing types of data that healthcare institutions are tasked with, keeping track of various models needed for predictive analytics.

Impact #1	The team was able to connect to disparate enterprise systems and bring the data into a common data set with embedded analytical tools.
Impact #2	They moved from desktop to enterprise analytics, turning prediction theory into a life-enhancing reality in the operating room.
Impact #3	The use of predictive analytics allowed them to manage the ever-increasing types of data that healthcare institutions are tasked with.

Impact #1

The team was able to connect to disparate enterprise systems and bring the data into a common data set with embedded analytical tools.

Impact #2

They moved from desktop to enterprise analytics, turning prediction theory into a life-enhancing reality in the operating room.

Impact #3

The use of predictive analytics allowed them to manage the ever-increasing types of data that healthcare institutions are tasked with.

Benefit #1	Reduced surgical site infections by about 58%.

Benefit #1

Reduced surgical site infections by about 58%.

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Overview

University of Iowa Hospitals and Clinics Transforms the O.R.

Operational Impact

Quantitative Benefit