University of Iowa Hospitals and Clinics Transforms the O.R.
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- TIBCO Statistica
技术栈
- Predictive Analytics
- Real-Time Data Processing
- Data Aggregation
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
技术
- 分析与建模 - 预测分析
- 分析与建模 - 实时分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 医疗保健和医院
适用功能
- 质量保证
- 商业运营
用例
- 预测性维护
- 远程病人监护
- 临床图像分析
服务
- 软件设计与工程服务
- 系统集成
关于客户
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.
挑战
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.
解决方案
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.
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