The User Experience – At the Speed of Thought: Kaleida Health
公司规模
1,000+
地区
- America
国家
- United States
产品
- Tableau Version 6
技术栈
- Oracle databases
- Excel
- Data warehouse
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 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
- 商业运营
- 质量保证
用例
- 质量预测分析
- 实时定位系统 (RTLS)
服务
- 数据科学服务
关于客户
Kaleida Health is the largest health care provider in Western New York. The organization has a workforce of 10,000 employees and operates five hospitals, several clinics and nursing homes, and a visiting nurse association. It also manages millions of patient records. The organization's data warehouse is robust, but the reporting tools it was using were proving to be inadequate for its needs. The organization needed a business intelligence tool that could handle large data sets quickly and without causing frustration for its users.
挑战
Kaleida Health, the largest health care provider in Western New York, was struggling with traditional reporting tools that were inadequate for handling its large data sets. The company needed a BI tool that could process large amounts of data quickly and efficiently. The existing Oracle Reporting system was found to be clunky and unfriendly, making it difficult for non-technical staff to interpret reports. The result was that important data often went unnoticed. The company wanted a solution that could provide users with reports they could understand and interact with.
解决方案
Kaleida Health decided to create a corporate analysis department around Tableau, a business intelligence tool. The company's corporate analyst, Jennifer Keubler, spends 95 percent of her day using Tableau, primarily pulling data from Oracle databases into Excel first. For monthly analytics, she extracts data directly into Tableau from the data warehouse and is able to save and re-run queries. This is a huge time-saver when dealing with millions of records, with 40+ fields per record. The new version of Tableau eliminated the problem of slow processing. It also allowed for the linking of different tables, which Kuebler uses to merge files to an Excel table or link them to different extracts.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
HaemoCloud Global Blood Management System
1) Deliver a connected digital product system to protect and increase the differentiated value of Haemonetics blood and plasma solutions. 2) Improve patient outcomes by increasing the efficiency of blood supply flows. 3) Navigate and satisfy a complex web of global regulatory compliance requirements. 4) Reduce costly and labor-intensive maintenance procedures.
Case Study
Harnessing real-time data to give a holistic picture of patient health
Every day, vast quantities of data are collected about patients as they pass through health service organizations—from operational data such as treatment history and medications to physiological data captured by medical devices. The insights hidden within this treasure trove of data can be used to support more personalized treatments, more accurate diagnosis and more advanced preparative care. But since the information is generated faster than most organizations can consume it, unlocking the power of this big data can be a struggle. This type of predictive approach not only improves patient care—it also helps to reduce costs, because in the healthcare industry, prevention is almost always more cost-effective than treatment. However, collecting, analyzing and presenting these data-streams in a way that clinicians can easily understand can pose a significant technical challenge.
