Quick analysis with QlikView means shorter patient queues at Malmö University Hospital
公司规模
Large Corporate
地区
- Europe
国家
- Sweden
产品
- QlikView
技术栈
- Business Intelligence Systems
实施规模
- Departmental Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
技术
- 分析与建模 - 实时分析
适用行业
- 医疗保健和医院
用例
- 过程控制与优化
服务
- 数据科学服务
关于客户
Malmö University Hospital is a university and a regional hospital that provides basic and highly specialized medical care for 270,000 inhabitants in Malmö, Sweden. The hospital is one of the first county councils in Sweden to proactively manage its healthcare follow up process to improve the quality of patient care. The hospital wanted to introduce shorter waiting times, increase availability and guarantee equal treatment in all the clinics in the region. Being able to follow the patient’s care history puts greater demand on visibility into patient records and waiting times, which Region Skåne achieves by using the QlikView analysis tool.
挑战
Malmö University Hospital was facing challenges in managing patient waiting times and deviations. The hospital needed to gain increased control of the flow of patients. There was a need to find a cost-effective and powerful solution that allowed analysis of information from the many different systems. The Eye Clinic at Malmö University Hospital was working on how to correctly prioritize patients in terms of referral management and thereby increase accessibility. Their goal was to make a patient’s path through the healthcare process as quick and easy as possible. The clinic had problems with managing waiting times and deviations and the management needed to gain increased control of the flow of patients.
解决方案
After a thorough evaluation of different IT tools, they chose to implement QlikView. QlikView compiles information about patients and resources from different systems and makes it easy for staff to evaluate needs and more effectively utilize resources so as to optimize the use of available resources, such as personnel and equipment. Through its logical and easy-to-use interface, QlikView requires less training than traditional business intelligence systems especially at the end-user level. It is easy for new staff to get acquainted with the solution and quickly derive insights from the flow model as QlikView is so easy to use.
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.
