Pyramid insights empower Philadelphia Healthcare to take better care of clients
Company Size
1,000+
Region
- Europe
Country
- Netherlands
Product
- Pyramid
- Qlik
- Tableau
- Power BI
Tech Stack
- Business Intelligence (BI)
- Data Visualization
- Predictive Analytics
- Machine Learning
- Robotic Process Automation (RPA)
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Visualization
- Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Remote Control
Services
- Data Science Services
- System Integration
- Training
About The Customer
Philadelphia Healthcare is a non-profit organisation based in the Netherlands that supports over 9,000 clients with various disabilities across 500 locations. The organisation employs around 8,000 staff members and is supported by 6,000 volunteers, along with more than 16,000 parents and family friends. Philadelphia Healthcare aims to provide independence and the highest possible quality of care to its clients. The organisation faces challenges common in the healthcare sector, such as skills shortages and rising costs, which necessitate the smart use of resources and technology to maintain and improve service quality.
The Challenge
Philadelphia Healthcare is a non-profit organisation in the Netherlands that supports over 9,000 clients with various disabilities across 500 locations. Around 8,000 employees and 6,000 volunteers – aided by more than 16,000 parents and family friends – work hard to give clients independence and the best possible quality of care. Healthcare everywhere is under threat from skills shortage and rising costs, which means organisations like Philadelphia must be smart in the how they maximise resources. Jasper Drenth, Manager of Data Delivery & Analytics, recognised the part that better BI can play in keeping services affordable with less people. An obstacle to this strategy was siloed reporting systems that stored many versions of the truth. Different departments were getting different answers to the same questions. To help them on the journey to a single source of truth, a broad range of BI tools was evaluated, including Qlik, Tableau and Power BI. Pyramid was chosen, according to Drenth, because Pyramid’s people did a better job of mapping its solution to the challenges of the organisation.
The Solution
Making the same data available to everyone was one part of a transition made possible by Pyramid; the other was intuitive dashboards that carers, not just data experts, could use. The goal was to democratise data and make it useful to as many people as possible in the organisation. A measure of success is that Pyramid has grown from 300 end users to over 6,000. What started as a BI tool for Finance, Planning and the Board has quickly grown. Each care team now has access to their own dashboards, where they can explore simple-to-digest visual information and less static reports. Crucially, they can access them directly, rather than have to wait for monthly reports. Armed with a new BI tool, one goal was to drive best practice and consistency across a country-wide organisation. A user-friendly, highly visualised dashboard was developed that shows Key Performance Indicators (KPIs) to managers who are often responsible for more than one care location. The goal was to provide them with the right information at the right time and help identify problems areas.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
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.
