Qlik > Case Studies > Colchester University Hospital Tames Big Data to Deliver Excellence in Healthcare with QlikView

Colchester University Hospital Tames Big Data to Deliver Excellence in Healthcare with QlikView

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Customer Company Size
Large Corporate
Region
  • Europe
Country
  • United Kingdom
Product
  • QlikView
Tech Stack
  • SAP
  • Movex DW/BI
  • Cognos
  • Oracle
  • Excel
  • IBM iSeries
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Cost Savings
  • Customer Satisfaction
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Real Time Analytics
Applicable Industries
  • Healthcare & Hospitals
Applicable Functions
  • Business Operation
  • Quality Assurance
Use Cases
  • Predictive Quality Analytics
  • Real-Time Location System (RTLS)
  • Remote Asset Management
Services
  • Data Science Services
  • System Integration
About The Customer
Colchester Hospital University NHS Trust (CHUFT) is an acute NHS Foundation dedicated to providing healthcare that consistently delivers an exceptional patient experience. The system of hospitals focuses on meeting the lifelong healthcare needs of the population by offering a full range of specialty care services, including technically advanced inpatient and outpatient care, 24-hour emergency care, oncology, pharmacy, and home and community services. The Trust provides healthcare services to over 370,000 people from Colchester and the surrounding area of North East Essex. CHUFT is committed to providing welcoming, kind, involving, responsive, professional and quality care to its patients. The Trust is nationally recognized for operational excellence in healthcare throughout the United Kingdom.
The Challenge
Colchester Hospital University NHS Trust (CHUFT) was struggling with managing big data and extracting valuable insights. The organization was dealing with over 2,000 reports per day and 140GB of data per week, which made timely and accurate reporting critical for their decision-making process. The existing system was limited in content, flexibility, and visibility across the organization. Reports were often out of date and reflected incorrect and inconsistent patient information. The hospital needed a solution to efficiently and accurately analyze data, particularly related to mortality rates and oncology treatment.
The Solution
In early 2011, CHUFT deployed QlikView, a leading provider of Business Discovery – user-driven BI – to tackle the hospital’s big data concerns. QlikView helped transform CHUFT’s analytics almost instantly, with the Trust rolling out new dashboards to improve patient care each month. The suite of applications which were developed included business-critical dashboards for functions like cancer patient wait times, patient arrivals and departures, mortality rates, and readmissions. The QlikView applications have helped to identify inaccuracies in clinical coding and patient care. CHUFT has been able to see where patients are admitted, their diagnosis, as well as what procedures they’ve had and the outcome of those procedures. Physicians can use that information to decide on the most appropriate and safest path of care, equipped with a host of background information. Further, the applications trigger alerts when patients fall outside of their key pathway milestones allowing for early intervention and management.
Operational Impact
  • QlikView has empowered CHUFT's daily operations and fundamentally changed the way they use information.
  • The deployment has immensely changed the culture of the organization, and with over 235 active daily users, CHUFT now has the tools it needs to inform excellent and efficient patient care.
  • For the first time in the Trust’s history, clinicians are able to instantly benchmark themselves against their peers using real-time intelligence on length of stay, readmissions, mortality, admissions and more.
  • The Patient Safety team is now completely reliant on QlikView for its investigations into mortality, which are reviewed on a weekly basis.
Quantitative Benefit
  • Reduced reporting time from 231 hours per month to 54 hours per month.
  • Achieved annual efficiency and productivity savings of £45,924.
  • Reduced the number of deaths by 158 per year.

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