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Background. Requirement to reduce patient waiting timesAbsence of detailed information Data held on different systemsServices defining and managing waiting times differently. The challenge. To identify a way to measure and report patient waits using a consistent methodTo use the data produced t
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1. Using data to improve patient care The NHS Analytical Fair
9th September 2009
Leeds
2. Background Requirement to reduce patient waiting times
Absence of detailed information
Data held on different systems
Services defining and managing waiting times differently
3. The challenge To identify a way to measure and report patient waits using a consistent method
To use the data produced to begin to drive organisational service development to improve patient care
4. Using a partnership approach – key objectives agreed To introduce the concept of improving the patient journey as a means of reducing waits
To create service ownership over waiting times
To identify service improvement champions to facilitate a network for sharing ideas
To develop a user friendly accessible tool available to all staff in clinical services
To encourage more accurate data collection
5. The Service Transformation Access Report – a STAR is born The development of STAR is an example of information being used to improve patient care
STAR highlights waiting time pressures and acts as a driver for service improvement
6. So what is STAR?
7. STAR facts First web-based reporting system within Cumbria PCT to present both aggregated figures & a patient-level drill down
Need for training is minimal
Website is easily accessible cross county
No extra software required
Administering access to STAR is easy
8. This is the first page users see after they have logged in to STAR. It shows figures aggregated at specialty level:
9. Users can drill down from the specialty level view to the patient details view below. Traffic-lighting is used to highlight longer waits:
10. A separate page shows just the over 18 week waits, grouped in a way that’s helpful to managers:
11. This graph shows the trend in the number of waits over an eight week period:
12. How data captured can become useful information for managing services
How the timeliness and accuracy of data capture impacts on the information generated and the production of reports
STAR has raised awareness of
13. But STAR has led to much more…..
14. It has also led to A culture shift in the way both Service teams and Operational Managers approach waiting times.
Improved relationships between the Information Department and provider services.
Improved performance
15.
But how do we know?
16. From January 2009 the number of patients waiting: > 18 weeks has reduced from 633 to 146 > 15 weeks has reduced from 894 to 301 ‘I think STAR has enabled me as a manager to keep on top of waiting times. Our team secretary alerts us to long waiters…’ Manager
17. Long waits targeted, through services
investigating information shown on STAR.
Improved data quality, achieved through validation of
waiting lists.
19. Increased service redesign work to reduce waits
21. “ ….Data can be very powerful. When used
correctly, data becomes information and
then knowledge..... By embracing the use of
information, clinicians can bring about real
improvements for patients…..”
Dr Donal O’Donoghue
(National Director for Kidney Care)
22. Acknowledgements Cheryl Taylor - Service Improvement Lead
David Foster - Head of Information
Lin Kendall - Head of Clinical Systems Applications
Rachel Wallace - Information Officer
Cath Johnston - Data Quality Manager
23. Questions?
