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Using data to improve patient care

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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Using data to improve patient care

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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 thats 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 ODonoghue (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?

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