How should we measure ambulance service quality and performance?

Coster, Jo, Turner, Janette, Irving, Andy , Wilson, Richard, Siriwardena, A. Niroshan and Phung, Viet-Hai (2014) How should we measure ambulance service quality and performance? In: International Conference on Emergency Medicine, 11-14 June 2014, Hong Kong Convention and Exhibition Centre.

How should we measure ambulance service quality and performance?
PDF (Poster)
ICEM2014_Delphi.pdf - Presentation
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Item Type:Conference or Workshop contribution (Poster)
Item Status:Live Archive


The problem
Ambulance services in England treat 6.5 million people per year but get no information about what happens to patients after discharge. This has led to a reliance on measuring response times rather than outcomes to assess how well services perform, and little opportunity for identifying problems and good practice or evaluating service developments.
Research aim
There is a lack of consensus on which outcome measures are important for pre-hospital care so we set out to address this within the Prehospital Outcomes for Evidence Based Evaluation (PhOEBE) research programme.
We conducted a two round Delphi study to prioritise outcome measures identified from a systematic review and a multi-stakeholder consensus event. 20 participants scored 57 measures over two rounds. Participants included policy makers and commissioners, clinical ambulance service and ambulance service operational groups. Outcomes were scored in three categories: patient outcomes; whole service measures and clinical management.
Highly ranked patient outcome measures related to pain, survival, recontacts and patient experience. High ranking outcomes in the Clinical Management group related to compliance with protocols and guidelines and appropriateness and accuracy of triage. In the Whole Service measures group highly ranked measures related to completeness of clinical records, staff training and time to definitive care.
The next steps are to identify which measures are suitable for measuring with routine data; use a linked dataset to build predictive models and determine what aspects of care can predict good or poor outcomes (mortality and non-mortality); measure the effectiveness and quality of ambulance service care, and; assess the practical use of the measures and the linked data as a way to support quality improvement in the NHS.

Keywords:Emergency Medical Systems, ambulance services, quality, performance, data, Delphi study, consensus methods
Subjects:B Subjects allied to Medicine > B990 Subjects Allied to Medicine not elsewhere classified
A Medicine and Dentistry > A300 Clinical Medicine
Divisions:College of Social Science > School of Health & Social Care
ID Code:16213
Deposited On:09 Dec 2014 21:18

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