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Allied Healthcare Professions Service Improvement Projects Regional Event Turning Data Into Knowledge Resource Pack.

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Presentation on theme: "Allied Healthcare Professions Service Improvement Projects Regional Event Turning Data Into Knowledge Resource Pack."— Presentation transcript:

1 Allied Healthcare Professions Service Improvement Projects Regional Event Turning Data Into Knowledge Resource Pack

2 2 Company Confidential Aims of the session understand how data is vital to the service improvement process introduce principles of measurement in relation to project outcomes using information for action and decision making

3 3 Company Confidential Information for action Good information is the foundation of good decision-making in every aspect of healthcare

4 4 Company Confidential Traditional NHS information target driven, standard based

5 5 Company Confidential From Data to Knowledge – A Continuous Process Subjective and judgmental Objective and analytical Data Information Intelligence Knowledge Insight Process Driven – ‘Black Box’

6 6 Company Confidential Layers of information Information Intelligence

7 7 Company Confidential Model for improvement Testing Changes Testing Changes The Plan-Do-Study-Act (PDSA) cycle is shorthand for testing a change in the real work setting — by planning it, trying it, observing the results, and acting on what is learned. This is the scientific method used for action-oriented learning Setting Aims Setting Aims Baseline your current state and set aims. The aim should be time-specific and measurable; it should also define the specific population of patients that will be affected Establishing Measures Establishing Measures Use quantitative measures to determine if a specific change actually leads to an improvement Selecting Changes Selecting Changes All improvement requires making changes, but not all changes result in improvement. Organizations therefore must identify the changes that are most likely to result in improvement Institute for Healthcare Improvement

8 8 Company Confidential Why aims? to provide a clear focus for what we are trying to achieve to prevent confusion arising between what we are trying to achieve and how we are attempting to achieve it to enable us to be clear about whether we have achieved on what we have set out to achieve

9 9 Company Confidential An effective aim statement is: Specific –covers the who, when and how it will be achieved Measurable –stated clearly written with numerical measures and stretched targets that are not achievable with the current system Agreed upon –agreement by all members of the team that the end result is desirable and achievable, and supported by clinical and managerial leaders Realistic and relevant –is practical about what can be achieved within the time available Time bound –it is clear about the time-scales for delivery within the collaborative programme

10 10 Company Confidential Why measure? measurements for judgment –where measures are used to judge against performance targets, other Trusts, etc measurements for diagnosis –where measured are used to understand the process, see if there is a problem and how big it is – useful early on in your project measurements for improvement –where a few specific measures linked to strategic and project aims, demonstrate over time whether changes are making improvements

11 11 Company Confidential Common mistakes compare this year to last year or current performance to some arbitrary fixed past value using averages does not tell you about variation collecting data because it always has been collected

12 12 Company Confidential Averages as a performance measure TrustPerformance (mins) Target (mins) Trust A40.840 Trust B35.9540 Trust C39.140

13 13 Company Confidential 0 10 20 30 40 50 60 70 80 Trust B Measurement over time Trust C Trust A

14 14 Company Confidential Walter’s golden rules data should always be presented in a way that preserves the evidence. displaying data using averages and aggregates loses the richness of the individual data points. display the individual data points (in the NHS these are often individual patients), then provides analysis to interpret what the user sees

15 15 Company Confidential 0 10 20 30 40 50 60 70 80 90 Day 1 4710131619 Seconds to answer phone Average based on first 10 days Eight one side Five down (or up) Change 1 st step – plot the dots

16 16 Company Confidential Time Observed value Statistical Process Control chart

17 17 Company Confidential Why use SPC focus attention on detecting and monitoring process variation over time distinguish special causes from common causes of variation, as a guide to local action identify where real change has taken place in a process encourage continuous improvement understand capability of process to meet targets help engage clinicians/health care professionals

18 18 Company Confidential Why focus on variation there is variation in every process variation creates uncertainty there are different types of variation there are different ways of managing variation we need to understand causes of variation to take action to reduce it introducing standardised processes helps to improve quality the root cause of delays for patients in the care system often variability, not volume the greater the variability, the more capacity we need to meet demand we create the variability through the way we organise our systems

19 19 Company Confidential Active wait in weeks Consultant B - Routine Inpatients 0 10 20 30 40 50 60 70 80 90 191725334149576573818997105113121129137145 Patients admitted January to December 2004 Weeks waited PatientsAverage (36)LCL (20) UCL (53)9 month target The erratic pattern of dots on this graph is caused by wide variation in weeks waited by consecutively admitted patients. This illustrates that patients are not being seen in turn. The tight clustering of dots around the middle red line in this graph indicates minimal variation in weeks waited by consecutively admitted patients. This illustrates that patients are being seen in turn. Active wait in weeks Consultant A - Routine Inpatient 0 10 20 30 40 50 60 17131925313743495561677379859197103109115 Patients admitted January to December 2004 Weeks waited PatientsAverage (15)LCL (0) UCL (47)9 month target Variability in waiting list management

20 20 Company Confidential Common cause or special cause variation common cause variation –predictable, consistent pattern of variation over time due to constant causes –variation is inherent in a process –eg patterns in the data such as weekend or evening effects, or peaks and troughs in demand special cause variation –unpredictable, inconsistent pattern of variation over time, can be attributed to specific events –variation is unexpected in a process –eg an RTA, member of staff off sick, equipment failure/maintenance

21 21 Company Confidential “A phenomenon will be said to be controlled when, through the use of past experience, we can predict, at least within limits, how the phenomenon may be expected to vary in the future ” Shewart - Economic Control of Quality of Manufactured Product, 1931

22 22 Company Confidential Turning data into intelligence - summary traditional measurement understanding measurement to improve systems a model for - setting aims - defining measurement systems - showing improvement (achieving outcomes) measuring, understanding and managing variation pitfalls to avoid

23 23 Company Confidential Finally Understanding variation is the key to managing chaos Walter Shewart (1930)

24 Lindsay Winterton Mobile 07801 376 011 e-mail: lindsay.winterton@frontlinemc.com


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