NHS Improvement An Overview of Statistical Process Control (SPC) October 2011

Similar documents
Online Student Guide Types of Control Charts

How Will You Know That a Change Is An Improvement?

CMIP Performance Measure Trend Report Guide Disease Specific Care (DSC) Certified Program Rates and National/State Overall Rates

Online library of Quality, Service Improvement and Redesign tools. Run charts. collaboration trust respect innovation courage compassion

Use and interpretation of statistical quality control charts

Strategies for Improvement of Process Control

Quality Management (PQM01) Chapter 04 - Quality Control

Introduction to Control Charts

PDCA/Process Improvement

A Practical Guide to Selecting the Right Control Chart

GUIDANCE ON CHOOSING INDICATORS OF OUTCOMES

Computer Science and Software Engineering University of Wisconsin - Platteville 3. Statistical Process Control

Quality Control Troubleshooting Tools for the Mill Floor

Understanding Variation

CONTROL CHART. We have what it takes! Continuous quality improvement - our tool for delivering... service of greater worth.

INTI COLLEGE MALAYSIA DIPLOMA IN ENGINEERING PROGRAMME EGR 286 : PRODUCTION PLANNING & CONTROL FINAL EXAMINATIION : AUGUST 2002 SESSION

Introduction to STATISTICAL PROCESS CONTROL TECHNIQUES. for Healthcare Process Improvement

NHS Improvement Overview Change Management the Systems and Tools for Managing Change October 2011

Statistics Quality: Control - Statistical Process Control and Using Control Charts

Process Performance and Quality Chapter 6

Application of statistical tools and techniques in Quality Management

Process Performance and Quality

LO1: Understand how inspection and testing methods and processes improve quality control

Quality Management. It costs a lot to produce a bad product. Norman Augustine

Describe the impact that small numbers may have on data

Lecture Notes on Statistical Quality Control

1. Control Charts. Control charts can be used to: Assess process stability Assess process capability Aid in process improvement

Welcome and thank you for joining us. Bienvenue et merci de vous joindre à nous. We will begin shortly

Sample Mean Range

The Importance of Understanding Type I and Type II Error in Statistical Process Control Charts. Part 1: Focus on Type 1 Error

An Introductory Guide. For Clinicians & Service Managers CAPACITY FOR PSYCHOLOGICAL THERAPIES SERVICES. By The Mental Health Collaborative

Welcome and thank you for joining us. Bienvenue et merci de vous joindre à nous. We will begin shortly

Chapter 5 Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc.

Sources of Variation in Manufacturing and Service Processes

AS Module 2 (I CT4): Topic 13.3 Corporate Information Systems Strategy

Using Data to Guide improvement. Objectives

BraindumpStudy. BraindumpStudy Exam Dumps, High Pass Rate!

Continuous Improvement Toolkit

Workshop 5. Managing Quality. Kate Hughes & John Whiteley

Assignment 5: Statistical Process Controls. Laura M Williams, RN, CLNC, MSN. IET603: Statistical Quality Assurance in Science and Technology

Statistical Process Control

Chapter 8 Variability and Waiting Time Problems

Data and Measurement: How we put run chart theory into practice for improvement projects. June 2017

Learning about Clinical Trials

SPC for Right-Brain Thinkers

Statistical process control as a tool for research and healthcare improvement ...

Quality Initiatives. Statistical Control Charts: Simplifying the Analysis of Data for Quality Improvement 1

International Program for Development Evaluation Training (IPDET)

Capability on Aggregate Processes

Operations and Supply Chain Management Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras

An Introductory Guide. For Clinicians & Service Managers IMPROVING ACCESS TO PSYCHOLOGICAL THERAPIES SERVICES START HERE

Chapter 1. Introduction

To provide a framework and tools for planning, doing, checking and acting upon audits

Engenharia e Tecnologia Espaciais ETE Engenharia e Gerenciamento de Sistemas Espaciais

ISHIKAWA S 7 TOOL OF QUALITY PARETO DIAGRAMS AND CONTROL CHARTS NEFİSE M. NABİ

November This is a joint programme between Demand and Capacity Trainer Programme Student Prospectus NHS England and NHS Improvement

Using the Power of Statistical Thinking

YOU WON T FALL. WITH RUN CHARTS

Lean Six Sigma Green Belt Supplement

SHN! Atlantic Sustainability and Spread October 2012

Genetic Treatment. Germ-line Genetic Therapy. Munson-Davis Look Bravely at a Brave New World. Enhancement. Curing Disease. Somatic cell.

Build Trust in Survey Responses Sample Selection & Sample Size

Discover the Journey to Work

36.2. Exploring Data. Introduction. Prerequisites. Learning Outcomes

Daniel Y. Peng, Ph.D.

MAY 2016 Report Number: NHSE009

TALENT PIPELINE MANAGEMENT ACADEMY. Strategy 6: Continuous Improvement

Before You Start Modelling

Lesson 14 Statistical Process Control

INVENTORY CURRENT VALUE

Toolkit. The Core Characteristics of a Great Place to Work Supporting Framework and Tools. Author: Duncan Brodie

Topic 02 Biomedical Data

Challenges faced when taking strategic decisions. Results of 2010 Global Survey. Executive Summary

Handy guide to calculating new to follow-up ratios

Department of Industrial Engineering Short Learning Programmes 2014

Statistical Process Control Seminar at Jireh Semiconductor. Topic Agenda

SELECTED APPLICATIONS OF STATISTICAL PROCESS CONTROL IN METALLURGY. Darja NOSKIEVIČOVÁ

provided that the population is at least 10 times as large as the sample (10% condition).

Sawtooth Software. Sample Size Issues for Conjoint Analysis Studies RESEARCH PAPER SERIES. Bryan Orme, Sawtooth Software, Inc.

Technical Features Sound Construction Design Aid For Office Acoustics

Big Tent S&OP: Expanding the Scope of a Critical Process

WEQAS: what is it and what does it mean?. Celia Critchley Point of Care Co-ordinator Warrington and Halton Hospitals NHS Foundation Trust

Compliance Issue Analysis

The materials required over the next two modules include:

QUALITY IMPROVEMENT FORM

How To Design A Clinical Trial. Statistical Analysis. Gynecologic Cancer InterGroup

Strategy 6 Table of Contents

Understanding Variation and Statistical Process Control: Variation and Process Capability Calculations

AD-A DEFENSE CONTRACT MANAGEMENT COMMAND DATA VALIDATION FILTER June 1993 DTIC - T. S, ELECT-rE DLA-93-P30054 N1) DEFENSE LOGISTICS AGENCY

Chapter 9A. Process Capability & SPC

Policy as imagined and practiced in the Emergency Department

Chapter 6 - Statistical Quality Control

John G. Surak PhD Surak and Associates Clemson, SC

Equipment and preparation required for one group (2-4 students) to complete the workshop

Applying Statistical Techniques to implement High Maturity Practices At North Shore Technologies (NST) Anand Bhatnagar December 2015

Chapter 4: Foundations for inference. OpenIntro Statistics, 2nd Edition

Sensitizing Rules for Fuzzy Control Charts

Improving forecast quality in practice

PROPENSITY SCORE MATCHING A PRACTICAL TUTORIAL

Cork Regional Technical College

Transcription:

NHS Improvement An Overview of Statistical Process Control (SPC) October 2011

Statistical Process Control Charts (X, Moving R Charts) What is Statistical Process Control (SPC)? We all know that measurement is integral to the improvement methodology in healthcare but how do we know whether or not we have actually made a difference and if the care being delivered is getting better, staying the same or getting worse each year? What we do not always take into account is the variation in the way that services are delivered by individual departments, people and even different types of equipment. All of these differences in the way things are done lead to differences in the way services are delivered. The main aims of using Statistical Process Control (SPC) charts is to understand what is different and what is the norm. By using these charts, we can then understand where the focus of work needs to be concentrated in order to make a difference. We can also use SPC charts to determine if an improvement is actually improving a process and also use them to predict statistically whether a process is capable of meeting a target. SPC charts are therefore used: As way of demonstrating and thinking about variation As simple tool for analysing data measurement for improvement As a tool to help make better decisions - easy and sustainable to use The way in which data within healthcare is traditionally analysed leads to confusion and inaccuracy. The simple fact that important operational decisions are often made from data where there is limited understanding of the process and its variation is often worrying. If individuals do not understand variation, they often look at data (as in the chart below) and: They see trends where there are no trends They try to explain natural variation as special events They blame and give credit to people for things over which they have no control They can t understand past performance They can t make predictions or plan for the future Their ability to make improvements is limited NHS Improvement 2 August 2011

ABSENTEEISM BY DEPARTMENT 14 12 10 8 6 4 2 0 January May September January A B C D E F G H Variation There are two types of variation found within SPC charts: Natural (common cause) variation Is inherent in the design of the process Results in a stable IN CONTROL process because the variation is predictable Is due to random or chance causes of variation 80 70 60 50 40 30 20 10 0 F M A M J J A S O N D J F M A M J J A S O N D NHS Improvement 3 August 2011

Special cause variation Is due to irregular or unnatural causes that are not inherent in a process - extrinsic Results in an unstable OUT OF CONTROL process because variation is not predictable Is due to non-random or assignable causes of variation (i.e. a signal that the process has changed ) 90 80 70 60 50 40 30 20 10 0 F M A M J J A S O N D J F M A M J J A S O N D Control Charts vs. Run Charts Run charts have traditionally been used in service improvement to measure changes in a process over time. There is however marked differences between run charts and SPC charts in addition to the mean or average, control charts have 2 extra lines that are calculated using modified statistics and these determine the variation range. These lines are commonly referred to as the Upper Control Limit (UCL) the upper line, and Lower Control Limit (LCL) the lower line. SPC charts require an absolute minimum of 10 data points in order to create a valid chart, although there is increased reliability when using 20 or more data points. Data should also be plotted chronologically in date or process order and ideally represent an individual as opposed an aggregate value. In summary, control charts: Are more sensitive than run charts a run chart cannot detect special causes due to point to point variation or use rules for detecting special causes Have the added feature of control limits which estimate natural variation Define process capability Allow us to more accurately predict process behavior NHS Improvement 4 August 2011

What can SPC do for you? SPC charts have multiple uses but in summary can be used: To identify if a process is sustainable - i.e. are your improvements sustaining over time To identify when an implemented improvement has changed a process - i.e. it has not just occurred by chance To understand that variation is normal and to help reduce it To generally understand processes - helping make better predictions and thus improve decision making To recognise abnormalities within processes To prove or disprove assumptions and (mis) conceptions about services To drive improvement used to test the stability of a process prior to redesign work, such as Demand and Capacity Further practical applications of SPC charts include the ability to calculate a recommended capacity based on demand by using the charts to plot daily demand over time. What will SPC not do for you? SPC charts are very useful, but they will not: Solve your process issues you will need background intelligence in order to understand the process for potential redesign Provide all the answers SPC analysis is a tool to compliment all other methodologies i.e. process mapping and discovery interviews Validate data SPC is only as valid as the data used How do I create an SPC chart? SPC charts can be created manually but this tends to be a rather laborious exercise. There is a host of software available commercially than can create these and many other types of SPC charts for you from the data you enter. You can however use the NHS Improvement System to create both SPC and Capacity charts subject to your access agreement to the system. If you are interested in the calculations used to create an SPC chart (which can be done in excel for example), they are as follows: Use individual values to calculate the average NHS Improvement 5 August 2011

Calculate the difference between 2 consecutive values for all of the values as the moving range mr these values are always i.e. the difference between 5 and 6 = 1 and the difference between 7 and 0 = 7 Calculate the average mr Calculate one Sigma = Average mr/d2* Calculate the Upper Control Limit (UCL) = Average + (3 x Sigma) Calculate the Lower Control Limit (LCL) = Average (3 x Sigma) *The bias correction factor, d2 is a constant for given subgroups of size n (n = 2, d2 = 1.128) What do I do next? Once you have a chart, you will need to understand what it means in order to determine your next course of action. Initially you will be looking to see if a chart contains special cause variation or natural variation is the process in control or out of control. You need to remember that a process containing special cause variation is unpredictable and the data should not be used to reliably calculate a processes capability. Is the initial process stable? Yes No Type of variation Natural (common) Special + natural Right Choice Wrong Choice Consequences of making the wrong choice Change the process Treat normal variation as a special cause (tampering) Increased variation Investigate the origin of the special cause(s) Change the process Wasted resources NHS Improvement 6 August 2011

Determining the type of variation contained within a process is crucial at this stage (see chart above) as your intervention could lead to increased variation or wasted resources if you take the wrong course of action. This is why it is sometimes better to use SPC to determine the type of variation before any service improvement work i.e. demand and capacity. You should then develop improvement strategies - improvement strategies are determined by the sources of variation. Special cause variation investigate and find out why it exists and what each special cause data point may mean - remember that not every special cause is a negative factor as by redesigning the process, you are inadvertently introducing special cause variation Natural (common cause) variation change the process if you want to improve - Reduce the amount of variation by redesigning the process The control limits will give you a reliable indication in terms of the overall variation within the process. For example, the chart below represents a call to needle process where individual patient call to needle times have been plotted chronologically over time. While the average time is 50.64 minutes, the variation is between 0 and 106.93 minutes. This would indicate that any patient entering this process could expect to wait between 0 and 107 minutes to receive thrombolysis treatment from their point of call. Special cause variation points have also been flagged which would require further investigation in order to understand this process. NHS Improvement 7 August 2011

There are different types of special cause variation points found within SPC charts some software automatically highlights these points for you, such as the NHS Improvement System, but you can find more details about SPC by using the links to further resources within this section. You can then continue to use SPC charts to see if there has been an improvement in the process. Usually as this occurs over time, you will see the overall variation reducing and the process capability increasing. SPC charts should not be considered as a one-off methodology but used continually to monitor a processes performance and to measure for improvement Process Capability SPC charts can also enable you to see if a particular process can meet a specific target. The calculation used will determine the process capability. Most software currently available to generate SPC charts will not calculate the process capability so this will have to be done manually. However, Rapport will calculate this for you. The calculation used to determine process capability is: Capability = Target - Average 3 * standard deviation A value of 1 means the process is 100% capable of achieving the target. A negative figure means more than 50% of patients will not meet a given target. The procedure for calculating process capability is therefore: Test for stability by plotting a control chart first If unstable, gain control by identifying and controlling the main factors that affect the situation Only if it is stable, calculate a process capability to determine if it is capable of meeting the target Links to further resources For information on improvement knowledge and skills and on measurement for improvement, see the Improvement Leaders Guides produced by the NHS Institute for Innovation and Improvement http://www.institute.nhs.uk/products/improvementleadersguidesboxset.htm. NHS Improvement 8 August 2011

The series of guides covers General improvement skills, process and systems thinking and personal and organisational development in 13 booklets. All of the service improvement tools and techniques training materials can be accessed by going to: The Directory of Improvement Resources on the NHS Improvement System. NHS Improvement 9 August 2011

NHS Improvement 3 rd Floor St Johns House East Street Leicester LE1 6NB Telephone 0116 222 5253 Email: Support@improvement.nhs.uk