ORIGINAL RESEARCH The run chart: a simple …

1 The run chart : a simple analytical toolfor learning from variation inhealthcare processesRocco J Perla,1 Lloyd P Provost,2 Sandy K Murray3 Background:Those working in healthcare today arechallenged more than ever before to quickly andefficiently learn from data to improve their services anddelivery of care. There is broad agreement thathealthcare professionals working on the front linesbenefit greatly from the visual display of datapresented in time :To describe the run chartdan analytical toolcommonly used by professionals in qualityimprovement but underutilised in :A standard approach to the construction, useand interpretation of run charts for healthcareapplications is developed based on the statisticalprocess control :Run charts allow us to understandobjectively if the changes we make to a process orsystem over time lead to improvements and do so withminimal mathematical complexity.

2 This method ofanalyzing and reporting data is of greater value toimprovement projects and teams than traditionalaggregate summary statistics that ignore timeorder. Because of its utility and simplicity, therun chart has wide potential application inhealthcare for practitioners and charts also provide the foundation for moresophisticated methods of analysis and learning suchas Shewhart (control) charts and skills associated with using data forimprovement vary widely among thoseworking to improve healthcare. We describea simple analytical tool commonly used byprofessionals in quality improvement, butunderutilised in healthcaredthe run those health professionals that use runcharts, they provide a valuable source ofinformation and learning for both practi-tioner and patient.

3 The following scenariodescribed by Neuhauser and Diaz2providesone example of the simplicity of run chartsand their potential for wide application inhealthcare:Susan Cotey is a diabetes educator at HuronHospital in Cleveland, Ohio. She gives outgraph paper to elderly diabetic patients wholive in the most impoverished part of her uses a self-help book designed specifi-cally for her patients. Each patient getsa copy. She asks them to plot their bloodsugar measures over time, connect the dotsand bring their graphs in to small discussiongroups of similar patients who share theirexperience and learn about diabetes self-management (diet, exercise, weightcontrol).

4 Nearly every patient brings in theirgraph. The large majority of patientsimprove their diabetic control. This hospitalhas made diabetes management a centre ofits healthcare use of run charts by these patients withdiabetes summarises the spirit of our paperdthe run chart has a role to play in healthcareimprovement many healthcare professionalsnow recognise the value of statistical processcontrol methods, applications and tools inimproving the quality of care, much of thisfocus in the healthcare improvement litera-ture is on Shewhart (control) charts andtheir various derivatives (such as cumulativesummation charts and funnel plots).

5 3 Verylittle has been written about the use andapplication of run run chart allows us to learn a great dealabout the performance of our process withminimal mathematical complexity. Specifi-cally, it provides a simple method to determineif a process is demonstrating non-randompatterns, what we term a signal . By focussingon the time order that data are collected, therun chart can be applied when traditionalmethods to determine statistical significance(t-test, chi-square, F test) are not uses of the run chart for improve-ment activities include the following4:<An additional text box ispublished online only. Toview this file please visit thejournal online ( ).

6 1 UMass Memorial HealthCare, Worcester,Massachusetts, USA2 Associates in ProcessImprovement, Austin, Texas,USA3 Corporate TransformationConcepts, Eugene, Oregon,USAC orrespondence toDr Rocco J Perla, Office ofQuality and Patient Safety,Center for Innovation andTransformational Change, 22 Shattuck Street, Worcester,MA 01605, USA; 26 July 201046 BMJQualSaf2011;20:46e51. RESEARCH on April 8, 2011 - Published by from <Displaying data to make process performance visible<Determining if changes tested resulted in improve-ment<Determining if we are holding the gains made by ourimprovement<Allowing for a temporal (analytic) view of data versusa static (enumerative) viewDisplaying data on a run chart is often the first step indeveloping more complex Shewhart (control) charts45and in the design of planned thispaper, we briefly outline the construction, interpretationand use of run AND CONSTRUCTION OF A RUN CHARTA run chart is a graphical display of data plotted in sometype of order.

7 The horizontal axis is most often a timescale (eg, days, weeks, months, quarters) but could alsoinclude sequential patients, visits or procedures. Thevertical axis represents the quality indicator beingstudied (eg, infection rate, number of patient falls,readmission rate). Usually, the median is calculated andused as the chart s centreline. The median is requiredwhen using the probability-based rules to interpret a runchart (see below). The median is used as the centerlinebecause (1) it provides the point at which half theobservations are expected to be above and below thecenterline and (2) the median is not influenced byextreme values in the data.

8 Goal lines and annotations ofchanges and other events can also be added to the 1shows an example of a run chart . As shownin figure 1, the run chart helps us understand and visu-alise the impact of different interventions and tests ofchange over time. To determine objectively when thesedata signal a process improvement, we use the medianand run chart rules described in the next primary advantage of using a run chart is that itpreserves the time order of the data, unlike statistical testsof significance that generally compare two or moreaggregated sets of data. For example, the summarystatistic presented infigure 2lookslike there is improve-ment in the before to after data attributed to a change inthe system.

9 Summary statistics for each of the three unitsshown infigure 2where the change was tested producethe same pre-test mean and SD (70 min, min) andpost-test mean and SD (30 min, min). Further,a t-test produced a highly significant result (t22 ,p< ). The question we want answered, however, is notwhether our change was statistically significant butwhether the change is associated with a sustainableimprovement in each unit where the change was from Unit 1 would yield the bar chart infigure 2andsupport the conclusion that we have achieved a sustain-able improvement. Data from Unit 2 would yield the samebar chart but the data here reveal that improvement wasalready occurring before the change was tested.

10 Data fromUnit 3 would also result in the same bar chart . In Unit 3,the change did result in improvement, however, it was notsustained. Viewing data over time rather than in summarystatistics yields richer data and more accurate conclusionsfor improvement TO HELP INTERPRET A RUN CHARTWhen improvement data are presented in healthcare(eg,clinical reports, dashboards, project updates, andboard reports), people will often over- or under-react toa single or most recent data point (and begin tampering,possibly making things worse).8 The terms shift and trend are often used indiscriminately on a subjectivebasis as a means for moving a conversation or decisionforward, without recognition that statistical definitionsof such terms exist and rely on more than a single datapoint.