[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-167453-en":3,"doc-seo-167453-105":30,"detail-sidebar-cat-1-en-105":95},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":11,"category_id":12,"category_name":13,"doc_title":14,"doc_description":15,"doc_content":16,"file_id":17,"file_url":18,"file_type":19,"file_size":20,"view_count":4,"is_deleted":4,"is_public":11,"is_downloadable":11,"audit_status":11,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":15,"update_tm":28,"read_time":29},167453,1099513958607,"Jiven","https://ap-avatar.wpscdn.com/avatar/100002390cf8733938c?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778829742770036399",1,11,"Presentations","Run Chart & Control Chart - Instructions","Run charts and control charts are used to analyze data over time and determine whether process changes are driving improvement. The run chart helps improvement teams visualize performance and distinguish common-cause variation from special-cause variation. When more than 15 data points are available, a control chart adds upper and lower control limits to flag special-cause variation, support early success signals, and help maintain gains. Instructions cover axis setup, scaling, plotting sequence, median/mean centerlines, and control-limit calculations plus chart annotation.","QI Essentials Toolkit:\nRun Chart & Control Chart\nA run chart is a graph of data over time. It is a simple and effective tool to help you determine whether the changes you are making are leading to improvement.\nRun charts help improvement teams formulate aims by depicting how well (or poorly) a process is performing, understand the value of a particular change, and begin to distinguish between common and special causes of variation.\nCommon-cause variation is the natural or expected variation inherent in a process. Special-cause variation arises because of specific circumstances that are not inherent in the process.\nA control chart, which includes an upper control limit (UCL) and a lower control limit (LCL), goes further to help teams distinguish between common and special causes of variation within a process. Use a control chart when you have more than 15 data points and want more insight into your data.\nControl charts help improvement teams identify special-cause variation in a process, identify early signs of success in an improvement project, and monitor a process to ensure it is holding the gains from a quality improvement effort.\nCopyright © 2017 Institute for Healthcare Improvement. All rights reserved. Individuals may photocopy these materials for educational, not-for-profit uses, provided that the contents are not altered in any way and that proper attribution is given to IHI as the source of the content. These materials may not be reproduced for commercial, for-profit use in any form or by any means, or republished under any circumstances, without the written permission of the Institute for Healthcare Improvement.\nInstructions\nObtain a set of data points in their natural time sequence.\nDraw the vertical and horizontal axes, leaving room on all sides to title and label the graph.\nLabel the vertical (Y) axis with the name of the value being measured (e.g., Percent of Births by C-section, Number of Days to Third Next Available Appointment, etc.).\nLabel the horizontal (X) axis with the unit of time or sequence in which the numbers were collected (e.g., April, May, June, etc., or Quarter 1, Quarter 2, etc.).\nDetermine the scale of the vertical axis. The scale should extend from a number 20 percent larger than the largest value to a number 20 percent smaller than the smallest value. Label the axis in equal intervals between these two numbers.\nPlot the data values in the sequence in which they occurred.\nDraw lines to connect the data points on the graph.\nCalculate the median (the data point half way between the highest and the lowest data point) of the plotted numbers and draw the line on the graph.\no Note: For a control chart, complete these two steps:\nInstead of calculating the median, calculate the mean or control limit (the average) of the plotted numbers and draw the line on the graph.\nCalculate and then draw upper and lower control limits that correspond to +/- 3 sigma limits from the mean. (We recommend doing this in Microsoft Excel or another software program.)\nTitle the chart, and note the goal line and the sample size.\nAnnotate the chart, indicating when tests of change were initiated, so that it is easy to see the effect of changes on the measure. Also indicate any external events that may have affected the performance of the process.\nExample: Run Chart\nExample: Control Chart\nValuVealuBeeiBneginMgeMaesausruerded\nBefore filling out the template, first save the file on your computer. Then open and use that version of the tool. Otherwise, your changes will not be saved.\nTemplate: Run Chart or Control Chart\nTTiimmee","cbCaioMexSeRvWre","https://ap.wps.com/l/cbCaioMexSeRvWre","docx",262423,4,"English","en",105,"# Run chart vs. control chart\n## Purpose of run charts\n## Purpose of control charts\n# How to create a run chart\n## Data preparation and axes\n## Scale, plotting, and median\n# How to create a control chart\n## Center line and mean\n## Upper and lower control limits\n## Title and annotations","[{\"question\":\"What is the main difference between a run chart and a control chart?\",\"answer\":\"A run chart graphs data over time to help detect improvement. A control chart adds upper and lower control limits to distinguish common-cause from special-cause variation within a process.\"},{\"question\":\"When should you use a control chart instead of a run chart?\",\"answer\":\"Use a control chart when you have more than 15 data points and want more insight into your data.\"},{\"question\":\"How do you construct the axes and scale for the chart?\",\"answer\":\"Draw vertical and horizontal axes with room for titles and labels, label Y with the measured value and X with the time/sequence unit, then set the Y scale from about 20% above the largest value to about 20% below the smallest value using equal intervals.\"},{\"question\":\"What calculations are required for a control chart’s center line and limits?\",\"answer\":\"Instead of a median, calculate the mean (control limit) of the plotted numbers and draw it as the center line. Then calculate and draw upper and lower control limits corresponding to +/- 3 sigma limits from the mean.\"}]","Run Chart & Control Chart - Instructions | DOCX",1788214337,2,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":14,"keywords":34,"description":15,"schema_data":35,"social_meta":90,"head_meta":92,"extra_data":94,"updated_unix":28},"run-chart-control-chart-instructions","",{"@graph":36,"@context":89},[37,52,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":11},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":29},"https://docshare.wps.com/template/","Template",{"item":48,"name":13,"@type":43,"position":49},"https://docshare.wps.com/template/presentations/",3,{"item":51,"name":14,"@type":43,"position":21},"https://docshare.wps.com/template/run-chart-control-chart-instructions/167453/",{"url":51,"name":14,"@type":53,"author":54,"headline":14,"publisher":56,"fileFormat":59,"inLanguage":23,"description":15,"dateModified":60,"datePublished":61,"encodingFormat":59,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":41,"name":57,"@type":58},"DocShare","Organization","application/vnd.openxmlformats-officedocument.wordprocessingml.document","2026-09-05","2026-08-31",true,{"@type":64,"interactionType":65,"userInteractionCount":67},"InteractionCounter",{"@type":66},"ViewAction",5,{"@type":69,"mainEntity":70},"FAQPage",[71,77,81,85],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main difference between a run chart and a control chart?","Question",{"text":75,"@type":76},"A run chart graphs data over time to help detect improvement. A control chart adds upper and lower control limits to distinguish common-cause from special-cause variation within a process.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"When should you use a control chart instead of a run chart?",{"text":80,"@type":76},"Use a control chart when you have more than 15 data points and want more insight into your data.",{"name":82,"@type":73,"acceptedAnswer":83},"How do you construct the axes and scale for the chart?",{"text":84,"@type":76},"Draw vertical and horizontal axes with room for titles and labels, label Y with the measured value and X with the time/sequence unit, then set the Y scale from about 20% above the largest value to about 20% below the smallest value using equal intervals.",{"name":86,"@type":73,"acceptedAnswer":87},"What calculations are required for a control chart’s center line and limits?",{"text":88,"@type":76},"Instead of a median, calculate the mean (control limit) of the plotted numbers and draw it as the center line. 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