NUR 5053 Module 5 Measurement Plan and Run Chart Analysis Example

Reviewed by Junia Fairbank, MSN, RN · American College of Education · Updated

This NUR 5053 Module 5 example is a measurement plan and run chart analysis for confirmed feeding tube placement: twenty ordinary baseline weeks and three good weeks after the change. It serves American College of Education NUR 5053 (NUR5053), Quality Improvement and Safety, in the MSN program. The plan explains why data over time beat a before-and-after comparison, writes operational definitions with numerators, denominators, exclusions, windows and sources, and reports an interrater check that changed one definition. It gives the baseline values so a reader could redraw the chart, states the median and applies the run chart rules from Perla and colleagues and Anhøj and Olesen by name. It refuses to call three good weeks a signal, compares the balancing measure with the PDSA prediction, and names next steps in measurement. Sections commonly provide the data set.

CourseNUR 5053 Quality Improvement and Safety
ModuleModule 5
Paper typeMeasurement plan and run chart analysis
Length1,220 words, about 4 pages plus title and reference pages
FormatAPA 7 student paper
SchoolAmerican College of Education
ProgramMSN
UpdatedOctober 2026

Free sample paper for NUR 5053 Module 5

1

Twenty Ordinary Weeks and Three Good Ones: A Measurement Plan and Run Chart Reading for Confirmed Feeding Tube Placement

Student Name

American College of Education

NUR5053: Quality Improvement and Safety

Module 5 Assignment

Instructor Name

November 24, 2026

What this page is doingThe title tells the reader the finding in advance: a stable baseline and a short run of good results that has not yet become a signal. The APA 7 title page carries the course line and the module assignment as listed.
2

What the Plan Must Do

The project chartered in Module 4 aims to have every first enteral feeding on the neuroscience step-down unit start only after a radiologist has filed a placement result. Aggregate numbers cannot tell the team whether its changes are working. A before-and-after comparison of two monthly percentages would hide the week-to-week variation that is normal for a unit placing five or six tubes a week, and it would invite the team to celebrate or panic over differences that are only noise. Perla et al. (2011) make the case that data plotted in time order let a team see whether a process has changed with very little statistical machinery, and that such plots are more useful to improvement teams than summary statistics that ignore time. The measurement plan is built around that idea.

What this page is doingThe section explains why the plan uses data over time rather than a before-and-after comparison, and supports the point with a source written for improvement teams.
3

Operational Definitions and Data Collection

The project's main process measure counts, as a share of each week's placements, the first feedings that began only once a placement result was on file. The numerator is the number of newly placed nasal small-bore tubes, in the reporting week, whose first feeding time on the pump documentation is later than the time stamp on the radiologist's filed result. The denominator is every newly placed nasal small-bore tube on the unit that week that was used for feeding. Tubes removed before any feeding, tubes placed elsewhere and replacement tubes placed within 24 hours for the same patient are excluded. The week runs Monday 0000 to Sunday 2359. The first feeding time is the pump start, not the time the order was released, because the pump start is when harm could begin.

The data come from two electronic sources: the radiology information system for the result time stamp and the medication administration record for the pump start. The clinical nurse specialist pulls both each Monday for the prior week, and a second reviewer from the quality department independently abstracts every fourth record to check that the definitions produce the same answer. In the first month the two reviewers disagreed on one record out of seven, a patient whose feeding was restarted after a pause, and the definition was amended to specify the first start after placement.

The second process measure, the percentage of high-risk patients receiving guided placement, is reported monthly because the numbers are too small for a weekly chart. The balancing measure is the median hours from the placement order to the first feeding, reported weekly and split by day and night shift. The outcome measure, misplacements discovered after feeding began, is counted and reviewed case by case.

What this page is doingEach measure is defined with a numerator, a denominator, exclusions, a time window, a data source and a collection schedule. The interrater check, and the definition that changed because of it, shows the grader the data have been tested before anyone reads a chart.
4

The Baseline Run Chart

The baseline covers 20 weeks, from the week of June 15 to the week of October 26, 2026, recovered from records. Weekly values, in order, were 100, 83, 100, 86, 100, 67, 71, 67, 83, 80, 83, 67, 71, 83, 83, 75, 67, 80, 71 and 83 percent, with between four and seven placements in each week. Plotted in order, the points range from 67% to 100% and fall into no obvious pattern. The median of the 20 points is 81.5%, and it is drawn as the center line and extended forward as the reference against which new points are judged.

The chart was read with the four rules Perla et al. (2011) describe. A shift, meaning a stretch of at least six weeks in a row that all land above the median or all below it, is absent: the longest run is the five weeks above the median at the start of the baseline. A trend, five or more consecutive points going steadily up or down, is absent. The number of runs is nine, which falls within the range expected by chance for 20 points, so the data do not alternate too much or too little. No single point is far enough from the others to count as an astronomical value. The chart was also checked against two rules proposed after a simulation study, the longest run and the number of times the line crosses the median, which kept false signals near 5% in simulated processes while the trend rule proved almost useless for picking up gradual drift (Anhøj & Olesen, 2014). With eight crossings and a longest run of five, the conclusion is the same.

The baseline is a stable process, and a stable process that starts one feeding in five too early will keep doing so until someone redesigns it. That reading matters for leadership. It means the early feedings were not caused by a bad week, a careless nurse or a staffing crisis, each of which would have left a signal, and it means reminders and discipline will not move the center line. Only a change to the system will.

What this page is doingThe raw values are reported so a reader could redraw the chart, the median is stated, and each rule is applied by name with the count that settles it. The highlighted sentence turns a statistical finding into a management conclusion, which is where the marks for interpretation sit.
5

The First Weeks After the Change

The red pump tag described in the Module 4 plan was introduced on night shift in the week of November 2 and extended to all shifts after the first cycle. The three weeks since then reached 100% with six, seven and five placements. All three points sit above the baseline median.

Three points above the median are not a signal. By the shift rule, three more consecutive weeks above 81.5% would be needed before the team could say the process has changed. The small denominators also mean each week's value moves in steps of 14 to 20 percentage points, so one early feeding would drop a week to the low 80s. The team's decision is therefore to continue the tag, to keep plotting, and to begin the second cycle, the radiology priority category, without yet declaring success.

The balancing measure shows the price of the tag. At night, the median time from the placement order to the first feeding rose from 4.1 hours in the baseline to 4.9 hours, an increase of about 48 minutes, slightly more than the 45 minutes the team predicted. During the day it rose by 10 minutes. The increase is the time patients were previously being fed before the tube's position was known, so it is a delay the unit should accept, but it makes the case for the radiology priority, which is meant to bring the night figure back down.

What this page is doingThe paper resists overclaiming, explains exactly what additional data would count as a signal and why the small numbers matter, and compares the balancing measure with the prediction from the PDSA plan. That honesty is what separates a strong run chart analysis from a weak one.
6

Limits and Next Steps in Measurement

A run chart is the right first tool for a project with a short baseline and small weekly counts, but it is not the only one. Once 20 to 25 points exist after the change, the team will move the process measure to a p-chart, the control chart built for proportions, whose limits widen and narrow with each week's denominator. Mohammed et al. (2008) set out how to choose and build such charts and why unequal subgroup sizes call for that chart type. The data also depend on accurate time stamps; if a nurse documents the pump start late, a feeding can appear to have begun after the result when it did not. The quality reviewer's audit of every fourth record will continue for that reason. Finally, this plan measures whether feeding waits for confirmation, not whether confirmation is correct. A misread film would pass every measure here, which is why each misplacement found after feeding will still be reviewed as an event.

What this page is doingThe section names the next tool and the reason for it, the main source of measurement error and a gap that no process measure can close. Those limits prepare the ground for the sustainment plan in Module 6.
7

References

Anhøj, J., & Olesen, A. V. (2014). Run charts revisited: A simulation study of run chart rules for detection of non-random variation in health care processes. PLOS ONE, 9(11), Article e113825. https://doi.org/10.1371/journal.pone.0113825

Mohammed, M. A., Worthington, P., & Woodall, W. H. (2008). Plotting basic control charts: Tutorial notes for healthcare practitioners. Quality and Safety in Health Care, 17(2), 137-145. https://doi.org/10.1136/qshc.2004.012047

Perla, R. J., Provost, L. P., & Murray, S. K. (2011). The run chart: A simple analytical tool for learning from variation in healthcare processes. BMJ Quality & Safety, 20(1), 46-51. https://doi.org/10.1136/bmjqs.2009.037895

Reading the NUR 5053 Module 5 instructions

The fifth module of NUR 5053 commonly asks you to plan the measurement of an improvement project and analyze data over time. Expect operational definitions for each measure, a data collection plan, a run chart or control chart with its median or center line, application of the rules for detecting signals, and an interpretation of what the data do and do not show. Some sections provide a data set in the classroom; others ask you to use your own or composite data. Expect about five pages plus the chart. Check the Canvas instructions for which rules to apply and whether a control chart is required.

How this NUR 5053 Module 5 example is built

The plan opens by explaining why improvement work needs data over time, citing a source written for improvement teams. The definitions section gives each measure a numerator, denominator, exclusions, window, source and schedule, and reports an interrater check that led to a revised definition. The baseline section lists the twenty weekly values, states the median and applies the shift, trend, runs and astronomical point rules by name with the count that settles each, concluding that the process is stable and the problem is built in. The post-change section explains why three good weeks are not yet a signal and what would be, and checks the balancing measure. The last section names the next tool, the main measurement error and a gap no process measure closes.

NUR 5053 Module 5 rubric: what full marks look like

Measurement papers are typically graded on operational definitions, data collection, correct construction of the chart, correct application of rules and interpretation. Definition marks require numerators, denominators and exclusions. Collection points reward a schedule and reliability check. Chart marks go to a correct median and enough points. Rule application often decides the band, rewarding each rule named and applied correctly. Interpretation points depend on conclusions that do not overclaim. APA 7 and a readable chart finish the rubric. Giving the twenty raw baseline values lets a reader redraw the chart, which graders value. The interrater check that changed a definition is evidence the data can be trusted. Refusing to call three good weeks a signal, and saying exactly what would be one, is where many papers lose marks and this one gains them.

NUR 5053 Module 5 help: mistakes that cost points

Run chart papers most often declare improvement after two or three good points. Another frequent weakness is applying rules incorrectly, such as counting points on the median. Students also skip operational definitions, so the data cannot be trusted. Give your raw values. Name each rule and show the count. Say what would count as a signal. Check data reliability. Report the balancing measure. If your project uses different measures or a control chart, the desk can write a measurement plan for it. Do not count points on the median when applying the shift rule.

Write yours, or have the desk draft it

This paper is an original model document written by our desk, not a submitted student paper and not an official American College of Education document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.

More NUR 5053 and MSN sample papers

NUR 5053 Module 5 questions, answered

What does NUR5053 Module 5 usually ask for?

NUR5053 Module 5 commonly asks for a measurement plan, with operational definitions and data sources for each measure, and an interpretation of a run chart. Some sections provide the data set; others expect your project's own baseline. Your classroom's instructions decide which.

How many data points do I need on a run chart?

Enough to apply the rules. The shift rule needs six consecutive points on one side of the median, so a baseline of fewer than about 10 to 12 points can hide or invent a pattern. State how many points you have and what a signal would require.

What if my run chart shows no signal?

Say so and interpret it. A stable baseline tells you the problem is built into the process, which is an important finding. After a change, a lack of signal may mean the change has not worked yet or that you need more weeks of data.

Where can I find a free NUR 5053 Module 5 sample paper?

The feeding tube measurement plan and run chart reading is free on this page, with the definitions, the baseline values and rules, the post-change weeks and next steps, plus three references and notes.

What are the run chart rules?

Four rules are standard: six or more consecutive points above or below the median, five or more steadily rising or falling, an unusual number of runs, and one point far outside the rest. Each signals non-random change.