A quality improvement (QI) project asks you to find a problem in care, test a change on a small scale and show whether it worked. Marks go to a clear aim, sound methods and honest measurement. This guide walks through each stage and the tools that instructors expect to see.
QI aims to improve a specific process or outcome in a local setting, using small, rapid tests of change. It differs from research, which aims to produce generalisable knowledge under a formal protocol. That difference matters for ethics: many organisations treat QI as an operational activity, but you should confirm with your program and the site how your project is classified and whether review is required.
The Institute for Healthcare Improvement popularised the Model for Improvement, which starts with three questions: What are we trying to accomplish? How will we know a change is an improvement? What changes can we make that will result in improvement? Your project should answer all three.
Start with a specific problem you can support with data, such as a process that is often skipped, a delay, or an avoidable harm on one unit. Then write a SMART aim: Specific, Measurable, Achievable, Relevant and Time-bound.
Example structure: "Increase the percentage of patients on Unit X who receive teach-back at discharge from [baseline] to [target] by [date]." Use your own baseline and target from real or course-supplied data, not invented ones.
List everyone affected: patients and families, nurses, physicians, pharmacists, managers, quality staff and support services. For each, note their interest, likely concerns and what you need from them. A short stakeholder table plus a plan for engagement shows you understand that improvement is a team effort.
Do not choose your intervention before you have looked for causes. Markers notice when the solution has clearly come first.
PDSA stands for Plan, Do, Study, Act. Each cycle tests one change on a small scale, such as one shift, one nurse or a handful of patients, so that failure is cheap and learning is fast.
| Phase | What you do | What to write |
|---|---|---|
| Plan | Choose a change, predict the result, decide who, when and how you will measure | Prediction and measurement plan |
| Do | Run the test and note what happens, including problems | Observations and issues |
| Study | Compare results with your prediction | What the data show and what surprised you |
| Act | Adopt, adapt or abandon the change | Decision and next cycle |
Show at least one full cycle, including a change you adapted because the first attempt did not work. That is normal, and it is evidence of real learning.
Use three kinds of measures. Outcome measures track the result you care about. Process measures track whether the steps you changed are happening. Balancing measures check that the change has not caused a problem elsewhere, such as longer discharge times.
Display data over time on a run chart: time along the bottom, your measure up the side, and a median line. Run charts make trends and shifts visible in a way a before-and-after average cannot. Annotate the chart with the dates of each change.
Do not claim more than the data support. A short project with few data points shows a signal, not proof. Say so, and explain what further cycles would confirm.
Improvements fade when the project team moves on. Address how the change will be embedded: updated policy or order sets, staff training, a named owner, ongoing audit and feedback, and how success will be reported. Then say where else the change could spread and what would need to adapt.
The SQUIRE guidelines (Standards for QUality Improvement Reporting Excellence) give a checklist for reporting QI work, covering the problem, context, intervention, study of the intervention, measures, analysis, results, discussion and ethics. Many programs use SQUIRE headings to structure the final paper. See the SQUIRE website for the current checklist.
Share your topic, setting and rubric in your brief and get a model project write-up or an edit of your own.
They overlap but differ. An EBP project applies published evidence to a practice question, while a QI project tests changes locally and measures results in your own setting. Many capstones combine them. See the EBP paper guide.
Follow your course. Some programs require real unit data, others supply a case or allow a proposal. Never invent data. If you lack it, describe how you would collect it.
Your rubric decides. Quality of learning matters more than the count, so one well-documented cycle usually beats several thin ones.
A strong QI paper reads as a story with evidence: a real problem, a defined aim, thoughtful analysis, small tests, honest data and a plan to keep the gains. Explore the QI proposal resource for a template, and the capstone project ideas guide if you are choosing a topic.
To get a model write-up or feedback on your draft, request an instant quote at /order. Delivered work includes 14 days of free revisions, and refund terms are on the money-back guarantee page. Please use any model paper in line with your institution's academic-integrity policy.