Differentiating QI from Research

QI and Research: Similar Methods, Different Goals

Quality improvement and clinical research are both systematic, data-driven approaches to advancing healthcare — but they serve fundamentally different purposes. Research seeks to generate new, generalizable knowledge that extends beyond a single institution, often testing a hypothesis across larger populations using fixed protocols. QI, by contrast, applies existing knowledge to improve a specific local process, program, or system, using short iterative cycles that can be adjusted in near real-time to meet a defined quality goal.

That distinction carries real consequences. Research may place participants at risk in service of knowledge that benefits society broadly, while QI is designed to benefit the patients within a specific system without increasing risk beyond standard care. Knowing which framework applies to your project shapes everything from team structure and study design to whether IRB oversight is required.

QI and Research: Key Differences in Stakeholder Involvement and Data

Stakeholder Involvement

Quality improvement is a collaborative process that actively engages the people closest to the work — frontline staff, clinicians, and operational leaders — in designing and testing changes to local processes. Research teams tend to be more specialized, led by investigators with subject-matter expertise. While research participants contribute data, they are generally not involved in shaping study design once a protocol is established.

Data

QI projects typically rely on smaller, practical data samples that allow teams to monitor performance in real time and assess whether changes are leading to improvement. The emphasis is on learning and adapting quickly, rather than achieving statistical proof. Research studies, by contrast, require larger and more rigorously designed data sets to produce results that are statistically valid and generalizable to broader populations.

Common Challenges in QI Data Requests

Data is one of the most frequent pain points in quality improvement work. Several patterns tend to complicate the process:

Requests without a defined problem

One-time reports drawing on extensive retrospective data are often labeled as “quality” work without a clear problem statement or plan for ongoing monitoring.

Data requested after project completion

When data collection follows rather than precedes a project, it can be difficult to distinguish quality improvement from retrospective research.

Individual rather than team-based efforts

Quality improvement requires a collaborative, multidisciplinary approach. Without a team structure, initiatives are less likely to result in sustainable, practice-level change.

Resources

The resources below build a practical understanding of QI vs. research, starting with the conceptual foundation and moving through the key elements of designing and executing effective QI work.

Understanding the Core Distinction

Differentiating QI from Research

In this video, Lynne Meyer, PhD, MPH, Director of Graduate Medical Education at UF’s College of Medicine, walks through the key differences between clinical research and quality improvement. She covers purpose, design, who benefits, what risks are involved, and how each initiative concludes — giving clinicians a clear conceptual framework for categorizing their own work.

Determining IRB Oversight

Does Your Project Require IRB Oversight? Self-Certification Questions

Dr. Meyer presents the six self-certification questions developed by the UF Health Quality Improvement Project Registry to help clinical teams determine whether their project is QI or research. Each question targets a specific indicator — such as intent to generate generalizable knowledge, involvement of experimental interventions, or multi-site scope — and walks through what each answer signals about IRB review requirements. Teams are reminded that while these questions are a strong guide, any uncertainty should be referred directly to the Institutional Review Board.

QI in Institutional Context

What Is Patient Safety and Quality Week — and Why It Matters

This video offers a firsthand look at how UF Health celebrates and elevates QI work through its annual Patient Safety and Quality Week. A reviewer of project proposals describes the event as an institution-wide opportunity to showcase improvement efforts, earn CME credit, discover cross-departmental collaboration, and draw inspiration from the breadth of frontline-driven projects completed each year. It provides clinicians with a motivating glimpse of where their own QI work could lead.

Designing a Strong QI Project

This group of videos features Lynne Meyer, PhD, MPH, Director of Graduate Medical Education at UF’s College of Medicine, drawing on her extensive experience reviewing QI proposals to share what separates projects that succeed from those that struggle. Together, they offer a practical guide to the core elements of well-designed QI work.

Green Flags: What Strong QI Proposals Look Like

Dr. Meyer shares the first things she looks for when reviewing a QI proposal: a well-written SMART goal and an interprofessional team. She explains how a clearly defined, specific, measurable, achievable, realistic, and time-bound goal signals that a team has genuinely thought through their project — and why representation from across disciplines and frontline roles is essential to a project’s credibility and success.

From Too Broad to Just Right: The Power of a Focused QI Project

Scope creep is one of the most common pitfalls in QI work. Dr. Meyer explains why narrowing a project’s focus is critical to knowing where you’re headed — and illustrates the point with a compelling real-world example of a cardiology team that traced missed appointments to a bus stop a mile from the clinic, then worked with the transit authority to solve the problem directly.

Good Data, Bad Data: Building a QI Measurement Plan That Actually Works

A strong QI project requires not just measurable outcomes, but the right outcomes. Dr. Meyer walks through the difference between data you can collect and data that actually answers your improvement question — using the example of measuring clinician knowledge before and after training, and why that alone cannot tell you whether patient care has improved.

The Right Team: Stakeholders, Front-Line Voices, and Driving Real Change

Dr. Meyer revisits the importance of team composition, emphasizing that the people closest to the problem — nurses, physicians, aides, environmental staff, and others — must have a seat at the table. She explains how frontline representation signals to reviewers that a team is positioned to understand, and actually fix, the issue they’re targeting.

Beyond Compliance: What Makes a QI Project Truly Impactful

A technically sound project isn’t always an impactful one. Dr. Meyer describes the difference between projects done out of obligation and those driven by genuine problem-solving — and encourages clinicians to connect their work to institutional goals, investigate root causes, and embrace the iterative nature of QI. Her closing advice: think small, try one change, and don’t be afraid to get started.

Quick Reference

Comparing QI and Research

This table provides a side-by-side comparison of Quality Assurance/Quality Improvement (QA/QI) and research across several key points. Use it as a quick reference to understand the fundamental differences between these two methodologies.

Quality vs. Research from the UF IRB

The University of Florida Institutional Review Boards issued this policy brief to address frequently asked questions about the complex distinctions between QA/QI and research. Use it to understand the gray areas and determine if your project requires IRB consultation.