Spread is the process of taking a change that has been successful in one context and using it in another. Successful spread efforts require leadership, better ideas, a set-up strategy, communication, measurement, and feedback.

From the perspective of those adopting the changes, they must go through the same process of testing, adapting, and implementing the change ideas. However, a well-designed, resourced, and led organizational spread strategy can accelerate the journey to results.

Spread efforts will benefit from the use of the PDSA cycle. Systems adopting the change need to plan how best to adapt the change to their unit and to determine if the change resulted in the predicted improvement.

Example

• Implementing a change: A new medication reconciliation form is made standard practice in one hospital. The form is embedded in the electronic health record (EHR) and all new staff are trained on it.
• Spreading a change: Another hospital in the health system has decided to use the same form. They consult the project sponsor and team lead and invite them to consult with their team to find out what they learned during their testing and implementation phases in order to accelerate the work of testing and implementing the form in their facility.

A change is ready for implementation when the improvement team has completed the following:

• Tested the change, typically starting on a small scale and increasing the scale based on the learning of each PDSA cycle
• Tested the change under varying conditions in order to adapt to the local environment
• Established a causal relationship between the change and the desired outcome through appropriate data collection and analysis

Implementation is a permanent change to the way work is done and, as such, involves hardwiring the change into the workflow or standard work within an organization. It may affect documentation, written policies, hiring, training, compensation, and aspects of the organization's infrastructure that are not heavily engaged in the testing phase. Implementation also requires the use of PDSA cycles.

Example

• Testing a change: Three nurses on different shifts use a new medication reconciliation and order form.
• Implementing a change: The new form is made standard practice, the old form is removed from the department, the new form is added to relevant manuals and computer files, including orientation and training materials for new staff.

Model for Improvement: Plan-Do-Study-Act (PDSA) Cycles

Once a team has identified testable change ideas, the next step is to test them. The Plan-Do-Study-Act (PDSA) cycle is a method for learning how the change works in the local environment — by planning it, trying it, observing the results, and acting on what is learned, teams can build their knowledge about the potential of a change to result in improvement in their local context. This is the scientific method, used for action-oriented learning. Most changes will require many PDSA cycles, planned and executed in a sequence, to develop a change, test it under varying conditions, and eventually implementing it, if the change is shown to result in improvement.

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Reasons to Test Changes

• To increase your belief that the change will result in improvement.
• To decide which of several proposed changes will lead to the desired improvement.
• To evaluate how much improvement can be expected from the change.
• To decide whether the proposed change will work in the actual environment of interest.
• To decide which combinations of changes will have the desired effects on the important measures of quality.
• To evaluate costs, social impact, and side effects from a proposed change.
• To minimize resistance upon implementation.

Steps in the PDSA Cycle

Step 1: Plan

Plan the test or observation, including a plan for collecting data.

• State the objective of the test.
• State the questions the test will be designed to answer
• Make predictions about what the results of the test will be (answers to the stated questions)
• Develop a plan to test the change. (Who? What? When? Where? What data need to be collected?). Early PDSA cycles should be scoped as small as possible.

Step 2: Do

Execute the plan.

• Carry out the test as planned.
• Document problems and unexpected observations.
• Begin analysis of the data.

Step 3: Study

Analyze the data and study the results.

• Complete the analysis of the data.
• Compare the data and result to your predictions.
• Summarize and reflect on what was learned.

Step 4: Act

Refine the change, based on what was learned from the test.

• Determine what modifications should be made.
• Prepare a plan for the next test.

Example of a First Test of Change (PDSA Cycle)

Depending on their aim, teams choose promising changes and use Plan-Do-Study-Act (PDSA) cycles to test a change quickly often on a small scale at first, see how it works, and refine the change as necessary before testing it on a broader scale, and implementing if shown to lead to the desired improvement.

The following example shows how a team started with a small-scale test.

Example First PDSA: Diabetic patient planned visits for blood sugar management support

Objective: To learn about how patients respond to being offered an appointment for blood sugar management support

Questions:

• How will patients respond to being asked?
• What barriers might arise with the scheduling?

Prediction: Patients who are struggling with blood sugar management will be interested in scheduling a dedicated appointment. We will be able to find a time that works for the patient and the diabetes educator.

• Plan: We will start the test with one doctor and one patient. On Tuesday, Dr. J will ask one patient if they would like more information on how to manage their blood sugar. The scheduler will confirm an appointment with the diabetes educator if they say yes.
• Do: Dr. J asked their first patient with diabetes on Tuesday. The patient was excited to schedule the appointment.
• Study: Patient was appreciative of the offer. We were able to schedule an appointment within one week.
• Act: No change to the process yet, but we will have to keep an eye on the workload of the diabetes educator. For the next PDSA cycle, Dr. J will ask the next five patients and work with the scheduler to create planned visits for those who say yes.

Tips for Testing Changes

• Plan multiple cycles for a test of a change and think a couple of cycles ahead. When designing a test, imagine at the start what the subsequent test or two might be, given various possible findings in the "Study" phase of the PDSA cycle. For example, teams that are redesigning same-day admission criteria should also be planning how those criteria will be applied.
• Scale down the size of the test. For example, scale down the number of people involved in the test ("sample the next 10" instead of "get a sample of 200"), and the location or duration of the test ("test it in Operating Room #1 for one week"). Be innovative to make the test feasible.
• Choose easy changes for early tests and don’t reinvent the wheel. Look for the concepts that seem most feasible and will have the greatest impact. Adopt or adapt successful changes made elsewhere, for example, instead of creating your own treatment protocol try modifying another hospital’s protocol.
• Test with willing volunteers.
• Do not try to get consensus when testing as this may delay your efforts and learning. When possible, choose changes that do not require a long process of approval, especially during the early testing phase. Consensus and "buy-in" are necessary for implementation, but not when testing.
• Test over a wide range of conditions (day of the week, provider, etc.). Try a test quickly; ask, "What change can we test by next Tuesday?"
• Collect useful quantitative and/or qualitative data during each test. Avoid technical slowdowns, like waiting for new software to be installed, and instead try recording test measurements and charting trends with paper and pencil.
• Reflect on the results of every change. After making a change, a team should ask: What did we expect to happen? What did happen? Were there unintended consequences? What was the best thing about this change? The worst? What might we do next? Too often, people avoid reflecting on failure. Remember that teams often learn very important lessons from failed tests of change.
• Be prepared to end the test of a change. If the test shows that a change is not leading to improvement, the test should be stopped. Note: "Failed" tests of change are a natural part of the improvement process. If a team experiences very few failed tests of change, it is probably not pushing the boundaries of innovation very far.  

Linking Tests of Change

​Testing changes is an iterative process: the completion of each Plan-Do-Study-Act (PDSA) cycle leads directly into the start of the next cycle.

A team learns from the test — What worked and what didn't work? What should be kept, changed, or abandoned? — and uses the new knowledge to plan the next test. The team continues linking tests in this way, refining the change until it is ready for broader implementation.

Note: People are far more willing to test a change when they know that changes can and will be modified as needed. Linking tests of change helps overcome an individual’s natural resistance to change by developing staff trust that ineffectual changes will not be mandated, and making the results observable.

Example Linked Tests of Change

Decrease length of stay (LOS) for emergency department (ED) patients with x-rays

• PDSA 1: Test quick-look for extremity x-rays on one shift. Monitor LOS for patients with x-rays and error rate. Review results with Radiology.
• PDSA 2: Revise documentation process and try quick-look for two days.
• PDSA 3: Redesign viewing area and continue quick-look for two weeks.
• PDSA 4: Make quick-look standard practice and monitor.

Testing Multiple Changes

​Typically, teams test more than one change at a time. All of the changes are aimed at achieving the same ultimate goal. Teams must develop linked tests of change, moving from testing to implementation, for each change, thinking through how the changes are likely to interact.

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Example of Testing Multiple Changes

A team working on reducing the average extubation time for elective coronary artery bypass graft (CABG) patients worked on several changes at the same time. Each of the changes went through several linked Plan-Do-Study-Act (PDSA) cycles which are often referred to as a PDSA Ramp. Throughout the project, data on extubation time was collected in order to determine if the changes were resulting in improvement.

Change 1: Standardize pain management

In order to be extubated early, patients must not be too heavily sedated. The team began by revising the existing standards for postoperative pain management. Instead of using the traditional high dose of morphine, the team ran a series of PDSA cycles to develop, test, and eventually implement the use of smaller, more frequent doses. In this way, patients' pain was managed adequately, yet patients were awake enough to be extubated safely.

Change 2: Standardize anesthesia management

Patients cannot be extubated if they are heavily sedated. The team ran a series of PDSA cycles to develop, test, and eventually implement having anesthesiologists use lower doses of sedatives to prevent patients from remaining heavily sedated long after the surgery was completed.

Change 3: Establish a rapid weaning and extubation protocol run by nurses and respiratory therapists

The team ran a series of PDSA cycles to develop, test, and eventually implement a set of criteria that patients need to meet in order to be extubated safely, given the changes in anesthesia and pain management.

Change 4: Reduce delays in obtaining arterial blood gas (ABG) results

The team identified delays in obtaining ABG results and weaning parameters as barriers to early extubation. They ran a series of PDSA cycles to develop, test, and eventually implement assigning a dedicated respiratory therapist to obtain these results.

Model for Improvement question: What change can we make that will result in improvement?

While all changes do not lead to improvement, all improvement requires change. The ability to develop, test, and implement changes is essential for an individual, group, or organization that wants to improve.

System-level improvement usually requires fundamental changes to the design of the system that result in improved performance and outcomes without increasing costs — not just quick fixes to bring a system back into control or to a previous level of performance.

To answer the third question in the Model for Improvement — What change can we make that will result in improvement? —the following might be helpful:

• Careful examination of the existing system (using flowcharts, for example)
• Exploration of the current system attributes that get in the way of better performance (a cause and effect diagram might be useful)
• Investigation of best practices inside and outside your organization to understand what is possible

When generating ideas for change that will result in improvement, subject matter expertise is valuable. Ideas may come from the literature, point-of-care staff, customers of the system being improved, researchers, and other experts,  and should be adapted for the local context. Developing a theory (or conceptual model sometimes represented in a driver diagram, for example) that organizes and describes how the changes will result in improvement in the system is a key part of getting started.

Another useful set of tools for identifying changes are “change concepts” — general notions or approaches to change that have been found to be useful in developing specific ideas for changes that lead to improvement. Creatively combining these change concepts with knowledge about specific subjects can help generate ideas for tests of change. 

Wherever you find your ideas for change, run Plan-Do-Study-Act (PDSA) cycles to test a change or group of changes on a small scale to learn how they work in your local environment and see if they result in improvement. If they do, expand the tests and gradually incorporate larger samples and under a variety of conditions until you are confident that the changes can and should be implemented and adopted more widely.

The change concepts included here were developed by Associates in Process Improvement (see The Improvement Guide [Langley GJ, Nolan KM, Nolan TW, Norman CL, Provost LP. San Francisco: Jossey-Bass Publishers, Inc.; 2009] for a list of 72 change concepts, as well as examples of how they were applied in process improvement, both inside and outside of health care).

Examples of Categories of Change Concepts

Eliminate Waste

In a broad sense, waste can be considered as any activity or resource in an organization that does not add value to an external customer. Some possible examples of waste are materials that are thrown away, rework of materials and documents, movement of items from one place to another, inventories, time spent waiting in line, people working in processes that are not important to the customer, extra steps or motion in a process, repeating work that has previously been done by others, over-specification of materials and requirements, and more staff than required to match the demand for products and services.

Toyota is famous for focusing improvement on the following "seven wastes":

• Waste of overproduction
• Waste of waiting
• Waste of transportation
• Waste of processing itself
• Waste of inventory (stock)
• Waste of motion
• Waste of producing defective parts or products

Improve Workflow

Products and services are produced by processes. How does work flow in these processes? What is the plan to get work through a process? Are the various steps in the process arranged and prioritized to obtain quality outcomes at low costs? How can we change the workflow so that the process is less reactive and more planned? A flowchart is a great tool for understanding your existing processes and envisioning improvement in workflow.

Optimize Inventory

Inventory of all types is a possible source of waste in organizations. Inventory requires capital investment, storage space, and people to handle and keep track of it. In manufacturing organizations, inventory includes raw material waiting to be processed, in-process inventory, and finished goods inventory. For service organizations, the number of skilled workers available is often the key inventory issue. Extra inventory can result in higher costs with no improvement in performance for an organization. How can we reduce costs associated with the maintenance of inventory? Understanding where inventory is stored in a system is the first step in finding opportunities for improvement. 

The use of inventory pull systems such as "just-in-time" is one philosophy of operating an organization to minimize the waste from inventory. In a pull system of service, the timely transition of work from one step in the process to another is the primary responsibility of the downstream (i.e., subsequent) process. This is in contrast to most traditional push systems, in which the transition of work is the responsibility of the upstream (i.e., prior) process.

Change the Work Environment

What would make the environment better able to support improvement? Examples of change concepts to change the work environment include the following:

• Invest more resources in improvement
• Give people access to information
• Conduct training
• Implement cross-training
• Develop alliances and cooperative relationships

Producer/Customer Interface

To benefit from improvements in quality of products and services, the customer must recognize and appreciate the improvements. Many ideas for improvement can come directly from a supplier or from the producer's customers. Many problems in organizations occur because the producer does not understand the important aspects of the customers’ needs or customers are not clear about their expectations from suppliers. The interface between producer/provider and their customers presents opportunities to learn and develop changes that will lead to improvement.

Manage Time

This age-old concept provides an opportunity to make time a focal point for improving any organization. An organization can gain a competitive advantage by reducing the time to develop new products, waiting times for services, lead times for orders and deliveries, and cycle times for all functions in the organization. Many organizations have estimated that less than five percent of the time needed to manufacture and deliver a product to a customer is actually dedicated to producing the product. The rest of the time is spent starting up or waiting.

Focus on Variation

Everything varies! But how does knowing this help us to develop changes that will lead to improvement? Many quality and cost problems in a process or product are due to variation. The same process that produces 95 percent on-time delivery or good product is the same process that produces the other 5 percent of late deliveries or bad product. Reduction of variation in such cases will improve the predictability of outcomes (may actually exceed customer expectations) and help to reduce the frequency of poor results.

Error Proofing

Errors occur when our actions do not agree with our intentions even though we are capable of carrying out the task. Often, we have to act quickly in a given situation or are required to accomplish a number of tasks sequentially or even simultaneously. Making these slips is part of being human. We might do such things as:

• Forget to enter information or enter it incorrectly
• Leave out a step in a process or do them in the wrong sequence
• Include the wrong merchandise in a shipment
• Try to use something in the wrong way
• Put something together wrong

Although these errors or slips are the result of human actions, they occur because of the interaction of people with a system. Some systems are more prone to error than others. We can reduce errors by redesigning the system to make it less likely for people in the system to make errors. This type of system design or redesign is called error proofing.

Focus on the Product or Service

What improvements can you make to the design of the product or service? Examples of change concepts that focus on the product or service include the following:

• Mass customize
• Reduce the number of components
• Change the order of process steps
• Differentiate using quality dimensions

Model for Improvement question: How will we know that a change is an improvement?

Measurement is a critical part of knowing if we have made a difference, what the impact of the changes are, if we have met our aim, and future action to take. When selecting measures, it is vital to include the people whose lives will be impacted by the improvement to have a voice in deciding what measures are important from their perspective. While aims often center around a quantitative aim or target, it’s important to measure your improvement work using quantitative and qualitative data.

Measurement for improvement should not be confused with measurement for research. This difference is outlined in the table below.

Three Types of Measures

Use a set of measures (typically 4 to 10) in order to track change and learning over time across different areas of the system (or processes). The three types of measures commonly used include: outcome, process, and balancing measures. 

Disaggregating data (stratification) to show potential systemic inequities can be an important strategy for ensuring that improvement efforts close rather than maintain or widen equity gaps (e.g., race, ethnicity, ancestry, language, sexual orientation, gender identity). 

Outcome Measures 

Linking back to the numeric goal within the aim statement, the outcome measure indicates how the system is working, specifically the impact on the customers/patients. Typically there is one outcome measure for an improvement initiative, and at times, there may be a need for two. 

Examples: 

• For diabetes: Average hemoglobin A1c level for BIPoC patients with diabetes 
• For access: Number of days to 3rd next available appointment 
• For critical care: Intensive Care Unit (ICU) percent unadjusted mortality 
• For medication systems: Adverse drug events per 1,000 doses 
• For population health: Number of children under 10 years old experiencing hunger 

Process Measures 

Are the parts/steps in the system performing as planned? Are we on track in our efforts to improve the system?

Examples: 

• For diabetes: Percentage of BIPoC patients whose hemoglobin A1c level was measured twice in the past year 
• For access: Average daily clinician hours available for appointments 
• For critical care: Percent of patients with intentional rounding completed on schedule 
• For population health: Number of children under 10 years old receiving school meals 

Balancing Measures (looking at a system from different directions/dimensions) 

Are changes designed to improve one part of the system causing new problems in other parts of the system? 

Examples:

• For reducing time patients spend on a ventilator after surgery: Make sure reintubation rates are not increasing 
• For reducing patients' length of stay in the hospital: Make sure readmission rates are not increasing

Tips for Effective Measures

Plot Data Over Time

Improvement requires change, and change is, by definition, a temporal phenomenon. Much information about a system and how to improve it can be obtained by plotting data over time, such as data on length of stay, volume, patient satisfaction — and then observing trends and other patterns. Tracking a few key measures over time is the single most powerful tool a team can use. [See additional information below.]

Seek Usefulness, Not Perfection

Remember, measurement is not the goal; improvement is the goal. In order to move forward to the next step, a team needs just enough data to know whether changes are leading to improvement.  Also, try to leverage existing measures the team is already collecting data for and reporting on so it’s also easier and not additional work.

Use Sampling

Sampling is a simple, efficient way to help a team understand how a system is performing. In cardiac surgery, the patient volume is typically low enough to allow tracking of key measures for all patients. However, sampling can save time and resources while accurately tracking performance. For example, if accurate data is not easily available through automated administrative databases, instead of monitoring the time from catheterization to cardiac surgery continuously, measure a random sample of 10 to 20 cardiac surgery patients per month.

Example: Use Sampling

Below is an example of using sampling in measuring the time for transfer from the emergency department (ED) to an inpatient bed.

Rapid movement from the ED after a decision to admit the patient is critical flow for entry to the entire system for emergent patient care. It represents the ability of patients with various illnesses to get into the system through the most common admission route.

Sampling approach: The measurement will consist of 6 weekly data collections of 25 patients each. The patients can be sampled in several ways, such as in one of the three ways described as follows:

• 5 patients per day for 5 days of the week (patients must be consecutive and at least one day must be a weekend day)
• 25 consecutive patients regardless of any specific day, except that it must include some weekend admissions
• If there are fewer than 25 admissions for a week, the total admissions for the week should be included in the sample

The time is measured from the decision to admit to the physical appearance of the patient into the inpatient room. The destination cannot be a "holding area" but must be a "real inpatient bed." The sample collection should be done in real time, so a data collection process needs to be worked out by members of the team to achieve this goal. The collections must be done weekly and summarized as the percentage of patients in the sample that achieved the goal for that week. Six weeks of data needs to be collected and six data points placed on a run chart.

Integrate Measurement into the Daily Routine

Useful data are often easy to obtain without relying on information systems. Don’t wait two months to receive data on patients’ average length of stay in the hospital from the information systems department. Develop a simple data collection form and make collecting the data part of someone’s job. Often, a few simple measures will yield all the information you need.

Use Qualitative and Quantitative Data

In addition to collecting quantitative data, be sure to collect qualitative data, which often are easier to access and highly informative. For example, ask the nursing staff how weaning from medications is going or how to improve the sedation protocol. Or, in order to focus your efforts on improving patient and family satisfaction, ask patients and their families about their experience of the cardiac surgery process.

Plotting Data Over Time

Plotting data over time using a run chart is a simple and effective way to determine whether the changes you are making are leading to improvement. Annotate the run chart to show the changes you made.   

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Model for Improvement question: What are we trying to accomplish?

The three fundamental questions in the Model for improvement can be addressed in any order, although teams typically start with the first question — What are we trying to accomplish? — to guide them in setting aims.

Answering the model’s three questions is an iterative process — the team moves back and forth between them as changes in thinking in one question or learning from PDSA cycles results in changes in thinking in another.

Setting an initial aim is essential to starting an improvement initiative. An organization will not improve without a clear and firm intention to do so.

Elements of an effective aim: 

• What we are improving
• By what date and how much we want to improve: Time-bound and measurable (how much? by when?)
• For/with whom are we doing this work: Define the specific population whose lives will be affected by the improvement effort
• Where the improvement is taking place

Agreeing on the aim is crucial, as is allocating the people and resources necessary to accomplish the aim. Engage the individuals who will most benefit from the improvement on the improvement team and in defining the aim.

To help develop improvement project aims, health care organizations often use the six overarching "Aims for Improvement" outlined in the 2001 report, Crossing the Quality Chasm: A New Health System for the 21st Century:

• Safe: Avoid injuries to patients from the care that is intended to help them.
• Effective: Match care to science; avoid overuse of ineffective care and underuse of effective care.
• Patient-Centered: Honor the individual and respect choice.
• Timely: Reduce waiting for both patients and those who give care.
• Efficient: Reduce waste.
• Equitable: Close racial and ethnic gaps in health status.

Tips for Setting Aims

Co-Design the Aim

Ensure that individuals who will most benefit from the improvement are members of the team that is defining the aim(s). “Customers” of the process, individuals with lived/living experience, and stakeholders in the community that receive care all have insights into the experience of care, what is likely to be successful, and know how to engage people in change that the health system cannot access alone.

Choose Aims That Explicitly Close Equity Gaps

Look at why one group of individuals may be experiencing different outcomes than other groups. Explicitly call out systemic barriers like racism, ageism, primary language, and other factors that have led to the inequitable outcomes that you seek to address with the improvement project. Remember that improving for all may lead to equality but not to equity, while improving for those with the worst outcomes will benefit everyone.

State the Aim Clearly

Teams make better progress when their aims are specific, clear, and simple. The essential elements of an aim statement include:

• What we are improving
• By what date we want to see improvement, ideally expressed as month and year (e.g.,“by October 2028”) rather than as a general timeframe (e.g., “within 10 months”)
• How much we want to improve (what success would look like), stated in numerical goals
• For/with whom are we doing this work
• Where we are doing the work
• Sometimes explaining why is also helpful

Include Numerical Goals When Possible

Teams are more successful when they have unambiguous, focused aims, ideally with numeric goals that clearly signal what success would look like. This helps to create a burning platform for change from the current performance to improved performance.

For example, the aim "Reduce preterm births among Black birthing people" is not as effective as "Reduce preterm births among Black birthing people from 15% to 9% by August 2025." The numerical goals also help team members begin to think about what their measures of improvement will be, what changes they might test, and what level of support they will need.

However, numerical goals must be established rationally — there should be a clear line of site between the theory of what changes are likely to result in improvement, the resources allocated, the measurement system, and the numerical goals stated in the aim.

Set Stretch Goals

A "stretch" goal is one to reach for within a certain time. Setting stretch goals in an aim statement — such as "Reduce preterm births among Black birthing people from 15% to 9% by August 2025" — communicate immediately and clearly that maintaining the status quo is not an option.

Effective leaders make it clear that the goal cannot be met by simply tweaking the existing system. Once this is clear, people begin to look for ways to fundamentally redesign the current system and overcome current barriers to achieve the stretch goals. Be sure to align stretch goals with the system identified, the scope of the change ideas, and the resources available to the team.

Be Careful of Aim Drift

Once the aim has been set, the team needs to be careful not to back away from it deliberately or "drift" away from it unconsciously. The initial stretch goal "Reduce preterm births among Black birthing people from 15% to 9% by August 2025" can drift to become "Reduce preterm births among Black birthing people to 12%” — or the focus can shift to something different and less explicit, such as “Improve the experience of Black birthing people.” Revising the initial aim isn’t necessarily a bad thing, as long as the change is acknowledged explicitly by the team and relevant stakeholders and the revised aim includes best-practice elements.

To avoid drifting away from the aim, repeat the aim continually. Start each team meeting with an explicit statement of aim — "Remember, we’re focusing on reducing preterm births among Black birthing people from 15% to 9% by August 2025" — and then review progress quantitatively over time.   

Be Prepared to Refocus the Aim

Every team needs to recognize when to refocus its aim. If the team’s overall aim is at a system level (e.g., "Increase access to cancer care for Latinx patients by reducing waiting time for appointments from 4 weeks to 2 weeks by January 2026"), team members may find that focusing for a time on a smaller part of the system (e.g., "Increase access to breast cancer screening for Latinx patients by 30% by May 2025") will help them achieve the desired system-level goal.

Note: Don’t confuse aim drift or backing away from a stretch goal (which usually isn’t a good tactic) with consciously deciding to work on a smaller part of the system (which often is a good tactic).

Examples of Effective Aim Statements

• Improve the patient experience during delivery for Black birthing persons as measured by an increase in patients reporting they were listened to from 25% to 75% by June 2024
• Increase colon cancer screening rates among patients ages 50+ who identify as Chinese from 50% to 70% by May 2025
• Reduce harm from use of anticoagulants from the current rate of 1.8 per thousand admissions to less than 1.4 by January 2025 and less than 1 per thousand admissions by January 2026
• Reduce waiting time to see a physician for all patients ages 65+ who identify as Black, Indigenous, or people of color to less than 15 minutes by July 2024
• Increase the percentage of patients whose primary language is not English that are transferred from the emergency department to an inpatient bed within 1 hour of the decision to admit from 25% to 50% by March 2024
• Increase the percentage of patients ages 50+ who self-identify as Black, Indigenous, or people of color that are transferred from the inpatient facility to a long-term care facility within 24 hours, after the patient is deemed ready to transfer, from 58% to 75% by April 2026
• Reduce average ventilator days by 2 to 4 days per discharge by November 2024
• Reduce adverse drug events (ADEs) per ICU day by 75% (or absolute number of less than 0.10 ADEs per ICU day) by December 2026

Improvement work thrives with a team. People involved in parts of the process or system that you are trying to improve will bring diverse perspectives and expertise to fuel more effective ideas for change that are more likely to be sustained while building will to make improvements.

Improvement teams vary in size and composition. Each organization forms teams to suit its own needs and the needs of the specific improvement effort.

First, review the purpose of the improvement initiative (you may or may not have a specific aim, yet, when you pull the team together).

Second, consider the system that relates to that purpose: What are the boundaries of the system that will be affected by the improvement efforts?

Third, ensure that the team includes members who are familiar with all the different parts of the process — leaders, managers, and administrators as well as those who work in the process, including physicians, pharmacists, nurses, point-of-care staff, and other subject matter experts.

Consider which “customers” or individuals with lived and living experience are most likely to benefit from the improvement and engage them as members of the team. 

When forming an improvement team, it is vital to apply an equity lens. Some questions to ask with an equity lens include the following:

• Who is invited to contribute input to the improvement effort to identify the desired outcome, measures, and change ideas?
• Whose expertise is valued? The people who are most affected by the improvement opportunity need to be represented in the team that is designing the work and ideally throughout the lifespan of the improvement effort.
• Are people who are engaged in different parts of the process represented? Who is missing?

Finally, each team needs an executive sponsor who takes responsibility for aligning the project to the organizational strategy, relieving bottlenecks, allocating resources, and supporting the improvement opportunity.

Team Roles

Effective teams include members representing different knowledge and experience of the system: system leadership, technical/subject matter expertise, day-to-day leader or process owner, and user/customer experience. There may be one or more individuals on the team with each kind of expertise, or one individual may have expertise in more than one area, but all areas should be represented on the team to successfully drive improvement.

Experience in the Process/System

Include team members who have knowledge of the process or system that is being improved and who represent a range of perspectives (e.g., patients, providers). Think about the end user and co-design with those individuals instead of for them. The team also needs someone with enough authority in the organization to test and implement a change and who understands both the clinical implications of proposed changes and the consequences such a change might have in other parts of the system.

Day‐to‐Day Leader or Process Owner

The process owner is usually the day-to-day improvement team leader. A day-to-day leader is the driver of the project, assuring that tests are implemented and overseeing data collection. It is important that this person understands not only the details of the system, but also the various effects of making change(s) in the system. After the improvement project ends, the process owner continues to be involved in implementing and maintaining the improvement.

Experience with Improvement Methods

At least one team member should have experience with improvement methods, such as through participating in past quality improvement (QI) initiatives or through formal QI training. A team member with improvement methods expertise can provide additional technical support by helping the team determine what to measure, assisting in design of simple, effective measurement tools, and providing guidance on collection, interpretation, and display of data.

Technical/Clinical/Subject Matter Expertise

Subject matter experts have expertise in areas relevant to the improvement project. They may not be able to attend all team meetings (in health care, this is especially true for busy clinicians), but should be consulted and engaged to the extent they are willing and able.

Project Sponsor (System Leader)

In addition to the working members listed above, a successful improvement team needs a sponsor, someone with executive authority who can provide liaison with other areas of the organization, serve as a link to senior management and the strategic aims of the organization, provide resources and overcome barriers on behalf of the team, and provide accountability for the team members. The sponsor is not a day-to-day participant in team meetings and testing, but needs to review the team's progress on a regular basis.

Example Team: Improving Care in Office Practices

Aim: We will improve care for all patients with chronic illness by making improvements in our clinic such that measures of patient experience (specifically percent reporting they are listened to and treated with respect) for patients who self-define as Black, Indigenous, or people of color increases from 25% to 75% within 18 months.

Team:

• Technical Expert: ____, MD, Physician at downtown primary care clinic
• Day-to-Day Leader: ____, RN, Manager of downtown primary care clinic
• Team Members:
  • Patient educator
  • Medical assistant
  • Clerk/scheduler  
  • Quality expert
  • Two to five patients who self-define as Black, Indigenous, or people of color and their family members
• Sponsor: ______, MD, Medical Director for primary care practices

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