Importance of Topic to Practice
Quality improvement (QI) has been an increasing area of focus in health care since the late 1990s and is a growing area of interest in health care models, mandates and legislation globally (1,2). Dietitians are integral members of health care teams, and knowledge of QI methodologies and practices is essential for the ability to participate in and enable health care innovation, change and sustainability. While dietitians are trained in research methods, traditional dietitian curriculum has been limited in quality improvement methodologies. The overall aim of this background is to provide an overview of QI methodology and how integrating QI into dietetic training and practices can facilitate improved outcomes for clients/patients, communities and the health care system.
Definition of Quality Improvement
In the context of health care, QI is an applied science that is centered on learning (3). QI is typically defined as having the core components of a stepwise approach to problem-solving, data-driven methods and shorter duration tests to increase the speed that these changes are applied to health care systems (4,5). Other definitions have evolved that continue to put a focus on client/patient outcomes. QI is also often called continuous QI or continuous process improvement.
Batalden and Davidoff describe QI as: “the combined and unceasing efforts of everyone—healthcare professionals, patients and their families, researchers, payers, planners and educators—to make the changes that will lead to better patient outcomes (health), better system performance (care) and better professional development” (6). An aligned definition offered by Lynn is: “systematic, data-guided activities designed to bring about immediate improvements in health care delivery in particular settings” (4).
The Triple Aim and Quadruple Aim are internationally recognized frameworks that focus on improvement in designing and delivering an effective health care system. The four objectives of the Quadruple Aim are:
- improving the patient and caregiver experience
- improving the health of populations
- reducing the per capita cost of health care
- improving the work life of providers (7).
The 2001 Institute of Medicine report outlined six quality dimensions for the 21st century health system (8). Most QI initiatives in health care are directly linked to one of these aims:
Dietetic-focused improvement projects can easily align with one or more of the six key aims listed above.
The specific focus of improvement can fundamentally vary due to methodology. For example, a main improvement language, Lean, is focused on the elimination of waste (e.g. time, defects, waiting, extra processing, etc.) (5). Its mechanism to improve care, and the model for improvement, has the focus of identifying and solving a problem through a series of testing changes (5). Improving care for the client/patient or customer is a commonly used language in improvement models. Six Sigma, which will not be discussed in length in this document, is focused on process control, elimination of variation, perfection and defect-free production (9). This is much more prevalent in manufacturing; however, it is used in areas of health care that have repeated standardized tasks with a consistently expected outcome (i.e. lab sample processing, supply chain management).
Some of the early QI work outlines a framework for understanding the work systems, called profound knowledge, that is composed of four key parts that relate to each other:
- appreciation for a system
- understanding of variation
- building knowledge
- human side of change (10).
This framework illustrates some of the differences from traditional research by applying both systems thinking and change management thinking to health care innovation.
Quality Improvement and its History in Health Care
Lean and QI are still both relatively new concepts and areas of study within the area of health care. The historical initiation of both Lean and the Model for Improvement that are recognizable in health care date back to industrial roots in the early 20th century (3,11). The history of QI in the health care and service industries can be largely attributed to the work of W. Edwards Deming (1900-1993), Walter Shewhart (1891-1967) and Joseph Juran (1904-2008). While these individuals are largely to be credited for the models of QI that are known and employed in health care, Florence Nightingale's famous quotes indicate that improvement thinking was already present in health care (12,13): “improved statistics would tell us more of the relative value of particular operations and modes of treatment than we have any means of ascertaining at present…and the truth thus ascertained would enable us to save life and suffering, and to improve the treatment and management of the sick” (13).
The history of QI goes back beyond 1940 (3). The QI models that are recognizable now, start largely with the work of Deming and Juran and the Toyota Motor Corporation where the system now known as Lean was created (1940-1960) (3). The expansion to other sectors (service and health care) globally was not until the late 1990s and continues to grow. The publication of two Institute of Medicine reports were critical to the current day focus on QI in health care: 1999 (To Err is Human) (14) and 2001 (Crossing the Quality Chasm) (8).
Quality Improvement and Practice-based Research: What Is the Difference?
QI and research are not inherently opposing or challenging methodologies. In 1997, Solberg et al. detailed that improvement, accountability and research are different processes with different aims, audiences, purposes, scope, measures, statistical processes and methods (15). This has been revised and printed in the health care data guide (16). The definitive difference between research and improvement is that improvement models aim to improve processes and care or make something that already exists better, while clinical research is ultimately designed to create or confirm knowledge (15,16). Both are important to dietetic practice.
Table 1: Differences Between Quality Improvement, Judgement or Accountability and Research (16)
Judgement or Accountability
Improvement of care process, system and outcomes
Judgement, choice, spur for change
New generalizable knowledge
No test, evaluate current performance
Accept Consistent Bias
Measure and adjust to reduce bias
Design to eliminate bias
“Just enough” data, small sequential samples
Obtain 100% of available and relevant data
“Just in case” data
Flexibility of hypothesis
Hypothesis flexible; changes as learning takes place
One Large Test
Determining if the change is an improvement
No focus on change
Hypothesis tests (t-tests, F-tests, Chi-square), p-value.
Confidentiality of data
Data used only by those involved in the improvement
Data available for public consumption
Research subjects’ identities are protected.
(Used with Permission).
Despite research and QI not conflicting, the publication of QI-based research has been slow (4). The publication gap in QI is due to multiple reasons. Clinicians who are participating in improvement projects are not often prepared nor do they have the capacity to prepare academic publications. After completing local quality improvement projects, it then stays local. Medical journals are also predominantly focused on traditional research methods, including publication requirements of specific statistical modelling and the involvement of research ethics boards. These journals are often staffed by those with academic research experience that is dedicated to the creation of new knowledge (4). There was limited guidance on publication standards for QI until the Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines were developed (17,18). The SQUIRE guidelines offer guidance and support to those publishing about health care improvement similar to guidelines that exist for other areas of research and publication.
Contributors to Success in Quality Improvement
There has been much written on the contributors to success in QI and the learned barriers to QI adoption in health care (19). Based on a review of the literature and rounds of opinion gathering and expert opinion, a framework for the success of improvement initiatives in an organization was published in 2011 (20). The framework and since developed tools to evaluate the likelihood of success summarizes the drivers towards success as 25 unique factors within six categories being:
- factors from the external environment
- organizational factors
- QI support and capacity
- the QI microsystem
- the specific QI team
- few miscellaneous factors.
The importance of this framework is that it gives structure to implementing QI and supports the success of QI initiatives and the publication of QI research.
Relevance of Quality Improvement in Dietetics Practice
In 2003, McGlynn et al. published a study that became a core fundamental paper defining the need for QI in health care (21). McGlynn et al. showed that only 54.9% of participants received recommended care as defined by research and best practice guidelines. The study looked at recommended care from the evidence-based model, many being systematic reviews for various diseases and conditions (21). This demonstrates that despite there being a large amount of literature on what best practice is, and should be, there is an ongoing need to support the translation of evidence into practice and to develop and support this implementation as a field of study of its own (5,22).
Quality improvement aims to support clinicians to use rapid changes to test the methods and applications of best practice and/or planned change ideas within their settings (5,23,24). Improvement science and methodology are often incorrectly assumed to be separate or opposing to evidence-based research or to not consider clinical evidence (3). Subject matter knowledge, including published best practice guidelines, is a key component of improvement science. Improvement science also incorporates elements such as the psychology of change, the appreciation of the system in which care is provided and the variation that occurs in these settings (24). Perla et al. summarized that the science of improvement is made up of two parts, the philosophy (the system of profound knowledge) of improvement and the application (methods, tools, subject matter knowledge and innovation and testing), ultimately leading to implementation and spread.
Quality improvement seeks to add to this knowledge through the application of tools, methods and processes, and most differently, the focus on small rapid testing to allow clinicians to determine how to apply knowledge to the populations with which they work (3).
As described by Parry, Rossi’s Iron Law occurs when an intervention is applied broadly to multiple settings and concepts without being tested and the effectiveness of the intervention decreases significantly (3). This is largely due to the need for testing.
Relevant Basic Information
Quality Improvement Models
QI is widely accepted as a rapid, stepwise approach to problem-solving using a systematic approach that begins with a problem or a challenge, not a solution or a desired end state (5,9,23). There are a variety of different improvement models that are all largely derived from the same core principles developed by Juran, Deming and others (5). There are structural consistencies between the models including problem definition, root causes analysis, testing improvements, implementation, and spread and scale (9). The models that exist arose from different developmental origins. Lean and Six Sigma are largely derived from the automotive industry specifically (25). The Model for Improvement and its approaches are focused on improvement, considering both the system that the change needs to occur within, and the methods and tools to improve it (5,23).
The models used in health care applications vary between countries and sectors, with variation in adoption and support of different parts of the models (2). In a study of QI adoption in European countries, national governments were most often found to be the drivers of the accepted QI policies, standards and targets (2). This is largely due to the mandatory legal requirement in many countries that health care organizations have QI plans (1,2,26)
All improvement methodologies have consistent core components: commitment of the organization to quality; focus on the customer or consumer; modification of systems, not people; ability to foster teamwork; and encouraging group problem-solving (27).
Model for Improvement
The Model for Improvement was designed in 1996 by the Associates for Process Improvements (API) as a method to guide improvement work (8). This method is the core component of the Institute for Healthcare Improvement (IHI)-QI approach (5). This model is easily applied to a large health care organization, cross-organizational projects or a small scale, single provider, single location initiative. The model focuses on a series of clarifying questions starting with identifying the aim by asking “what are we trying to accomplish”, then identifying the measures by asking “how will we know if a change is an improvement”, and then looking at what can be tested “what change can we make that will result in an improvement" and then a mechanism for testing change ideas for testing changes (PDSA: plan, do, study, act) (23).
Image 1: The Model for Improvement (23)
(Used with Permission).
Lean methodology, while derived from the same founders (Juran and Deming), is rooted in manufacturing and is largely attributed to Taiichi Ohno and the development of the Toyota Production System (28). This model is focused on the increase in customer value, largely focused on the elimination of waste and the focus on improvement in efficiency through the standardization of repeated processes (5). Many health care organizations have adopted this model; however, the language and the tools can be complex and detailed, leaving some to feel ill-equipped to use them.
Others Including Human-centred Design
Design thinking and human-centred design are newer models of improvement, which are slightly different from the aforementioned, yet share many similarities. Design thinking roots itself in the client/patient experience and empathy for users and applies a methodology of rapid change often referred to as action-oriented rapid prototyping (29). Similar to both Lean and the IHI model of QI, it is a model based on holding on implementation until prototyping and testing have been accomplished. The component of the model closest to PDSA or PDCA: (plan, do, check, act) is that of Ideation - Prototype - Testing (29).
How to Start Using Quality Improvement
There are many how-to guides published on QI specifically for health care providers (30). The model that is simplest to use is aligned with the model for improvement and the IHI-QI approach (5). The tools and structures recommended from here forward in this background will focus on that approach. There are a number of “how-to” guides and QI basic guides, including the Institute for Healthcare Improvement’s Quality Improvement Essentials Toolkit (30) and the Health Quality Ontario’s Quality Improvement Guide (31).
Steps to Starting Any Quality Improvement Project
Identify a Team or Project Group(s)
Improvement in health care is multifaceted and impacts many, including other staff, departments and clients/patients. Don Berwick wrote about the shift using two Japanese words, taseki and jisei (32). Taseki roughly translates to “the burden is yours” and jiseki translates to “the burden is ours”.
The inclusion of client/patient and experiential voices into quality improvement projects is starting to receive more documented success, indicating why experience-based co-design is necessary for this work (33).
Improvement teams should be limited in size, focused on the problem and include specific roles such as lived experience, clinical leadership, technical leadership, executive/management sponsorship and QI leadership and facilitation (31).
Identify and Refine the Understanding of the Problem
Once the group is formed, the next step involves understanding the problem that needs to be solved in partnership with the team and clients/patients.
To understand the problem in more detail, the root cause(s) often need to be explored. Often, teams will have different perspectives as to the true cause of a problem, which may lead to lack of clarity on the focus of the improvement work (34). Root cause analysis has been a term used for over 50 years and is connected to high risk sectors (34). Common tools for supporting root cause analysis include the 5 Whys and Fishbone Diagrams (also known as an Ishikawa diagram) (30,34).
Table 2: Tools for Quality Improvement Root Cause Analysis
Where to Learn More
The 5 Whys analysis
The 5 Whys was developed at Toyota and is a simple tool that encourages the continued asking of the question “why?” until there is a singular answer that can be the basis of an improvement project (34).
The Fishbone Diagram
The Fishbone Diagram is a visual representation of all of the different elements that may contribute to a singular problem. There are standardized headings that can be used to help organize ideas and root cause attribution (34).
After the problem is identified, refining an aim statement can define the problem and focus the group on the work. Developing an aim statement is similar to writing a measurable goal that many dietitians use in practice with clients/patients. Health care goal setting has many methodologies, labels and variations in how it is done (35,36). Most improvement how-to guides or methods recommend following a framework that is similar to smart goals in determining what is being changed, by how much, by when. These questions and measures aligned like this work well with the model for improvement (23).
Before writing an aim statement, root cause(s) often need to be explored. Often teams will have different perspectives as to the true cause of a problem, which may lead to lack of clarity on the focus of the improvement work. Root cause analysis has been a term used for over 50 years and is connected to high risk sectors (34). Common tools for supporting root cause analysis include the 5 Whys and Fishbone Diagrams (also known as an Ishikawa diagram) (30,34).
Table 3: The Elements of an Aim Statement (31,35) (with examples)
Aim Statement Component
What needs to change?
What is the measure that is most connected to this problem?
No show rates
In what direction?
Increase or decrease?
By how much?
Knowing the baseline level of performance before starting is key to improving.
How much it should change can be informed by experience, best practice, evidence and other sources.
From 30% to 10%
Having time-bound goals will help the project team stay motivated towards the goal, and also encourage the team to move beyond testing into implementation.
By six months from the starting point of the project.
Identify the Measures
Improvement efforts aim to change something for the better (37). Thus, there needs to be a way to tell if there is a change, the extent the change leads to improvement and how the change will be implemented in a real work setting. Despite how obvious the need or the changes may feel, the science of QI relies on measures that can be tracked from establishing a baseline through to its implementation. Tracking change also allows for an evaluation of cost, social impact and intended or unintended impact of the proposed change. This can not only contribute to process improvement but help to minimize resistance that may occur when change is introduced in an organization.
When deciding an improvement focus, all improvement in health care will likely come from one of six dimensions of care including safety, effectiveness, patient-centeredness, timeliness, efficiency and equity (8).
Measures used to evaluate the effectiveness of QI projects fall mainly into three categories called a family of measures (8,23):
- Outcome Measures: outcome measures are typically the data that is the most closely connected to the aim statement or the impact or purpose of the change. What is the result? The impact on client/patient experience and/or health outcomes.
- Process Measures: these are measures of processes and tasks. Often, process measures calculate if and how the changes that were implemented are happening.
- Balancing Measures: monitoring unintended consequences when change occurs.
The Institute for Healthcare Improvement notes: “All improvement will require change, but not all change will result in improvement.” (23). This is relevant to improvement work because often measurement is not used in project management and changes that are perceived without statistical frameworks are often misunderstood and celebrated as successful or not when some relatively straightforward statistical processing would have shown the difference.
Data sources for quality improvement can be numerous, including:
- electronic medical records
- data registries (local, provincial, national or international)
- qualitative data (surveys, interviews, focus groups)
- manually collected data (time, counts etc.) (31).
QI methodologies rely on testing a flexible hypothesis with sequential tests of change (see testing changes below) (15). Testing sequential changes to identify if a change has caused an improvement required the use of data over time. Data over time is most commonly displayed in improvement work as run charts or control charts.
Hypothesis tests are not commonly used in improvement due to the testing of multiple changes in a sequential process with a flexible hypothesis (15).
Visualizing Data: Run Charts
The use of the run chart is considered a simple way to display data over time. Run charts display data in an order that is essential to answer the core improvement question “did it change?” (24). They are also referred to as line graphs and are commonly available in most spreadsheet software.
Image 2: An Example of a Run Chart Using Hypothetical Data
In a run chart, the vertical axis represents the change or outcome being studied, and the horizontal axis represents a continuous variable, such as time (24). The median is used as the center line and is calculated based on the baseline data. The median allows run chart rules to be used to interpret the change of the system being studied. Rules to interpret run charts are based on the frequency of data points in relationship to the median and based on direction. Terms that are used often and subjectively, like “trend” and “shift”, have a specific meaning when interpreting run charts.
Visualizing Data: Control Charts or Shewhart Charts
Control charts have similarities to run charts but incorporate visualization of variation. Variation is a key consideration in improvement work and the Deming system of profound knowledge (10). There is variation in most processes. Some of it is expected (common cause) and another variation is unexpected (special cause) (38,39). Control charts allow those studying the data to learn more about what is “normal” for a system’s performance vs abnormal or “special”. There are many types of control charts based on the features of data that is being presented.
Control charts also have a set of rules to aid in interpretation that revolves around the center line and the control limits (16).
Image 3: An Example of a Control Chart Using Hypothetical Data
Deciding whether to use a run chart or a control chart is usually considered as a matter of the amount of data that is available. If the work has just started and there are less than 12 data points, a run chart is usually sufficient until more data is collected (16). A control chart improves the learning by being able to illustrate when the system is showing “special” cause variation.
Change Idea Generation: Developing and testing changes is the “fun” part of QI and, at the same time, often the reason improvement methods do not work (23). Change ideas make up the “what changes will lead to improvement?” question in the model for improvement. Sometimes the ideas to be tested will come easily to the group, and other times it will feel more challenging to generate ideas to test. Talking to staff, clients/patients and families can help generate change ideas. If it is more challenging to find changes to test, change concepts were developed in 1996 by the Associates for Process Improvements (API). This is a list of 72 general, abstract notions that could help the group identify changes, such as:
- Eliminate things that are not used. (#1)
- Eliminate multiple entry. (#2)
- Use reminders. (#59)
- Adjust to peak demands. (#22)
Organizing change ideas can be done using different mapping tools such as a driver or a tree diagram, affinity diagram and others. Driver diagrams are excellent for reinforcing that the chosen change ideas and tests connect back to the original problem or improvement aim (23).
Image 4: Driver Diagram (Adapted from (23))
Developing and Testing Changes
Testing changes before doing the preceding steps often leads to money, time and resources being spent on solutions that cannot be confidently connected to the problem and the impact of the changes on improvement cannot be determined (40). For example: a new order entry software is purchased for a hospital to fix meal tray errors before understanding if the order entry tool was the problem.
Testing changes in QI is one of the most exciting elements. It is where ideas translate into action through a structured learning approach (40). Testing changes in rapid cycles leads to the ability to collect data quickly to be able to solve problems in a timely way. In comparison to the health care research-driven model of randomized control trials, the PDSA offers an approach for testing changes in a complex system (41,42).
PDSA or PDCA are the common terms for this testing. As discussed above, with each of the various improvement models, there is variation in the language of each stage; however, the simplicity of the 1993 framework from Deming (43) that has been adapted into the Model for Improvement is the most applicable and adaptable for clinicians.
Image 5: The Plan-Do-Study-Act Cycle from the Model for Improvement (16,23).
Plan - Plan a change or test
Do - Carry out the change
Study - Examine the results. What was learned?
Act - Adopt, adapt or abandon the change
A caution lies in the oversimplification of the PDSA cycle. The evidence around QI and its effectiveness continues to be mixed, with a 2014 review showing that only 20% of studies using a PDSA approach fully documented the steps of the PDSA model (41). This is in large part due to the perceived simplicity of the model and the lack of recognition that health care is a complex model and local level context matters.
There are worksheets embedded in many health system QI toolkits that outline the steps of planning and executing a PDSA cycle. Due to the noted lack of application and the oversimplification of this model for improvement, it is highly recommended that clinicians engaging in improvement use a template and tool (41).
Spread and Scale of Changes
Scaling and spreading improvement is the next step after testing and adopting changes (44). This means taking the idea beyond the local environment where it was tested and spreading it to other clients/patients, departments and staff. This is by no means a straightforward process and is an emerging area of research. The research currently suggests that there are lessons to be learned from complexity science, implementation science and social science frameworks (45). Frameworks for the spread and scale of health care improvement suggest that the following need to be in place to support the spread of an improvement in a health system (44-46):
- strong leadership
- a succinct summary of the ideas being spread
- setup: Identification of the audience, key partners and a spread plan
- a social system including a communication plan
- measurement and feedback systems.
Dietetic Practice and Regulatory Considerations
QI has been suggested as an appropriate methodology by some dietetic regulatory colleges and will continue to be an emergent area of practice-based research with professional practice implications for dietitians (47).
QI skills can be implemented by dietitians by thinking about the following questions as outlined in more detail above:
- What could be better for the individuals that my practice, organization or service supports?
- How do we know that that is a problem or how our performance on that has been?
- What could be tested to make that better?
- How will we know what changes to implement and spread to other areas?
Dietitians have a professional obligation to provide safe, ethical and competent services. Competencies for dietetic practice are developed to promote a shared understanding of competency required to promote and protect the health of clients.
In Australia, the National Competency Standards includes quality improvement as part of an overall domain on applying critical thinking and integrating evidence into practice looking at conducting research, evaluation and quality improvement for the dissemination of findings (47).
In Canada, the Integrated Competencies for Dietetic Education and Practice (ICDEP) aim, “to guide dietetic education, continuous quality improvement and registration with a regulatory body in Canada.” (48). Quality improvement is specifically addressed in competency of Professionalism and Ethics, which focuses on risk management, mitigation, control and elimination (48). A provincial example from the College of Dietitians of Ontario (CDO) encourages dietitians to embrace quality improvement and the quality aims proposed by the Institute of Medicine as outlined above (8,48).
Dietitians are encouraged to evaluate client priority, to refer clients appropriately, develop skillful communication, engage clients, collaborate with other health professionals and practice more effectively (49). This guidance is stronger with the support of tools and frameworks to enable dietitians to properly apply this advice.
In the U.K., quality improvement is embedded into the dietetic preregistration curriculum to support the student to demonstrate a critical, integrated and applied understanding of quality improvement (50). Dietitians in the U.K. are regulated by the health and care professions council (HCPC) who set the standards of proficiency (51). This includes a standard that requires dietitians to recognize the need to collect and monitor data to evaluate the quality of practice and be involved in quality improvement processes.
Key Resources for Professionals
Education materials for clients, practice guidelines and other professional tools and resources can be found under the Quality Improvement Knowledge Pathway
Related Tools and Resources tab. Use the Audience, Country and Language sort buttons to narrow your search.
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