While there are many approaches to improving the quality of care in health care settings, the following represent three common tools for conducting clinical improvement work. The Model for Improvement (MFI) is primarily emphasized because of its ease of adoption, and because it is the foundation for most improvement efforts included in the Maintenance of Certification program of the ABP. Briefer summaries of Lean and Six-Sigma methods are also included, with listings of resources where the reader can find additional information.
Widely taught and promoted by the Boston-based educational and advocacy organization the Institute for Healthcare Improvement (IHI), the MFI is grounded in three simple questions that guide the work of the improvement leader and team. The model’s framework includes an Aim statement, a measurement strategy, and then the use of “rapid cycle” changes to achieve the aim. The IHI website, www.ihi.org, has an extensive resource library, and hosts an “Open School” that includes a QI/Patient safety modular curriculum for health professional students and their faculty at www.ihi.org/openschool.
The Aim statement answers the question, “What do we want to accomplish?” The measure question is “How will we know that a change is an improvement?” and the change component is focused on “What changes can we make that will result in improvement?” This model is represented in Figure 1–2.
Model for improvement. (Adapted with permission from Langley G, Moen R, Nolan K, et al: The Improvement Guide: AIM Model for Improvement. San Francisco: Jossey-Bass; 2009.)
Aim statements are a written description of what the team’s improvement goal is, and also include information on who comprises the patient population and a time frame within which the improvement will be achieved. They identify a “stretch” but achievable improvement target goal, and, often, some general statement regarding how the improvement will be achieved. Aim statements are sometimes characterized using the mnemonic SMAART: Specific, Measurable, Achievable, Actionable, Relevant, and Timely. Aim statements should be unambiguous and understandable to the stakeholders, and are most likely to be achieved if they are aligned with the strategic goals of the team or organization.
For example, the following statement meets the criteria for a SMAART aim statement, “We will reduce the frequency of emergency department visits and hospitalizations for patients with asthma seen at E Street Pediatrics by 25% by December 31, 2017,” whereas this next statement does not, “We will improve the care for patients with asthma by appropriately prescribing indicated medications and better educating families in their use.”
The first example provides a specific measurable goal, a time frame, and clarity with respect to who the patients are. A 25% reduction in ED/inpatient asthma visits will require a change in the system for asthma care delivery for the entire population of children with asthma; that extent of level of improvement is a stretch, but it is much more achievable than a goal would be if it was set to “eliminate” such encounters. The second example is unclear in terms of the measure for improvement, the time frame for the goal to be met, and even the population in question. The statement provides some sense of processes that could be utilized to improve asthma care but is missing needed specificity.
Specific measures provide a means to assess whether or not the improvement effort is on track. Three types of measures are useful. Outcome measures answer questions concerning the health care impact for the patients, such as how has their health status changed? Process measures are related to the health care delivery system itself. They answer questions about how the system is performing. Balancing measures seek to identify potential unintended consequences that are related to the improvement effort being undertaken. Examples are helpful to contextualize these conceptual definitions.
Table 1–1 reflects some examples of types of measures that might be employed in an asthma QI initiative.
Table 1–1.Examples of types of measures used in an asthma QI initiative. ||Download (.pdf) Table 1–1.Examples of types of measures used in an asthma QI initiative.
|Outcome Measures ||Process Measures ||Balancing Measures |
|Percent of children with asthma in the practice seen in the ED or hospitalized for asthma in the past 6 months ||Proportion of children with an asthma severity assessment in their medical record in the past year ||Average difference in the time between the last office patient’s scheduled appointment time and the actual office close time |
|Percent of children with persistent asthma in the practice with fewer than five missed school days due to asthma in the past year ||Percent of children with persistent asthma, of any severity, prescribed a controller medication at their most recent visit ||Staff satisfaction with their job |
| ||Percent of children prescribed a controller medication who report taking their medicine || |
| ||Percent of children in a practice asthma registry provided with a complete asthma action plan in the past 12 months || |
One might argue that adherence to a treatment plan (third process measure) is an outcome of the work of the practice/practitioner prescribing the medication. It is more consistent, however, to consider the translation of the treatment plan into action as a part of the process of care, and that the health status or outcome measure will be improved by fully improving the measured processes of care, including patient adherence to the treatment plan.
Measures are essential elements of any improvement work. It is a good idea to choose a manageable (4–6) number of measures, all of which can be obtained with limited or no extra effort, and with a mix of outcome, process, and balancing measures. Ideally, the best process measures are those that are directly linked to the outcome goal. The hypothesis in this specific example would be that assessing asthma severity and appropriately using controller medications and action plans would all contribute to reducing the number or frequency of missed school days and the need for ED/hospital utilization.
It is important to note that measurement in the setting of an improvement project is different from measurement in a research study. Improvement projects require “just enough” data to guide the team’s continuing efforts. Often, the result seen in a sequence of 10 patients is enough to tell you whether a particular system is functioning consistently or not. For example, considering the first process measure in Table 1–1, if in the last 10 patients seen with asthma, only two had their asthma severity documented, how many more charts need be checked to conclude that the system is not functioning as intended and that changes are needed? Other measures may require larger sample sizes, especially when assessing the impact of care changes on a population of patients with a particular condition. See Randolph’s excellent summary for a fuller description of measurement for improvement.
Once the team’s aim is established and the measures are selected, the third component of the MFI draws from industrial engineering and focuses on what changes in the system must be made that will result in the targeted improvements. To answer the question “What changes will result in improvement?” the improvement team should incorporate “Plan-Do-Study (or check)-Act” cycles, typically referred to as PDSA cycles. The cycles include the following steps.
Plan: What will we do that will likely improve the process measures linked to the outcome target goal? Who will do it? Where? When? How? How will the data be collected?
Do: Implementation of the planned change(s). TIP! It is good to make the change cycles as small as possible, for example, trying a new process on the next five patients being seen by one provider as opposed to wide scale implementation of a new chart documentation form across an entire clinic.
Study (or check): Once the small test of change is tried, its results are assessed. How many times did the process work as planned for the five patients included in the cycle?
Act: Based upon the results of the study of the cycle, recommendations are made as to what the next steps ought to be to achieve the goal. At this point, the cycle then resumes and planning begins for the next cycle.
Over the course of an improvement effort, multiple tests of change might be implemented for any or all of the process measures felt to be likely to impact the outcome measures relevant to the project.
The MFI has been used by improvement teams across numerous health care settings around the world. Further information about the model and examples can be found at www.ihi.org/openschool, or in The Improvement Guide (Langley et al).
The IHI Open School modules are an excellent online resource for clinicians interested in learning more about the fundamentals of quality improvement and patient safety. These educational lessons are free of charge to health professional students, residents, and university faculty members, and for a modest subscription fee to other clinicians. They are also free to health care practitioners in the developing world. An excellent original resource on implementing this model in clinical practice is in Berwick’s summary article from 1998.
DM. Developing and testing changes in delivery of care. Ann Intern Med 1998;128:651–656
L: The Improvement Guide: AIM Model for Improvement. San Francisco, CA: Jossey-Bass; 2009:24.
D: Model for Improvement—Part Two: Measurement and feedback for quality improvement efforts. Pediatr Clin North Am 2009;56(4):779–798
Also grounded in industrial engineering, an increasingly popular method for driving improvement efforts in health care settings is “Lean” or “Lean processing.” Early thinking about Lean processes is credited to the Toyota Manufacturing Company in Japan. The crossover to health care from manufacturing is a relatively recent phenomenon, but numerous hospitals and health care delivery settings, including individual clinics, have benefited from the application of these principles to their clinical operations. Lean improvement methods focus on reducing errors and variability in repetitive steps that are part of any process. In health care, examples of repeated processes would include how patients are registered and their information obtained; how medications are ordered, compounded, distributed, and administered; how consent forms are accurately completed in a timely manner prior to surgical procedures; and how antibiotics are reliably and efficiently delivered prior to surgical procedures.
Lean is a philosophy of continuous improvement. It is grounded in recognizing that the way we do things today is merely “current state.” With time, effort, focus, and long-term thinking, we can create a “future state” that is better than the status quo. It does so by focusing on identifying the value of all steps in any process and eliminating those steps that do not contribute to the value sought by the customer, or in health care, the patient/family. In doing so, improvements in outcomes, including cost and productivity, and in clinical measures of effectiveness can be realized. See Young for an early critical assessment of the incorporation of Lean into health care settings.
There are four categories that describe the essential elements of Toyota’s adoption of “Lean” as a management strategy. These four categories are: (1) philosophy (emphasize long-term thinking over short-term gain); (2) process (eliminate waste through very defined approaches including an emphasis on process flow and the use of pull systems to reduce overproduction, for example); (3) people/partners (respect, challenge, and grow staff); and (4) problem solving (create a culture of continuous learning and improvement).
There are a number of hospitals that have fully integrated Lean management as a primary basis for its organizational approach to improvement. Several were featured in a “White Paper” published by the IHI in 2005.
Liker: The Toyota Way. Madison, WI: McGraw-Hill; 2004.
SI: A critical look at Lean Thinking in healthcare. BMJ Qual Saf Health Care 2008;17:382–386
A third quality-improvement methodology also arose in the manufacturing industry. Motorola is generally credited with promoting Six Sigma as a management strategy designed to reduce the variability in its processes and thereby reducing the number of defects in its outputs. Organizations adopting Six Sigma as an improvement strategy utilize measurement-based strategies that focus on process improvement and variation reduction to eliminate defects in their work and to reduce cycle times, thereby increasing profitability and enhancing customer satisfaction. Sigma is the statistical measure of standard deviation and Motorola adopted Six Sigma as a performance indicator, promoting consistency of processes in order to have fewer than 3.4 defects per million opportunities. This performance goal has since become the common descriptor for this approach to improvement both in manufacturing and in service industries, including health care. Similar to Lean, the translation of business manufacturing strategies into health care has various challenges, but there are many processes that repeatedly occur in health care that can be routinized and made more consistent. Many health care processes fail far more frequently than 3.4 times per million opportunities. Consider pharmacy dispensing errors, medication ordering or administration errors, and patient-scheduling errors, just to name a few. These are a few of many examples of processes that could potentially benefit from the kind of rigorous analysis that is integral to the Six-Sigma approach.
In a typical Six-Sigma structured improvement project, there are five phases generally referred to as DMAIC: (1) Define (what is the problem, what is the goal?), (2) Measure (quantify the problem and improvement opportunity), (3) Analyze (use of observations and data to identify causes), (4) Improve (implementation of solutions based on data analysis), and finally, (5) Control (sustainable change).
One of the central aspects of Six Sigma as an improvement strategy is its defined focus on understanding the reasons for defects in any process. By understanding these drivers, it is then possible to revise the approach to either the manufacturing process or the service functions in order to reduce these errors and failures.
“Lean-Six Sigma” is a newer entity that draws from both methodologies in order to simplify the improvement work where possible, but retain the rigorous statistical method that is a hallmark of Six-Sigma projects. Lean focuses on where time is lost in any process and can identify opportunities to eliminate steps or reduce time. Six Sigma aims to reduce or eliminate defects in the process, thereby resulting in a higher quality product through a more efficient and lower cost process.
Regardless of the method used, improvement happens because an organization, team, or individual sets a goal to improve a current process through systematic analysis of the way things are done now, and then implementing planned changes to see how they impact the outputs or outcomes.
For additional information on Lean and Six Sigma, see www.isixsigma.com or www.asq.org/sixsigma.
L: What Is Six Sigma? New York, NY: McGraw-Hill; 2002.