When the QI team is assembled and prepared to integrate quality improvements into its organization, the focus then becomes the actual implementation. This section describes QI processes at a high operational level. The content is intended to provide answers for these reflection questions, as an organization makes specific decisions about what it wants to improve and how to actually accomplish the work:
In a health care organization, team members may suggest multiple areas that need ongoing measurement or improvement. The first task is to focus on one or more improvement areas, but it is recommended that no more than a few be selected. The following may be considered during the process of selecting opportunities for improvement:
An organization's processes that are weighted more heavily for improvement have one or more of the following characteristics:
Brainstorming is a valuable approach for generating ideas on additional opportunities for improvement. When performed in a structured manner, in a lively roundtable session led by a facilitator, it allows ideas to flow freely without debate or judgment. Subsequently, the ideas are reviewed, discussed, and clarified. During this stage, ideas are considered based on their projected time and resource requirements. Data collection efforts that may involve staff members outside the team are also taken into account. Then the team members rank and prioritize the areas based on organizational goals and needs, and a list of areas for improvement is identified.
For most teams, choosing improvement opportunities is an iterative process. After an organization creates a prioritized list using the methods described, it performs as many areas as feasible, considering the reality of its available resources and organizational constraints.
Data Infrastructure, Monitoring, and Evaluation
The first principle, QI Work as Systems and Processes, discussed in Part 1: Principles of QI, involves changes to the health system to improve performance. As patient outcomes may be affected, an organization wants to ensure that changes applied are true improvements. An effective way to accomplish this is to apply the fourth principle, Focus on Use of the Data.
An organization may already have existing data to track improvement. It needs to monitor the data that accurately reflects how a particular system is functioning, which requires an organization to focus on specific and well-defined data sets when monitoring QI.
To know which data to use and how to use it, understanding these three related concepts is important. The terminology for the concepts is introduced here, and more detail can be found in the Performance Management and Measurement module.
Used together, these three concepts form the basis for a QI data infrastructure. An organization should choose performance measures that reflect the care system targeted for improvement, and then set up a data collection system to document its performance. After the data is collected, then an organization analyzes the performance data and acts on that information. The ongoing process of collecting data, analyzing the data, introducing change based on that analysis, and again collecting data, is referred to as the improvement cycle.
Before choosing performance measures, a QI team first reviews its organizational topics of interest, as discussed in the previous section, What Are the Desired Improvements? In addition, it needs to consider parameters specific to its organization, such as, resources, constraints, and the population served. Good performance measures are always:
Once measures are identified, an organization then determines its data collection frequency and sampling. More frequent data collection allows an organization to focus its QI efforts more aggressively. Monthly data collection is suggested, but collection on a quarterly basis is adequate, if necessary. A more advanced discussion on data collection and sampling considerations can be found in the Managing Data for Performance Improvement module.
An organization's processes and procedures needs to be established for consistent reviews and analyses of the performance measurement data by the staff. The data is analyzed to identify trends and progress toward an organization's goals. This type of analysis also identifies opportunities for improvement, allowing the QI team to focus its efforts and ensure that system changes result in improvement. Additional information, including tools and resources to assist an organization with data analysis, can be found in the Managing Data for Performance Improvement module.
QI is a method for continuously finding ways to provide better patient care and services, and at its core, QI is a team process. Most QI initiatives benefit from having a team of individuals who are focused and accountable for clearly-defined improvement aims. Under the right circumstances, a team applies the knowledge, skills, and perspectives of different individuals to make lasting improvements. A diverse QI team is even more effective, because its members bring their varying backgrounds, viewpoints and experiences to the QI process. A small QI team of six or fewer members also works well and is easier to manage. When recruiting new members for a team, selecting enthusiastic members who are interested in QI produces better outcomes. In a smaller organization, it is common for one individual to fill multiple roles on the QI team. A more advanced discussion on developing a QI team can be found in the Improvement Teams module.
After an organization identifies opportunities for performance improvement through data analysis, it then can make changes to the underlying system targeted for improvement. Using quality improvement (QI) models, either alone or in combination, is an effective approach for categorizing potential changes to an organization's system, and identifying changes that worked in other similar settings. QI models help an improvement team to focus on changes that have already proven to be effective, and they also provide guidance on different ways to approach change. This section provides a brief introduction to specific models that many health care organizations use to successfully shape their quality program infrastructures and guide their QI activities to improve care for their patients.
Introduction to QI Models
There are a variety of QI models currently in use and five are highlighted here. Two of the models highlighted, Care Model and Lean Model, provide a framework to improve patient care. The other three models, Model for Improvement, FADE, and Six Sigma, focus on processes that monitor the results of measures:
Note: Experts are beginning to combine Six Sigma and Lean models into the one term, Lean Six Sigma. This is because they both require a focus on analyzing processes, and use mapping as a means to achieve improvement.
While it is not essential for an organization to understand all of the QI models listed in this module, a thorough understanding ensures a more versatile approach to QI. Each QI model and method offers a systematic approach for assessing and improving care services.
Improvement requires change, but not every change is an improvement. The approach used by most organizations is to adopt a strategy for managing change and train their staff to facilitate the improvement process. There are a number of change processes being used, including:
All of these change strategies have pros and cons and work under certain situations. When dealing with the high stakes of clinical care, a prudent approach has gained popularity with QI teams around the globe. The Model for Improvement is a strategy to systematically and effectively manage change, which stemmed from the work of William Edwards Deming, also known as the founder of continuous QI. The model has two parts, which are depicted in Figure 3.1: Model for Improvement:
Note: Testing changes is an iterative process: the completion of each test cycle leads directly into the start of the next cycle. A team learns from the test; i.e., What worked and what didn't work? What should be kept, changed, or abandoned? The team uses the new knowledge to plan the next test, and continues linking tests in this way, refining the change until it is ready for broader implementation.
**It is important to note that the Model for Improvement, and associated techniques for small changes tested over time, is strongly encouraged as a change methodology.
Tips for Testing Changes
The following suggestions may be used for effectively testing changes:
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