What Is Quality Improvement in Healthcare and How Does It Work?

This blog post is the first in a series on the basics of quality improvement and how to build a cadre of improvement experts to lead this work throughout the healthcare sector. 

Consumers today have access to products and services offered by companies located throughout the world. Similarly, companies have ready access to consumers all around the world. The globally connected market means that consumers and producers have more choices than ever about whom to do business with. Global competition is putting pressure on companies to find new and better ways to meet the needs of their customers, reduce costs, and increase productivity.

These trends are even more applicable in healthcare. With economic growth, increased education levels, and major investments in programs to improve access to care and generate demand for healthcare services, we have seen a major increase in the use of hospital services. The penetration of mobile phone networks in many low and middle income countries surpasses the integration of other infrastructure resources, such as water, electricity, and local internet access. The widespread availability of mobile phone networks has improved access to important health information for populations that have traditionally been underserved. These populations now use this information to make health related decisions about seeking appropriate care and to avoid significant health risks. These changes have led hospitals – both private and public – to prioritize continuous improvement of health services as a necessary and integral part of their business and policy strategies.

So, where does improvement come from? Improvement comes from the knowledge and creative actions of people. Understanding how people gain knowledge is important. Improvement is predicated on change. People have feelings and emotions about how changes will affect them. The psychology of decision making and change are important to creating improvements. The ability to make effective changes to how healthcare services are run has become a matter of survival for hospitals and providers. The rate and extent of improvements to products, processes, and systems directly relate to the nature of the changes that are developed and implemented. One way to develop change is to examine the current system for flaws and opportunities for improvement. Another way to develop a change is to design a new system without consideration of the way things are currently done.

Quality improvement in healthcare requires an approach that will help hospital staff members learn about the systems at work in their hospital and make changes to satisfy better and more consistently the needs of patients. To achieve improvement in a hospital, the staff must understand why improvement is necessary. The staff members that introduce an improvement need to develop a change and test the change before attempting to implement it across the hospital. They also need to have a feedback mechanism to determine if improvement is, in fact, happening. After testing a change on a small scale, learning and refining the change from each test, the staff also needs to know when and how to implement the change as a protocol or routine. This quality improvement strategy replaces the outdated philosophy of mistake detection and fire fighting. This approach to change brings about more rapid and efficient improvement. Although improvement requires change, not all changes are improvements.

PDSAThe test and learn framework for quality improvement is known as the Model for Improvement. This model has two parts. The first part consists of the three fundamental questions that form the basis for improvement:

  1. What are we trying to accomplish?
  2. How will we know that a change is an improvement?
  3. What changes can we make that will result in improvement?

The second part of the Model for Improvement is the Plan Do Study Act (PDSA) cycle. The cycle tests changes in real work settings. The cycle guides the test of a change to determine if the change is, in fact, an improvement.

We sometimes overlook the importance of having an explicit theory about which changes will result in improvement, a theory that we can update over time as we test changes, collect data, and learn about how to make the changes work in our local environments. PDSA cycles should be grounded in a theory about how the system works.

We also need to be open to the idea that some of our theories will be wrong. We want to avoid falling into the confirmation trap where we look only for data that confirm our theories. Collect data that is meaningful. Use data for learning, not judgment.