Quality Improvement

What is quality?
The Institute of Medicine defines quality as the “degree to which healthcare services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge.” (1)  Six dimensions of healthcare quality are identified that can be used as means for deciding on areas for improvement.

Dimension Meaning
Safe avoiding harm to patients from care that is intended to help them
Effective providing services based on scientific knowledge to all who could benefit, and refraining from providing services to those not likely to benefit
Patient-centred providing care that is respectful of and responsive to individual patient preferences, needs, and values, and ensuring that patient values guide all clinical decisions.
Timely reducing waits and sometimes harmful delays for both those who receive and those who give care
Efficient avoiding waste, including waste of equipment, supplies, ideas, and energy
Equitable providing care that does not vary in quality because of personal characteristics such as gender, ethnicity, geographic location, and socioeconomic status.


What is quality improvement?
Quality improvement (QI) has been described as “an organised system to continually improve processes, outcomes, and service, regardless of prior excellence, in order to be the best we can be.” (2) It involves developing theories for change, testing them, measuring their impact with data that is collected in “real time,” and refining theories of change using an iterative, trial and learning methodology e.g. PDSA (Plan, Do, Study, Act) cycles. It requires training in QI methodology, an improvement team who know the work involved because they are the ones doing the work, feedback through data, usually in the form of run charts, and support from improvement experts. Changes are tested, over time, and, if appropriate, in different environments, to build knowledge of the system, before they are implemented.
Quality improvement has also been described as a “complex social intervention.” (2) Improvement efforts are rarely straightforward, linear, “before and after” processes but can fluctuate, vary over time, and are dependent on context.

  1. Crossing the quality chasm : a new health system for the 21st century. Washington, D.C. ; [Great Britain]: National Academy Press, 2001.
  2. Walshe K. Understanding what works–and why–in quality improvement: the need for theory-driven evaluation. International journal for quality in health care : journal of the International Society for Quality in Health Care / ISQua 2007;19(2):57-9.


How does quality improvement differ from audit?
Audits tend to look at (often large amounts of) historical data to evaluate whether a standard has been met. They are useful for quality assurance to see if we are compliant with a given standard. These standards are often set by professional bodies or external regulators. If an audit demonstrates that we are not compliant with a standard, then the approach may vary from “repeat the audit next year” when it will be mandatory to do so, or by developing a change, and then re-auditing. Whilst audit may sometimes be a useful driver for change, it can sometimes become a tickbox exercise – “audits of audits” suggest that many are never completed or re-audited. This is not to diminish the role of audit altogether – it may be necessary to audit performance and standards, but quality improvement differs from a completed audit cycle in many ways:

  • Quality improvement is not mandatory, does not need to be based on a standard and may even be based on a hunch e.g. “What if all Gledhow wards arranged equipment for venepuncture and cannulation identically? Would we save doctors’ time?” If you were going to test this theory for a quality improvement project, you may wish to start on just one ward to test feasibility and may also wish to record the effects on workload for staff who organised the equipment room. “What if we saw our outliers first? Would patients be discharged from hospital sooner?” It’s possible that this may or may not occur, and you would have to balance this against the effects on seeing your base ward patients later.
  • Aims for quality improvement are normally set by the team doing the improvement rather than an external agent. This means that you won’t get punished or admonished for not achieving your target, and it something that the team doing the improvement agree is important
  • Measurement for quality improvement usually involves frequent (often weekly) small scale data collection, usually collected by the team doing the improvement work. Collecting data from even a small sample of patients on a regular basis enables you to see the effect of changes in real time rather than retrospectively (when it can sometimes be difficult to identify what caused a change) and build up a picture of a system over time. This is more effective than collecting two large before and after samples of data. (This is covered in more detail in the measures session in our Introduction to Quality Improvement Course)
  • Quality improvement involves continuous, repeated, iterative tests of change to build knowledge of what works (and what doesn’t) in the context of where the improvement efforts are taking place

This isn’t to say audit doesn’t have a role. It does. It is often necessary to assure ourselves that we are doing what we are supposed to. Audit can also be used to develop a QI project and may sometimes be used as part of a QI project.


The Model for Improvement
The Model for Improvement is made up of a set of three fundamental questions that drive improvement efforts and the PDSA cycle.

  • What are trying to accomplish?
  • How will we know that change is an improvement?
  • What change can we make that will result in improvement?

It has its roots in industry but has been used widely across the world to drive improvement in healthcare. The three questions are outlined in this diagram. They cover forming a team, setting aims, choosing appropriate measures, selecting and testing changes and evaluating the effectiveness of changes through repeated PDSA cycles. Changes are typically tested on a small scale, to build knowledge and confidence that they work before they are implemented on a larger scale.