The AURI Cycle

Historically, quality improvement in healthcare has been done on the basis of expert consensus. One of the most supported models in that vein is the Plan-Do-Study-Act cycle endorsed by the IHI. The cycle begins when a quality improvement intervention is identified. Once the intervention is identified, you plan how you will study the effect of the intervention, including data collection methods. The intervention is then enacted and data collection begins in a small sample population. Once data collection is complete, it is analyzed and compared to predictions to identify lessons learned. The intervention is modified based on what was learned, and the cycle is repeated with the modified intervention.

This PDSA process can be extremely costly, time consuming and involve many false-starts. In an era of expanding health information systems, a new model based on Clinical Knowledge Management is possible. Over the last several years, I have developed a new data-driven model; the CKM process, when applied to quality improvement, produces the Analyze-Understand-Redesign-Implement cycle.

I have had many successes using the AURI cycle applied to various QI projects. However, the AURI cycle is only possible when you have a robust health information system in place, and it is continually capturing and classifying data.

Analyze: Retrieve and evaluate data and information to create actionable knowledge with regard to your QI question. This step employs multiple statistical methods and data-analytic approaches.

Understand: The "reality check" of the new knowledge. New knowledge is presented to stakeholders to determine what is feasible and to identify barriers to success.

Redesign: The alteration of current processes, both major and minor, based on the understanding of the new knowledge.

Implement: The education plan, roll-out of new processes, and modifications to the health IT applications to ensure the continued capturing and classification of relevant data. Due to the necessity of altering HIT applications, the QI initiatives often affect a large sample of patients.

The reason large scale interventions and subsequent extensive data collection and analysis is possible is the continuous capturing and classifying of data in robust health information systems. Incorporating the ability for the health IT applications to capture the redesign process into the implementation phase is critical to successful AURI cycles.

Where robust HIS is available, the AURI cycle of quality improvement is a more efficient and cost effective model than the PDSA cycle. However, due to the large number of patients affected, it must be implemented strategically.