Variation: A Vexing Problem in Achieving Quality
There are many shining examples of evidence-based best practices with great outcomes in Ontario.
The challenge is the exceptional nature of these practices rather than a consistent standard of excellence and high quality. The quality of care is highly variable across the province.
This is not a problem unique to Ontario nor is it a new issue. Jack Wennberg from Dartmouth College in the United States has been identifying variation for several decades. He has identified wide variations in practice in numerous areas of healthcare and across many parts of the United States. Most of these variations are “unwarranted” – in other words, they are not explained by differences in the patients (age, gender, type of illness, etc.) or other factors.
Let me share one Ontario example. Recently Health Quality Ontario produced a chart highlighting Caesarean section rates across all hospitals that perform this procedure. The chance of a woman who has a low risk pregnancy having a caesarian section might be as low 4.5% or as high as 35.5% depending on which hospital she walks into. This is a staggering variation in just one province.
Variation is not inherently bad. Some variation allows us to better meet the unique needs of the patient. As Al Mulley noted in a 2010 article regarding variation in the UK National Health Service: “If all variation were bad, solutions would be easy. The difficulty is in reducing the bad variation, which reflects the limits of professional knowledge and failures in its application, while preserving the good variation that makes care patient-centred. When we fail, we provide services to patients who don’t need or wouldn’t choose them while we withhold the same services from people who do or would”.
Appropriately reducing variation will lead to safer, more efficient and more appropriate care. It will also help improve access and likely also patient satisfaction. In taking on this challenge to appropriately reduce variation HQO will draw on all facets of the organization: Quality improvement; evidence development; and performance monitoring and reporting. More importantly we will need to work closely with partners across the system to ensure the quality of the data, set targets, and understand what factors might be leading to the variation seen.
This means no multiple babies, baby is head down, no pre-term labour, no pre-existing health issues for the baby or mother, etc.