Healthcare #qualityimprovement is doing the right things right

 We can improve the quality and safety of the healthcare we deliver to patients.

That’s the premise behind quality improvement and patient safety programs, initiatives and interventions. The study of quality improvement interventions, called improvement science, is relatively new. Improvement science is just beginning to evaluate the performance of the tools and techniques. Many of the techniques such as Plan-Do-Study-Act (PDSA) cycle, Lean, and Six Sigma come from manufacturing and seek to improve efficiency. They seek to improve efficiency by doing things right. 

While it is important to get better at delivering the right care,

it is essential to first know what is the right care to deliver.

The assumption behind many of the manufacturing improvement processes is that we just need to get better at delivering the right care.  But all too often, we honestly don’t know what the right care is.

The right care should provide each person with care that is effective - that is care that improves their life compared to what would have happened had they not sought care.

What may surprise many people, even some working in health care is that many of the clinical actions we consider standard have not been shown to be more effective than other care options or even no care.

Evidence-based care seeks to fill this gap in knowing by:

First, using data to identify what we know

Then, develop and test solutions for what we don’t.

We identify what we know using data. We call the end result of the rigorous collection and critical analysis of all relevant data “evidence–based”. Good evidence–based analysis tells us how much confidence to have in a particular clinical action. Is there enough evidence to be reasonably sure that the clinical action works? Or perhaps there is just enough evidence to make a reasonable guess today that may change when we accumulate more and better data? Or is there simply not enough evidence to make any reasonable guess?

We use the science of evidence-based methods to help us determine which are the right clinical actions to deliver. We use manufacturing improvement processes to help us get better at doing the right things.

If your quality improvement toolbox only includes one or the other set of tools, you aren’t maximizing your effectiveness and efficiency. The incorporation of evidence-based methods can improve the quality of the care you deliver and encourage innovation while managing risk. Infusing your quality improvement innovations with evidence-based methods means you can begin to take more calculated risk. You can put evidence-based methods to work in your organization to identify the right things to do so that your manufacturing improvement tools can help you then standardize and systematize the best care.

 © TheEvidenceDoc 2016



How to use expertise rather than expert opinion in guideline development

Let’s banish the labels “expert” and “expert opinion” and learn how to appropriately use clinical expertise.

Let’s banish the labels “expert” and “expert opinion” and learn how to appropriately use clinical expertise.

So much clinical experience is not recorded, not standardized, but stored in those vast Watson brains of the individual clinicians. Use it, consider it, just don’t blindly accept concepts prefaced with, “in my experience…” as representation of general fact or evidence. The comments are offered as individual experience. Accept them as such and remember the following examples of why individual experiences are often biased.

An allergist friend of mine often complains to me that primary care docs never treat sinusitis long enough or with the right antibiotics. What does he base this opinion on? His clinical experience. He’s in a large group practice with primary care physicians. So he only sees and treats the 1-5% of sinusitis cases that are treatment failures and referred on from their primary care doc. His worldview of sinusitis treatment by primary care is built on a biased sample of patients that reflect the most serious cases. He never sees the 95-99% of cases that resolve on their own or with conservative management of their symptoms.

Similarly, an orthopedic surgeon argues that all patients who come in with knee pain require knee replacement surgery. Once again, her experience is based on a biased sample of patients who have failed all other treatment options and are referred for her surgical services. She misses all the patient successes with trials of exercise.

So if you don’t use experts for their expert opinions, how do you use them?

Use your panel’s expertise to:

  • Refine the clinical question. This will ensure that the questions you seek to answer are relevant to clinicians.
  • Help define the search terms. How many different names are there for the disease, clinical condition, interventions, etc?
  • Help define the inclusion and exclusion criteria for research selection. What populations and interventions will be in and which will be outside of the scope of your evidence review?
  • Help extract data from the studies. They’ll often find relevant data that may not be clearly labeled. And they’ll gain familiarity with the studies and what these studies are really about.
  • Develop recommendations. This is essential to be sure the recommendations are relevant to clinicians and the way they deliver care.