#QualityImprovement and #PDSA cycles - how to decide what to DO

Plan Do Study Act (PDSA) cycles are a quality improvement tool used to test process change. Not all change leads to improvement. In order to evaluate the change for its impact on your patients and the care you provide them, you need to test the change.

The Institute for Healthcare Improvement (IHI) uses the Model for Improvement developed by Associates in Process Improvement. Both sites provide resources for using this method, including this worksheet from IHI.

To summarize briefly, the process requires you to develop a PLAN for how you will test the change including how you will measure the change. Then you will DO the change in a small scale or pilot, measuring the outcome before and after implementing the change. After completing the pilot, you will STUDY the results of your test by carefully examining the before and after measurement. Finally, you ACT on what you learned, generally through modifying and re-testing the new change in a new PDSA cycle. You repeat until you are convinced that the change consistently creates more benefit than harm, which constitutes improvement.

There are many great resources on many different websites to help guide you in the PDSA process.

But the biggest challenge for you will be deciding WHAT to do.

STEP 1 - Know your organization’s most pressing problems. Hint - start with your data. Data includes your performance metrics, but it also includes your survey data from patients and staff.

STEP 2 - Prioritize - No organization has enough resources to change everything at once. Besides exhausting your staff, you’ll also contaminate your tests of change. When you change everything at once, you can’t determine which change produced the improvement, if there was improvement. And changing everything at once may produce no overall improvement, hiding real improvement that could be generated from one of the changes.

STEP 3 - Find evidence based innovations to address your priority problems. If you use innovations that have already been tested and found to work, you will have a head start. You will waste less time with more PDSA cycles and you are more likely to reduce unintended harm to your patients and staff from the change.

All this is necessary for successful PLANing of what to DO.

In the next post I’ll dig deeper into the process of how to decide what to do.

 ©TheEvidenceDoc 2018

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

 

 

Who is driving #populationhealth

What is population health management anyway? The short answer is, it depends on who you ask. There are many players in the population health space right now and their differing approaches and agendas are driving the confusion.

Why the sudden interest? In the US, healthcare is beginning a gradual change from its current focus on treating a single disease to helping whole people maximize their state of health and well being, and ultimately to helping whole groups of people be their healthiest. To do that we must improve the health status of people across the entire health spectrum, from preventing disease, through early disease detection, to managing the consequences of disease.

To help you understand the many drivers of interest in population health management, I created this diagram.

This diagram isn’t meant to add to your confusion but to explain some of the cause of the confusion. Let’s start on the right side of this slide, and I’ll describe each of the drivers and a little of their role.

So the many different drivers with their different goals is the reason you hear so many different definitions and buzzwords associated with population health management. These represent different pieces of the population health management puzzle. And organizations are choosing to focus on different parts of the puzzle as they approach population health management.

 

If you’d like to learn more about these drivers, you can download a free copy of the chart of Drivers of Interest in Population Health with links to the driver organizations and some of their resources.

TheEvidenceDoc 2016