Why Data Collection is a Necessary Part of Quality Improvement

Posted March 14, 2017 by Josh Grant

QI Tips: The Importance of Data
Data provides key insights the progression of change and improvements. 

Data and data collection occur at every phase of a quality improvement (QI)  initiative, and ultimately shape the progress and outcomes of the work. The information is both a catalyst for change and a result of it, making it a crucial element that can’t be ignored at any point.

Learning how data touches different points of QI work provides a clearer understanding of its importance for success.

Baselines and Context at the Beginning
Data collection is the beginning step in making any type of improvement. The best way to identify areas to change that lead to better outcomes for end users is to see where the pain points are and what practices could be more efficient. Without this first step a QI initiative would start with assumptions about what needs to change, which aren’t usually correct.

Once areas for improvement are defined, the collected data becomes baseline measures that provide context for progress over time. These are essentially the barometer that allow teams to understand what change ideas are beneficial and what one needs need to be refined to reach the intended outcomes.

Evaluating Routine Tests
Because every QI initiative relies on small tests of change, frequent data collection is a necessary step for full evaluation. Whether a new idea is part of the first Plan-Do-Study-Act (PDSA) cycle or the 30th, the data produced by the test is the insight that teams need in order to determine their best path forward.

Evaluation and analysis are the “S” (Study) in PDSA. The outcomes of every test should influence what happens next. Uninformed choices not based on data likely will not yield further progress and may actually lead to regression.  

After an Initiative
Even as QI work itself winds down, data should still be collected to monitor the long-term impact of system changes. The larger sample size and additional time show just how much of a difference has been made compared to previous weeks, months and even years. This long-term data is also good background data to have ready for future QI initiatives, especially when it comes to engaging leadership.

QI isn’t about making change for the sake of it or following mere instincts. It’s about choosing the right areas for improvement and determining strategic paths forward. And that’s just part of where data comes in. 

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