Boating Beyond Simple Shewhart Model 11

Destinations Purpose—To provide a quick long distance view. Content –Time or observations between events (g, h, t charts). –CUSUM and EWMA –Following a panel of patients Small Multiples (Thanks to Jerry Langley) Problem of changing denominators. –Comparing beginning and ending performance Prevalence difference vs. Percent Improvement Scatterplots –Smoothed Curves vs. Control Charts

Analyzing Rare Events Using Time or Occurrences Between Them

One way to analyze rare events

Another way to analyze rare events

t and g chart summary t-chart measures the time between events g-chart measures the number of incidents (procedures, admission) between events Both charts are useful when looking at rare events –Eliminates the need to wait for a long time period to collect enough data points

CUSUM and EWMA Early detection of shifts

Anatomy of a CUSUM chart

Monitoring CO 2 in a Nursery CUSUM Chart

Or, you can use an exponentially weighted moving average chart. SurgeriesDeaths Source: Benneyan, 2001

CUSUM vs. EWMA CUSUMEWMA Y-axis Cumulative sum of the difference between the observed mean and the target or average. Avg. of surrounding values, weighting close values very high and far away values very low (exponential weighting). X-axis Measurement number (observation). Time interval. Advantage Detects small shifts More sensitive than EWMA. Partially immune to autocorrelation. Detects small shifts. Partially Immune to autocorrelation. Easier to understand than CUSUM

Following a Panel of Patients

Small Multiple Graphs Denominator in blue Screening rate in red Rate (Percent) Denominator Month

Small Multiple Graphs Think-Pair-Share Why are they powerful? What are their limitations?

An Alternative: Percent of Patients Screened for Depression: A Period-Cohort Analysis. A cohort is a group of patients empanelled within a particular quarter.

Summarizing beginning and ending results

Compare to change in percent screened

Scatter plot comparing beginning and ending of period of observation.

Control Charts vs. Smoothed, Descriptive Data

Compare to corresponding c-Chart

Your Turn! 1.Think about your work and select a key quality characteristic (KQC). 2.Develop an operational Definition for the KQC. 3.Evaluate your definition with the criteria from the NQF in module 2. 4.Answer: What kind of chart or analysis would you use?