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Funnel Plots for Assessing Institutional Performance

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posted on 2021-11-13, 11:56 authored by Jennings, Amy

This thesis presents a comparison of maternal outcomes for births in New Zealand District Health Boards (DHBs).This is carried out through analysis of the National Minimum Dataset collected by the Ministry of Health for 2007.  The outcome compared is postpartum haemorrhage (PPH) the results are displayed using funnel plots, a useful tool for displaying unbiased information on performance outcomes when comparing institutions.   Exploration of the data found that there are differences in the demographics, maternal and birth characteristics among DHBs. The rates of PPH are different and the population mixes are made up of a range of different proportions of ethnic groups, ages and deprivation indexes. The exploratory analysis found that a large number of factors are associated with PPH. And that birth weight, parity and gestation had a large number of missing observations. These factors are not missing at random and require imputing prior to constructing the funnel plots.  Results show that there is divergence amongst DHBs in the postpartum haemorrhage rate. First a raw PPH rate was plotted and the results indicated there were differences among DHBs. As there are many potential predictors for PPHa logistic regression model was applied to find the most important factors related to PPH. This allows us to apply an adjusted rate for the funnel plot. The risk adjusted funnel plot also indicated differences among DHBs.  Two approaches are taken to account for the overdispersion. A winsorised estimate and a winsorised estimate with a random effects term are applied to the data. The approaches produced different results. The winsorised estimate widened the control limits and the random effects term narrowed the control limits. All four plots identified an extreme outlier and this was later removed from the analysis and the winsorisation funnel plots were rerun. The influential outlier made a difference and from this we can concluded that 2 out 20 DHBs lie outside the 95% control limits. These two DHBs could be stated as having a very low rate of PPH.


Copyright Date


Date of Award



Te Herenga Waka—Victoria University of Wellington

Rights License

Author Retains Copyright

Degree Discipline

Statistics and Operations Research

Degree Grantor

Te Herenga Waka—Victoria University of Wellington

Degree Level


Degree Name

Master of Science

ANZSRC Type Of Activity code

970101 Expanding Knowledge in the Mathematical Sciences

Victoria University of Wellington Item Type

Awarded Research Masters Thesis



Victoria University of Wellington School

School of Mathematics, Statistics and Operations Research


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