Detecting and Visualizing Outliers in Provider Profiling Using Funnel Plots and Mixed Effects Models-An Example from

Oliver Hirsch1, Norbert Donner-Banzhoff2, Maike Schulz3

  • 1Department of General Practice/Family Medicine, Philipps University Marburg, Karl-von-Frisch-Str.4, 35043 Marburg, Germany. oliver.hirsch@staff.uni-marburg.de.

Related Concept Videos

What Are Outliers?01:12

What Are Outliers?

Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
5.1K
Outliers and Influential Points01:08

Outliers and Influential Points

An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
6.3K
Arrhenius Plots02:34

Arrhenius Plots

The Arrhenius equation relates the activation energy and the rate constant, k, for chemical reactions. In the Arrhenius equation, k = Ae−Ea/RT, R is the ideal gas constant, which has a value of 8.314 J/mol·K, T is the temperature on the kelvin scale, Ea is the activation energy in J/mole, e is the constant 2.7183, and A is a constant called the frequency factor, which is related to the frequency of collisions and the orientation of the reacting molecules.
The Arrhenius equation can be used...
47.1K
Testing a Claim about Mean: Known Population SD01:11

Testing a Claim about Mean: Known Population SD

A complete procedure of testing the hypothesis about a population mean is explained here.
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
3.3K
Prescription, Nonprescription and Orphan Drugs01:02

Prescription, Nonprescription and Orphan Drugs

Prescription drugs require a prescription from a medical practitioner and can only be obtained from a pharmacy. They have many applications, including treating pain, anxiety, and hypertension.
The misuse and addiction to prescription drugs is a growing problem that can affect people of all age groups, specifically teenagers. This can happen when prescription medications are used in ways not intended by the prescriber, such as taking someone else's prescription or using medication for...
1.3K
Residual Plots01:07

Residual Plots

A residual plot is a statistical representation of data used to analyze correlation and regression results. It helps verify the requirements for drawing specific conclusions about correlation and regression. To obtain the residual plot, first, the residual for each data value is calculated, which is simply the vertical distance between the observed and the predicted value obtained from the regression equation.
When the residual values are plotted against the variable x, it is called a residual...
6.5K