Related Experiment Video
Updated: Feb 11, 2026
Retzius-Sparing Robot-Assisted Radical Prostatectomy
Published on: May 19, 2022
[Incidence of incontinence after radical prostatectomy using claims-based data]
M H J Schepens1, C M P Ziedses des Plantes, D M Somford
1Zorgverzekeraars Nederland, Zeist.
Objective:
To determine the effect of radical prostatectomy (RP) hospital volume on the probability of post-RP incontinence.
Design:
Retrospective research based on claims-based data of health insurers.
Method:
For every patient with RP the probability of incontinence was determined, based on the definition of claims of one or more incontinence pads per day. Casemix corrections were made based on indicators available in claims-data: age, lymph node dissection, and radiotherapy. No casemix corrections could be made for tumour stage and surgical technique.
Results:
A total of 1590 patients were included in this study; for 26.0% of these patients, an average of one or more incontinence pads per day were claimed for. A significant relation between the volume of RP per hospital and the claims of incontinence material was observed. The probability of incontinence was significantly lower in hospitals with a volume of more than 100 RP patients per year when compared to hospitals with less than 100 RP patients per year.
Conclusion:
The probability of post-RP incontinence decreases as hospitals conduct more RP procedures. The casemix factors included in the analysis only had a limited impact on this observation.
More Related Videos
Related Concept Videos
01:08Prevalence and Incidence
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
01:11Testing a Claim about Mean: Known Population SD
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...
01:24Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
01:19Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
01:21Testing a Claim about Mean: Unknown Population SD
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
01:16Radical Reactivity: Nucleophilic Radicals