Related Experiment Video
Updated: Jul 4, 2026
05:37
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Supply-side risk adjustment and outlier payment policy
Michel Mougeot1, Florence Naegelen
1University of Franche-Comte, CRESE, Besançon Cedex, France. michel.mougeot@uiv-fcomte.fr
Journal of Health Economics
|July 4, 2008
Summary
In prospective payment systems, outlier payments cover high hospital costs. The optimal outlier payment is based on realized costs when hospitals exert maximum cost reduction effort, regardless of patient severity.
Area of Science:
- Health economics
- Healthcare management
- Public health policy
Background:
- Prospective payment systems (PPS) are common in healthcare.
- Outlier payments are designed to manage unusually high hospital costs within PPS.
- Hospital cost reduction efforts are often made before patient severity is known.
Purpose of the Study:
- To determine the optimal structure of outlier payments in PPS.
- To analyze the impact of pre-determined cost reduction efforts on outlier payment design.
- To provide a framework for efficient hospital reimbursement under uncertainty.
Main Methods:
- Theoretical modeling of hospital incentives.
- Analysis of cost reduction effort and patient severity.
- Derivation of optimal outlier payment rules.
Main Results:
- The optimal outlier payment should be based on the hospital's realized cost.
- This optimal payment applies when the hospital exerts its highest level of cost reduction effort.
- The finding holds true irrespective of the patient's specific severity.
Conclusions:
- Outlier payment policies can be simplified under certain conditions.
- Aligning payments with efficient effort levels can improve healthcare system performance.
- This model offers insights for designing equitable and efficient reimbursement strategies.
Related Concept Videos
01:12What 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...
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
01:08Outliers 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 vertical...
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
01:00Detection of Gross Error: The Q Test
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
01:30Health Information Technology and Healthcare Information System
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
01:02Quantifying and Rejecting Outliers: The Grubbs Test
Sometimes, a data set can have a recorded numerical observation that greatly deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier. To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...