Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Compensation Mechanisms01:28

Compensation Mechanisms

The human body employs intricate mechanisms to counteract changes in blood pH, preventing conditions like acidosis (pH < 7.35) and alkalosis (pH > 7.45). These compensatory responses aim to restore normal arterial blood pH by engaging respiratory or renal systems, depending on the source of the imbalance.
Respiratory Compensation
This mechanism addresses metabolic-induced pH imbalances by adjusting breathing rates. Respiratory compensation begins within minutes of detecting a pH...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Equity Theory01:26

Equity Theory

Equity theory explains how our sense of fairness influences the dynamics of close relationships. Rooted in social psychology, the theory posits that individuals evaluate fairness by comparing the ratio of their contributions to the rewards they receive. Relationship satisfaction is highest when these ratios are perceived as balanced between partners, promoting mutual reciprocity and a sense of justice.Equity vs. Equality in RelationshipsEquity is distinct from equality. Fairness does not...
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Weighted Mean00:57

Weighted Mean

While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
First Derivative Test: Problem Solving01:25

First Derivative Test: Problem Solving

Imagine an asset price that crashes to a low point, rebounds sharply as bargain-hunters step in, and then gradually declines. Such behavior can be modeled with a smooth function whose turning points represent locally overvalued and undervalued regions. A convenient example that captures rebound followed by decay is:The high and low points of this curve are identified using the first derivative test, which determines where the function changes from increasing to decreasing or vice versa. To...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cephalotaxinone enzymes reveal a whole plant model for homoharringtonine biosynthesis.

Nature chemical biology·2026
Same author

Research integrity and transparency in CAM journals: an analysis of publication bias and reporting practices (1995-2023) in four leading journals.

Research integrity and peer review·2026
Same author

Strengthening the Physician Workforce: An Expert Panel Discussion.

The Permanente journal·2026
Same author

Exploring the potential of naked barley to manage deoxynivalenol accumulation from Fusarium head blight.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2026
Same author

Case Report and Epidemiological Investigation of Healthcare-associated <i>Plasmodium falciparum</i> Malaria Transmission in Westchester County, New York-2023.

Open forum infectious diseases·2025
Same author

Streamlining the Histopathologic Workflow in Diabetic Kidney Disease with Artificial Intelligence.

Journal of the American Society of Nephrology : JASN·2025

Related Experiment Videos

Financial gains and risks in pay-for-performance bonus algorithms.

Jerry Cromwell1, Edward M Drozd, Kevin Smith

  • 1RTI International, Research Triangle Institute, Waltham, MA 02451-1623, USA. jcromwell@rti.org

Health Care Financing Review
|July 16, 2008
PubMed
Summary

Pay-for-performance (P4P) bonuses are sensitive to how disease managers perceive intervention effectiveness and target difficulty, not just indicator weighting or correlation. Understanding these factors is key for effective quality improvement initiatives.

Related Experiment Videos

Area of Science:

  • Health Services Research
  • Healthcare Management
  • Health Economics

Background:

  • Evidence-based process indicators are crucial for assessing quality of care.
  • The structural design and parameters of pay-for-performance (P4P) bonus/penalty systems are less understood.
  • Optimizing P4P models requires analyzing the impact of various design parameters.

Purpose of the Study:

  • To develop a general model for quality payment arrangements.
  • To analyze the advantages and disadvantages of key P4P parameters.
  • To conduct simulation analyses of P4P payment algorithms.

Main Methods:

  • Developed a general model of quality payment arrangements.
  • Conducted simulation analyses of four P4P payment algorithms.
  • Varied seven key parameters, including indicator weights, intercorrelation, intervention effectiveness uncertainty, and baseline rates.

Main Results:

  • Bonuses averaged across multiple indicators showed insensitivity to weighting, correlation, and the number of indicators.
  • Bonus payouts were sensitive to disease manager perceptions of intervention effectiveness.
  • P4P bonus sensitivity was observed with challenging targets and the use of actual-to-target quality levels versus improvement rates.

Conclusions:

  • The design of P4P systems significantly impacts bonus distribution.
  • Disease manager perceptions and target setting are critical factors influencing P4P effectiveness.
  • Future P4P models should carefully consider these parameters for optimal quality improvement.