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Related Concept Videos

P-value01:10

P-value

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P-value is one of the most crucial concepts in statistics.
P-value stands for the probability value.  P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to  not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...
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Decision Making: P-value Method01:09

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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...
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Retrieval01:12

Retrieval

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Retrieval is the process of getting information out of memory storage and back into conscious awareness. This ability is essential for daily tasks like brushing hair and teeth, driving to work, and performing job duties. Retrieval occurs in three ways: recall, recognition, and relearning.
Recall involves accessing information without cues, such as during an essay test, where individuals must retrieve facts and concepts from memory unaided. Another example is remembering the name of a colleague...
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The Intermediate Value Theorem01:25

The Intermediate Value Theorem

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The Intermediate Value Theorem is a foundational result in calculus that guarantees the existence of solutions within certain intervals for continuous functions. Formally, the Intermediate Value Theorem states that if a function f is continuous on the closed interval [a, b], and if N is any value between f(a) and f(b), then there exists at least one c ∈ (a, b) such that f(c) = N. This theorem is instrumental in proving the existence of roots and in analyzing the behavior of continuous...
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Critical Values01:31

Critical Values

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A critical value is a definite value obtained from a particular probability distribution at a predecided confidence level (or a predecided significance level) for a given population parameter. The critical value provides demarcation that separates the sample statistics that are likely to occur from the ones that are unlikely to occur based on the given probability distribution and the population parameter to be estimated. The critical value for normal distribution is obtained from the z...
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Expected Value01:15

Expected Value

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The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
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Orienteering as a Tool for Cognitive Research: An Implementation Guide
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IN SEARCH OF VALUE.

Howard Larkin

    Trustee : the Journal for Hospital Governing Boards
    |April 30, 2016
    PubMed
    Summary

    Defining health care value is complex, with incomplete and conflicting measurements. Despite these challenges, some healthcare systems are actively pursuing value-based initiatives.

    Area of Science:

    • Health Services Research
    • Healthcare Management
    • Health Economics

    Background:

    • Defining and measuring value in healthcare presents significant challenges.
    • Existing metrics for healthcare value are often incomplete or contradictory.

    Purpose of the Study:

    • To explore the ongoing efforts of healthcare systems in defining and implementing value-based care.
    • To understand the drivers and strategies employed by healthcare systems despite measurement difficulties.

    Main Methods:

    • Qualitative analysis of healthcare system initiatives.
    • Review of current value measurement frameworks.
    • Case study approach to selected healthcare systems.

    Main Results:

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  • Healthcare systems are actively engaged in value-based care implementation.
  • Diverse strategies are being employed to define and measure value.
  • Progress is being made despite acknowledged measurement limitations.

    • Conclusions:

    • Healthcare systems are demonstrating commitment to value-based care.
    • Innovation in measurement and implementation is occurring concurrently.
    • The pursuit of healthcare value continues despite inherent complexities.