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Measures of Central Tendency02:16

Measures of Central Tendency

The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians, "average" is commonly accepted for "arithmetic mean."
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...
Statistical Significance01:37

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
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...
Real Number Operations01:27

Real Number Operations

The concept of real numbers includes all the values that can be represented on a continuous number line. The system began with basic counting values used for enumeration. It later expanded to include values that represent the absence of quantity and opposites of the counting values. When situations required expressing parts of a whole or dividing quantities evenly, values capable of representing such proportions were developed. When written using decimal notation, these values can end or repeat...
Quantifying Work02:30

Quantifying Work

As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.

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Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
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Meaningful dollars.

Crystal Conde

    Texas Medicine
    |August 3, 2011
    PubMed
    Summary
    This summary is machine-generated.

    Texas physician practices find Medicare and Medicaid electronic health record (EHR) incentive payments crucial for covering ongoing EHR system costs, including software maintenance and staff training.

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    Area of Science:

    • Health Informatics
    • Healthcare Management
    • Public Health Policy

    Background:

    • The widespread adoption of Electronic Health Records (EHR) is a key component of healthcare modernization.
    • Government incentive programs aim to facilitate EHR adoption and meaningful use.
    • Physician practices face significant costs associated with implementing and maintaining EHR systems.

    Purpose of the Study:

    • To assess the perceived impact of Medicare and Medicaid EHR incentive payments on Texas physician practices.
    • To understand how these incentive payments are expected to offset the operational costs of EHR systems.

    Main Methods:

    • Survey or interviews with Texas physician practices that have received EHR incentive payments.
    • Analysis of qualitative or quantitative data on cost perceptions and incentive utilization.

    Main Results:

    • Practices anticipate that incentive payments will substantially contribute to covering ongoing EHR expenses.
    • Key cost areas identified for coverage include software maintenance, system upgrades, and staff training.
    • The financial support is viewed as essential for sustaining EHR use and maximizing its benefits.

    Conclusions:

    • Medicare and Medicaid EHR incentive programs are perceived by Texas physicians as vital for managing the financial burden of EHR systems.
    • These incentives play a critical role in the long-term sustainability of EHR adoption and utilization in physician practices.