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Related Concept Videos

Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Correlation and Causation01:27

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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
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Correlation01:09

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
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Reaction Rate02:53

Reaction Rate

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The rate of reaction is the change in the amount of a reactant or product per unit time. Reaction rates are therefore determined by measuring the time dependence of some property that can be related to reactant or product amounts. Rates of reactions that consume or produce gaseous substances, for example, are conveniently determined by measuring changes in volume or pressure.
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Related Rates01:18

Related Rates

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When two or more physical quantities are linked by a single relationship, a change in one variable necessarily affects the others. This interdependence forms the basis of related rates analysis, which examines how different quantities change with respect to time. A classic physical example is an expanding balloon, where the size of the balloon changes continuously as air is added.For a hot air balloon, the inflated envelope is commonly idealized as a perfect sphere to simplify mathematical...
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Speciation Rates01:07

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Intermediate Strain Rate Material Characterization with Digital Image Correlation
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Proprietary management and higher readmission rates: A correlation.

Manish Mittal1,2, Chih-Hsiung E Wang2, Abigail H Goben3

  • 1Department of Pharmacology, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America.

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Proprietary hospitals show higher patient readmission rates compared to government and non-profit facilities. This difference persists across major diseases, impacting healthcare quality and costs for Medicare beneficiaries.

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Area of Science:

  • Healthcare Management
  • Health Services Research
  • Public Health Policy

Background:

  • Reducing preventable hospital readmissions is crucial for controlling rising healthcare costs and enhancing patient care quality for Medicare beneficiaries.
  • Previous initiatives to lower readmission rates have been hampered by poorly defined quality metrics, inadequate data collection, and a lack of data-driven strategies.

Purpose of the Study:

  • To investigate the relationship between hospital ownership structure and patient readmission rates.
  • To analyze readmission data across six major diseases within the context of the Medicare Readmissions Reduction Program (HRRP).

Main Methods:

  • Analysis of patient readmission data from the HRRP program (2012-2015).
  • Comparison of readmission rates across different hospital ownership types (proprietary, government, non-profit).
  • Inclusion of six major diseases: acute myocardial infarction (AMI), heart failure (HF), coronary artery bypass graft (CABG), pneumonia (PN), chronic obstructive pulmonary disease (COPD), and total hip/knee arthroplasty (THA/TKA).

Main Results:

  • Readmission rates were statistically higher in proprietary (for-profit) hospitals compared to government and non-profit hospitals.
  • This disparity in readmission rates was observed across all six major diseases studied.
  • The findings were independent of the hospitals' geographical distribution.

Conclusions:

  • Hospital ownership structure is a significant factor associated with patient readmission rates.
  • Policy makers should consider the implications of hospital ownership on patient care quality, particularly concerning revenue pressures in proprietary institutions.