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Related Concept Videos

Observational Studies01:11

Observational Studies

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Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
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Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Naturalistic Observations02:30

Naturalistic Observations

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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Standard Deviation01:10

Standard Deviation

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The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.
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Mean Absolute Deviation01:13

Mean Absolute Deviation

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The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
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Emerging Adulthood01:27

Emerging Adulthood

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Jeffrey Arnett's concept of emerging adulthood offers a framework to understand the unique developmental stage between adolescence and full-fledged adulthood, generally from ages 18 to 25. This period is marked by extensive exploration and shifts in identity, relationships, and career choices, a process known in psychology as role experimentation. Emerging adulthood reflects the evolving cultural expectations surrounding adulthood and the dynamic process of personal transformation during...
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Related Experiment Video

Updated: Jan 25, 2026

Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
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Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis

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Large observational study on risks predicting emergency department return visits and associated disposition

Charles Huggins1, Richard D Robinson1, Heidi Knowles1

  • 1Department of Emergency Medicine, Integrative Emergency Services, John Peter Smith Health Network, Fort Worth, TX, USA.

Clinical and Experimental Emergency Medicine
|May 1, 2019
PubMed
Summary

Over 6% of patients return to the emergency department (ED) within 72 hours. Homelessness and leaving without being seen predict return visits, while age and primary care access predict disposition changes.

Keywords:
Emergency service, hospitalPatient outcome assessmentReturn visit

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Area of Science:

  • Emergency Medicine
  • Healthcare Outcomes Research
  • Patient Safety

Background:

  • 72-hour emergency department return visits (EDRVs) are a key patient care metric.
  • Predictive risks for EDRVs are known but vary across studies.
  • Differences in risks for related vs. unrelated EDRVs and disposition deviations are understudied.

Purpose of the Study:

  • To compare risk patterns for related and unrelated EDRVs.
  • To identify risks predicting EDRV disposition deviations (EDRVDD).

Main Methods:

  • Retrospective observational study (Sept 2015 - June 2016) of 63,990 patients.
  • Compared demographic and clinical data for related EDRVs, unrelated EDRVs, and no EDRVs.
  • Used multivariate multinomial logistic regression to identify independent risk factors.

Main Results:

  • 4.65% had related EDRVs; 1.80% had unrelated EDRVs.
  • Top risks for EDRV: homelessness, left without being seen, elopement, left against medical advice.
  • Top risks for EDRVDD: geriatric status, lack of primary care physician.

Conclusions:

  • Over 6% of patients experienced EDRVs within 72 hours.
  • Multifactorial risks predict EDRVs.
  • Similar risks were found for EDRVs and EDRVDD.