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

Stratified Sampling Method01:16

Stratified Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
Discharge Summary Forms01:31

Discharge Summary Forms

The discharge summary is crucial as it enables a smooth transition from a healthcare facility to a patient's home or another care setting. This critical document facilitates seamless continuity of care, ensuring patients receive the necessary support and attention.
Here's a detailed look at the key components and guidelines for preparing a discharge summary:
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Pharmacokinetics in Pediatric Patients: Drug Excretion01:26

Pharmacokinetics in Pediatric Patients: Drug Excretion

In pediatric medicine, understanding the renal function and drug elimination nuances is crucial for administering safe and effective treatments. Newborns, in particular, display markedly slower renal functions than adults, profoundly affecting how drugs are cleared from their bodies. This slower drug clearance requires clinicians to extend the dosing intervals for many medications to prevent drug accumulation and toxicity while ensuring therapeutic efficacy.One key area where these adjustments...
Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...

You might also read

Related Articles

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

Sort by
Same author

The intersection of place and health: examining the association of social determinants of health and diabetes in children and adolescents in Florida.

BMC public health·2026
Same author

Subtypes and onset of hypertensive disorders of pregnancy and cardiovascular disease within 5 years after delivery.

Frontiers in cardiovascular medicine·2026
Same author

Partnerships With Health Plans to Link Data From Electronic Health Records to Claims for Research Using PCORnet®.

Medical care·2026
Same author

Characteristics of Pregnancy-related Health Events Across Care Settings Nationwide in PCORnet®.

Medical care·2026
Same author

Improving Patient Education Materials for HPV Self-Collection: Insights from Women at High Risk of Developing Cervical Cancer.

Cancer management and research·2025
Same author

Recent Advances in Our Understanding of Electronic Health Record-Based Social Needs Screening and Documentation in Pediatrics.

Academic pediatrics·2025

Related Experiment Video

Updated: Jul 9, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Disenrollment and re-enrollment patterns in a SCHIP.

Elizabeth A Shenkman1, Bruce Vogel, James M Boyett

  • 1University of Florida, Department of Pediatrics, 5700 SW, 34th Street, Suite 323, Gainesville, FL 32608. USA. eas@ichp.edu

Health Care Financing Review
|December 26, 2002
PubMed
Summary

Policy changes to the State Children's Health Insurance Program (SCHIP) reduced child disenrollment by 20%. Factors like child health and family income influenced enrollment and re-enrollment dynamics.

More Related Videos

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish
14:43

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

Related Experiment Videos

Last Updated: Jul 9, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish
14:43

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

Area of Science:

  • Public Health
  • Health Policy
  • Healthcare Access

Background:

  • State Children's Health Insurance Program (SCHIP) is crucial for child healthcare access.
  • Policy modifications can significantly impact program participation.
  • Understanding enrollment dynamics is key to program effectiveness.

Purpose of the Study:

  • To evaluate the effect of four specific policy changes on SCHIP disenrollment and re-enrollment.
  • To analyze how eligibility, premiums, benefits, and re-enrollment waiting periods influence program continuity.

Main Methods:

  • Analysis of disenrollment and re-enrollment data before and after policy implementation.
  • Statistical examination of policy impacts on program participation.
  • Assessment of variations in enrollment based on child health status and family income.

Main Results:

  • A 20 percent reduction in program disenrollment was observed post-policy changes.
  • Policy modifications demonstrated a significant impact on both disenrollment and re-enrollment rates.
  • Child health and family income were identified as significant factors influencing enrollment outcomes.

Conclusions:

  • Policy adjustments in SCHIP can effectively reduce child disenrollment.
  • Targeted strategies considering child health and socioeconomic factors are essential for optimizing program participation.
  • Further research into specific policy impacts can inform future healthcare access initiatives.